Version 2.8.0-alpha Mar 25, 2024

1. Format Overview

1.1. Namespace – NWB core

• Description: NWB namespace

• Name: core

• Full Name: NWB core

• Version: 2.6.0-alpha

• Authors:

  • Andrew Tritt

  • Oliver Ruebel

  • Ryan Ly

  • Ben Dichter

  • Keith Godfrey

  • Jeff Teeters

• Contacts:

  • ajtritt@lbl.gov

  • oruebel@lbl.gov

  • rly@lbl.gov

  • bdichter@lbl.gov

  • keithg@alleninstitute.org

  • jteeters@berkeley.edu

• Schema:

  • namespace: hdmf-common

  • doc: This source module contains base data types used throughout the NWB data format.

  • source: nwb.base.yaml

  • title: Base data types

  • doc: This source module contains neurodata_types for device data.

  • source: nwb.device.yaml

  • title: Devices

  • doc: This source module contains neurodata_types for epoch data.

  • source: nwb.epoch.yaml

  • title: Epochs

  • doc: This source module contains neurodata_types for image data.

  • source: nwb.image.yaml

  • title: Image data

  • doc: Main NWB file specification.

  • source: nwb.file.yaml

  • title: NWB file

  • doc: Miscellaneous types.

  • source: nwb.misc.yaml

  • title: Miscellaneous neurodata_types.

  • doc: This source module contains neurodata_types for behavior data.

  • source: nwb.behavior.yaml

  • title: Behavior

  • doc: This source module contains neurodata_types for extracellular electrophysiology data.

  • source: nwb.ecephys.yaml

  • title: Extracellular electrophysiology

  • doc: This source module contains neurodata_types for intracellular electrophysiology data.

  • source: nwb.icephys.yaml

  • title: Intracellular electrophysiology

  • doc: This source module contains neurodata_types for opto-genetics data.

  • source: nwb.ogen.yaml

  • title: Optogenetics

  • doc: This source module contains neurodata_types for optical physiology data.

  • source: nwb.ophys.yaml

  • title: Optical physiology

  • doc: This source module contains neurodata_type for retinotopy data.

  • source: nwb.retinotopy.yaml

  • title: Retinotopy

1.2. Type Hierarchy

• Container

  • CSRMatrix

  • DynamicTable

    • AlignedDynamicTable

      • IntracellularRecordingsTable

    • ExperimentalConditionsTable

    • IntracellularElectrodesTable

    • IntracellularResponsesTable

    • IntracellularStimuliTable

    • PlaneSegmentation

    • RepetitionsTable

    • SequentialRecordingsTable

    • SimultaneousRecordingsTable

    • SweepTable

    • TimeIntervals

    • Units

  • NWBContainer

    • Device

    • ElectrodeGroup

    • ImagingPlane

    • IntracellularElectrode

    • LabMetaData

    • NWBDataInterface

      • BehavioralEpochs

      • BehavioralEvents

      • BehavioralTimeSeries

      • ClusterWaveforms

      • Clustering

      • CompassDirection

      • CorrectedImageStack

      • DfOverF

      • EventDetection

      • EventWaveform

      • EyeTracking

      • FeatureExtraction

      • FilteredEphys

      • Fluorescence

      • ImageSegmentation

      • Images

      • ImagingRetinotopy

      • LFP

      • MotionCorrection

      • Position

      • PupilTracking

      • TimeSeries

        • AbstractFeatureSeries

        • AnnotationSeries

        • DecompositionSeries

        • ElectricalSeries

          • SpikeEventSeries

        • ImageSeries

          • ImageMaskSeries

          • OnePhotonSeries

          • OpticalSeries

          • TwoPhotonSeries

        • IndexSeries

        • IntervalSeries

        • OptogeneticSeries

        • PatchClampSeries

          • CurrentClampSeries

            • IZeroClampSeries

          • CurrentClampStimulusSeries

          • VoltageClampSeries

          • VoltageClampStimulusSeries

        • RoiResponseSeries

        • SpatialSeries

    • NWBFile

    • OpticalChannel

    • OptogeneticStimulusSite

    • ProcessingModule

    • Subject

  • SimpleMultiContainer

• Data

  • ElementIdentifiers

  • NWBData

    • Image

      • GrayscaleImage

      • RGBAImage

      • RGBImage

    • ImageReferences

    • ScratchData

  • VectorData

    • DynamicTableRegion

    • TimeSeriesReferenceVectorData

    • VectorIndex

2. Type Specifications

2.1. Base data types

This source module contains base data types used throughout the NWB data format.

2.1.1. NWBData

Overview: An abstract data type for a dataset.

NWBData extends Data and includes all elements of Data with the following additions or changes.

• Extends: Data

• Primitive Type: Dataset

• Inherits from: Data

• Subtypes: RGBImage, RGBAImage, Image, GrayscaleImage, ImageReferences, ScratchData

• Source filename: nwb.base.yaml

• Source Specification: see Section 3.2.1

2.1.2. TimeSeriesReferenceVectorData

Overview: Column storing references to a TimeSeries (rows). For each TimeSeries this VectorData column stores the start_index and count to indicate the range in time to be selected as well as an object reference to the TimeSeries.

TimeSeriesReferenceVectorData extends VectorData and includes all elements of VectorData with the following additions or changes.

• Extends: VectorData

• Primitive Type: Dataset

• Data Type: Compound data type with the following elements:

  • idx_start: Start index into the TimeSeries ‘data’ and ‘timestamp’ datasets of the referenced TimeSeries. The first dimension of those arrays is always time. (dtype= int32 )

  • count: Number of data samples available in this time series, during this epoch (dtype= int32 )

  • timeseries: The TimeSeries that this index applies to (dtype= object reference to TimeSeries )

• Default Name: timeseries

• Inherits from: VectorData, Data

• Source filename: nwb.base.yaml

• Source Specification: see Section 3.2.2

Table 2.2 Datasets, Links, and Attributes contained in <TimeSeriesReferenceVectorData>

Id	Type	Description
<TimeSeriesReferenceVectorData>	Dataset	Top level Dataset for <TimeSeriesReferenceVectorData> Neurodata Type: TimeSeriesReferenceVectorData Extends: VectorData Data Type: Compound data type with the following elements: idx_start: Start index into the TimeSeries ‘data’ and ‘timestamp’ datasets of the referenced TimeSeries. The first dimension of those arrays is always time. (dtype= int32 ) count: Number of data samples available in this time series, during this epoch (dtype= int32 ) timeseries: The TimeSeries that this index applies to (dtype= object reference to TimeSeries ) Default Name: timeseries
—description	Attribute	Description of what these vectors represent. Data Type: text Name: description

2.1.3. Image

Overview: An abstract data type for an image. Shape can be 2-D (x, y), or 3-D where the third dimension can have three or four elements, e.g. (x, y, (r, g, b)) or (x, y, (r, g, b, a)).

Image extends NWBData and includes all elements of NWBData with the following additions or changes.

• Extends: NWBData

• Primitive Type: Dataset

• Data Type: numeric

• Dimensions: [[‘x’, ‘y’], [‘x’, ‘y’, ‘r, g, b’], [‘x’, ‘y’, ‘r, g, b, a’]]

• Shape: [[None, None], [None, None, 3], [None, None, 4]]

• Inherits from: NWBData, Data

• Subtypes: RGBImage, GrayscaleImage, RGBAImage

• Source filename: nwb.base.yaml

• Source Specification: see Section 3.2.3

Table 2.3 Datasets, Links, and Attributes contained in <Image>

Id	Type	Description
<Image>	Dataset	Top level Dataset for <Image> Neurodata Type: Image Extends: NWBData Data Type: numeric Dimensions: [[‘x’, ‘y’], [‘x’, ‘y’, ‘r, g, b’], [‘x’, ‘y’, ‘r, g, b, a’]] Shape: [[None, None], [None, None, 3], [None, None, 4]]
—resolution	Attribute	Pixel resolution of the image, in pixels per centimeter. Data Type: float32 Required: False Name: resolution
—description	Attribute	Description of the image. Data Type: text Required: False Name: description

2.1.4. ImageReferences

Overview: Ordered dataset of references to Image objects.

ImageReferences extends NWBData and includes all elements of NWBData with the following additions or changes.

• Extends: NWBData

• Primitive Type: Dataset

• Data Type: object reference to Image

• Dimensions: [‘num_images’]

• Shape: [None]

• Inherits from: NWBData, Data

• Source filename: nwb.base.yaml

• Source Specification: see Section 3.2.4

2.1.5. NWBContainer

Overview: An abstract data type for a generic container storing collections of data and metadata. Base type for all data and metadata containers.

NWBContainer extends Container and includes all elements of Container with the following additions or changes.

• Extends: Container

• Primitive Type: Group

• Inherits from: Container

• Subtypes: OptogeneticSeries, NWBFile, Images, OpticalChannel, SpikeEventSeries, VoltageClampStimulusSeries, BehavioralEvents, FilteredEphys, LFP, EventDetection, ImageSeries, BehavioralEpochs, FeatureExtraction, EventWaveform, CurrentClampSeries, CompassDirection, OpticalSeries, ImagingPlane, RoiResponseSeries, TwoPhotonSeries, TimeSeries, ImageMaskSeries, OptogeneticStimulusSite, NWBDataInterface, VoltageClampSeries, ImageSegmentation, Clustering, ElectrodeGroup, MotionCorrection, PupilTracking, PatchClampSeries, EyeTracking, ImagingRetinotopy, Position, AbstractFeatureSeries, ProcessingModule, Subject, DfOverF, DecompositionSeries, IndexSeries, IntervalSeries, ClusterWaveforms, ElectricalSeries, IZeroClampSeries, Device, IntracellularElectrode, BehavioralTimeSeries, CurrentClampStimulusSeries, Fluorescence, CorrectedImageStack, AnnotationSeries, SpatialSeries, OnePhotonSeries, LabMetaData

• Source filename: nwb.base.yaml

• Source Specification: see Section 3.2.5

2.1.6. NWBDataInterface

Overview: An abstract data type for a generic container storing collections of data, as opposed to metadata.

NWBDataInterface extends NWBContainer and includes all elements of NWBContainer with the following additions or changes.

• Extends: NWBContainer

• Primitive Type: Group

• Inherits from: NWBContainer, Container

• Subtypes: OptogeneticSeries, Images, SpikeEventSeries, VoltageClampStimulusSeries, BehavioralEvents, FilteredEphys, LFP, EventDetection, ImageSeries, BehavioralEpochs, FeatureExtraction, EventWaveform, CurrentClampSeries, CompassDirection, OpticalSeries, RoiResponseSeries, TwoPhotonSeries, TimeSeries, ImageMaskSeries, VoltageClampSeries, ImageSegmentation, Clustering, MotionCorrection, PupilTracking, PatchClampSeries, EyeTracking, ImagingRetinotopy, Position, AbstractFeatureSeries, DfOverF, DecompositionSeries, IndexSeries, IntervalSeries, ClusterWaveforms, ElectricalSeries, IZeroClampSeries, BehavioralTimeSeries, CurrentClampStimulusSeries, Fluorescence, CorrectedImageStack, AnnotationSeries, SpatialSeries, OnePhotonSeries

• Source filename: nwb.base.yaml

• Source Specification: see Section 3.2.6

2.1.7. TimeSeries

Overview: General purpose time series.

TimeSeries extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Inherits from: NWBDataInterface, NWBContainer, Container

• Subtypes: OptogeneticSeries, SpikeEventSeries, VoltageClampStimulusSeries, ImageSeries, CurrentClampSeries, OpticalSeries, RoiResponseSeries, TwoPhotonSeries, ImageMaskSeries, VoltageClampSeries, PatchClampSeries, AbstractFeatureSeries, DecompositionSeries, IntervalSeries, IndexSeries, ElectricalSeries, IZeroClampSeries, CurrentClampStimulusSeries, AnnotationSeries, SpatialSeries, OnePhotonSeries

• Source filename: nwb.base.yaml

• Source Specification: see Section 3.2.7

Table 2.4 Datasets, Links, and Attributes contained in <TimeSeries>

Id	Type	Description
<TimeSeries>	Group	Top level Group for <TimeSeries> Neurodata Type: TimeSeries Extends: NWBDataInterface
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Data values. Data can be in 1-D, 2-D, 3-D, or 4-D. The first dimension should always represent time. This can also be used to store binary data (e.g., image frames). This can also be a link to data stored in an external file. Dimensions: [[‘num_times’], [‘num_times’, ‘num_DIM2’], [‘num_times’, ‘num_DIM2’, ‘num_DIM3’], [‘num_times’, ‘num_DIM2’, ‘num_DIM3’, ‘num_DIM4’]] Shape: [[None], [None, None], [None, None, None], [None, None, None, None]] Name: data
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——unit	Attribute	Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Name: unit
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description

Table 2.5 Groups contained in <TimeSeries>

Id	Type	Description
<TimeSeries>	Group	Top level Group for <TimeSeries> Neurodata Type: TimeSeries Extends: NWBDataInterface
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.1.7.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.1.8. ProcessingModule

Overview: A collection of processed data.

ProcessingModule extends NWBContainer and includes all elements of NWBContainer with the following additions or changes.

• Extends: NWBContainer

• Primitive Type: Group

• Inherits from: NWBContainer, Container

• Source filename: nwb.base.yaml

• Source Specification: see Section 3.2.8

Table 2.6 Datasets, Links, and Attributes contained in <ProcessingModule>

Id	Type	Description
<ProcessingModule>	Group	Top level Group for <ProcessingModule> Neurodata Type: ProcessingModule Extends: NWBContainer
—description	Attribute	Description of this collection of processed data. Data Type: text Name: description

Table 2.7 Groups contained in <ProcessingModule>

Id	Type	Description
<ProcessingModule>	Group	Top level Group for <ProcessingModule> Neurodata Type: ProcessingModule Extends: NWBContainer
—<NWBDataInterface>	Group	Data objects stored in this collection. Extends: NWBDataInterface Quantity: 0 or more
—<DynamicTable>	Group	Tables stored in this collection. Extends: DynamicTable Quantity: 0 or more

2.1.8.1. Groups: <NWBDataInterface>

Data objects stored in this collection.

• Extends: NWBDataInterface

• Quantity: 0 or more

2.1.8.2. Groups: <DynamicTable>

Tables stored in this collection.

• Extends: DynamicTable

• Quantity: 0 or more

2.1.9. Images

Overview: A collection of images with an optional way to specify the order of the images using the “order_of_images” dataset. An order must be specified if the images are referenced by index, e.g., from an IndexSeries.

Images extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: Images

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.base.yaml

• Source Specification: see Section 3.2.9

Table 2.8 Datasets, Links, and Attributes contained in <Images>

Id	Type	Description
<Images>	Group	Top level Group for <Images> Neurodata Type: Images Extends: NWBDataInterface Default Name: Images
—description	Attribute	Description of this collection of images. Data Type: text Name: description
—<Image>	Dataset	Images stored in this collection. Extends: Image Quantity: 1 or more
—order_of_images	Dataset	Ordered dataset of references to Image objects stored in the parent group. Each Image object in the Images group should be stored once and only once, so the dataset should have the same length as the number of images. Extends: ImageReferences Quantity: 0 or 1 Name: order_of_images

2.2. Devices

This source module contains neurodata_types for device data.

2.2.1. Device

Overview: Metadata about a data acquisition device, e.g., recording system, electrode, microscope.

Device extends NWBContainer and includes all elements of NWBContainer with the following additions or changes.

• Extends: NWBContainer

• Primitive Type: Group

• Inherits from: NWBContainer, Container

• Source filename: nwb.device.yaml

• Source Specification: see Section 3.3.1

Table 2.9 Datasets, Links, and Attributes contained in <Device>

Id	Type	Description
<Device>	Group	Top level Group for <Device> Neurodata Type: Device Extends: NWBContainer
—description	Attribute	Description of the device (e.g., model, firmware version, processing software version, etc.) as free-form text. Data Type: text Required: False Name: description
—manufacturer	Attribute	The name of the manufacturer of the device. Data Type: text Required: False Name: manufacturer

2.3. Epochs

This source module contains neurodata_types for epoch data.

2.3.1. TimeIntervals

Overview: A container for aggregating epoch data and the TimeSeries that each epoch applies to.

TimeIntervals extends DynamicTable and includes all elements of DynamicTable with the following additions or changes.

• Extends: DynamicTable

• Primitive Type: Group

• Inherits from: DynamicTable, Container

• Source filename: nwb.epoch.yaml

• Source Specification: see Section 3.4.1

Table 2.10 Datasets, Links, and Attributes contained in <TimeIntervals>

Id	Type	Description
<TimeIntervals>	Group	Top level Group for <TimeIntervals> Neurodata Type: TimeIntervals Extends: DynamicTable
—colnames	Attribute	The names of the columns in this table. This should be used to specify an order to the columns. Data Type: text Dimensions: [‘num_columns’] Shape: [None] Name: colnames
—description	Attribute	Description of what is in this dynamic table. Data Type: text Name: description
—start_time	Dataset	Start time of epoch, in seconds. Extends: VectorData Data Type: float32 Name: start_time
—stop_time	Dataset	Stop time of epoch, in seconds. Extends: VectorData Data Type: float32 Name: stop_time
—tags	Dataset	User-defined tags that identify or categorize events. Extends: VectorData Quantity: 0 or 1 Data Type: text Name: tags
—tags_index	Dataset	Index for tags. Extends: VectorIndex Quantity: 0 or 1 Name: tags_index
—timeseries	Dataset	An index into a TimeSeries object. Extends: TimeSeriesReferenceVectorData Quantity: 0 or 1 Name: timeseries
—timeseries_index	Dataset	Index for timeseries. Extends: VectorIndex Quantity: 0 or 1 Name: timeseries_index
—id	Dataset	Array of unique identifiers for the rows of this dynamic table. Extends: ElementIdentifiers Data Type: int Dimensions: [‘num_rows’] Shape: [None] Name: id
—<VectorData>	Dataset	Vector columns, including index columns, of this dynamic table. Extends: VectorData Quantity: 0 or more

2.4. Image data

This source module contains neurodata_types for image data.

2.4.1. GrayscaleImage

Overview: A grayscale image.

GrayscaleImage extends Image and includes all elements of Image with the following additions or changes.

• Extends: Image

• Primitive Type: Dataset

• Data Type: numeric

• Dimensions: [‘x’, ‘y’]

• Shape: [None, None]

• Inherits from: Image, NWBData, Data

• Source filename: nwb.image.yaml

• Source Specification: see Section 3.5.1

Table 2.11 Datasets, Links, and Attributes contained in <GrayscaleImage>

Id	Type	Description
<GrayscaleImage>	Dataset	Top level Dataset for <GrayscaleImage> Neurodata Type: GrayscaleImage Extends: Image Data Type: numeric Dimensions: [‘x’, ‘y’] Shape: [None, None]
—resolution	Attribute	Pixel resolution of the image, in pixels per centimeter. Data Type: float32 Required: False Name: resolution
—description	Attribute	Description of the image. Data Type: text Required: False Name: description

2.4.2. RGBImage

Overview: A color image.

RGBImage extends Image and includes all elements of Image with the following additions or changes.

• Extends: Image

• Primitive Type: Dataset

• Data Type: numeric

• Dimensions: [‘x’, ‘y’, ‘r, g, b’]

• Shape: [None, None, 3]

• Inherits from: Image, NWBData, Data

• Source filename: nwb.image.yaml

• Source Specification: see Section 3.5.2

Table 2.12 Datasets, Links, and Attributes contained in <RGBImage>

Id	Type	Description
<RGBImage>	Dataset	Top level Dataset for <RGBImage> Neurodata Type: RGBImage Extends: Image Data Type: numeric Dimensions: [‘x’, ‘y’, ‘r, g, b’] Shape: [None, None, 3]
—resolution	Attribute	Pixel resolution of the image, in pixels per centimeter. Data Type: float32 Required: False Name: resolution
—description	Attribute	Description of the image. Data Type: text Required: False Name: description

2.4.3. RGBAImage

Overview: A color image with transparency.

RGBAImage extends Image and includes all elements of Image with the following additions or changes.

• Extends: Image

• Primitive Type: Dataset

• Data Type: numeric

• Dimensions: [‘x’, ‘y’, ‘r, g, b, a’]

• Shape: [None, None, 4]

• Inherits from: Image, NWBData, Data

• Source filename: nwb.image.yaml

• Source Specification: see Section 3.5.3

Table 2.13 Datasets, Links, and Attributes contained in <RGBAImage>

Id	Type	Description
<RGBAImage>	Dataset	Top level Dataset for <RGBAImage> Neurodata Type: RGBAImage Extends: Image Data Type: numeric Dimensions: [‘x’, ‘y’, ‘r, g, b, a’] Shape: [None, None, 4]
—resolution	Attribute	Pixel resolution of the image, in pixels per centimeter. Data Type: float32 Required: False Name: resolution
—description	Attribute	Description of the image. Data Type: text Required: False Name: description

2.4.4. ImageSeries

Overview: General image data that is common between acquisition and stimulus time series. Sometimes the image data is stored in the file in a raw format while other times it will be stored as a series of external image files in the host file system. The data field will either be binary data, if the data is stored in the NWB file, or empty, if the data is stored in an external image stack. [frame][x][y] or [frame][x][y][z].

ImageSeries extends TimeSeries and includes all elements of TimeSeries with the following additions or changes.

• Extends: TimeSeries

• Primitive Type: Group

• Inherits from: TimeSeries, NWBDataInterface, NWBContainer, Container

• Subtypes: ImageMaskSeries, OpticalSeries, OnePhotonSeries, TwoPhotonSeries

• Source filename: nwb.image.yaml

• Source Specification: see Section 3.5.4

Table 2.14 Datasets, Links, and Attributes contained in <ImageSeries>

Id	Type	Description
<ImageSeries>	Group	Top level Group for <ImageSeries> Neurodata Type: ImageSeries Extends: TimeSeries
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Binary data representing images across frames. If data are stored in an external file, this should be an empty 3D array. Data Type: numeric Dimensions: [[‘frame’, ‘x’, ‘y’], [‘frame’, ‘x’, ‘y’, ‘z’]] Shape: [[None, None, None], [None, None, None, None]] Name: data
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——unit	Attribute	Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Name: unit
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—dimension	Dataset	Number of pixels on x, y, (and z) axes. Quantity: 0 or 1 Data Type: int32 Dimensions: [‘rank’] Shape: [None] Name: dimension
—external_file	Dataset	Paths to one or more external file(s). The field is only present if format=’external’. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_files’] Shape: [None] Name: external_file
——starting_frame	Attribute	Each external image may contain one or more consecutive frames of the full ImageSeries. This attribute serves as an index to indicate which frames each file contains, to faciliate random access. The ‘starting_frame’ attribute, hence, contains a list of frame numbers within the full ImageSeries of the first frame of each file listed in the parent ‘external_file’ dataset. Zero-based indexing is used (hence, the first element will always be zero). For example, if the ‘external_file’ dataset has three paths to files and the first file has 5 frames, the second file has 10 frames, and the third file has 20 frames, then this attribute will have values [0, 5, 15]. If there is a single external file that holds all of the frames of the ImageSeries (and so there is a single element in the ‘external_file’ dataset), then this attribute should have value [0]. Data Type: int32 Dimensions: [‘num_files’] Shape: [None] Name: starting_frame
—format	Dataset	Format of image. If this is ‘external’, then the attribute ‘external_file’ contains the path information to the image files. If this is ‘raw’, then the raw (single-channel) binary data is stored in the ‘data’ dataset. If this attribute is not present, then the default format=’raw’ case is assumed. Quantity: 0 or 1 Data Type: text Name: format
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—device	Link	Link to the Device object that was used to capture these images. Target Type Device Name: device

Table 2.15 Groups contained in <ImageSeries>

Id	Type	Description
<ImageSeries>	Group	Top level Group for <ImageSeries> Neurodata Type: ImageSeries Extends: TimeSeries
—device	Link	Link to the Device object that was used to capture these images. Target Type Device Name: device
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.4.4.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.4.5. ImageMaskSeries

Overview: An alpha mask that is applied to a presented visual stimulus. The ‘data’ array contains an array of mask values that are applied to the displayed image. Mask values are stored as RGBA. Mask can vary with time. The timestamps array indicates the starting time of a mask, and that mask pattern continues until it’s explicitly changed.

ImageMaskSeries extends ImageSeries and includes all elements of ImageSeries with the following additions or changes.

• Extends: ImageSeries

• Primitive Type: Group

• Inherits from: ImageSeries, TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.image.yaml

• Source Specification: see Section 3.5.5

Table 2.16 Datasets, Links, and Attributes contained in <ImageMaskSeries>

Id	Type	Description
<ImageMaskSeries>	Group	Top level Group for <ImageMaskSeries> Neurodata Type: ImageMaskSeries Extends: ImageSeries
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Binary data representing images across frames. If data are stored in an external file, this should be an empty 3D array. Data Type: numeric Dimensions: [[‘frame’, ‘x’, ‘y’], [‘frame’, ‘x’, ‘y’, ‘z’]] Shape: [[None, None, None], [None, None, None, None]] Name: data
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——unit	Attribute	Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Name: unit
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—dimension	Dataset	Number of pixels on x, y, (and z) axes. Quantity: 0 or 1 Data Type: int32 Dimensions: [‘rank’] Shape: [None] Name: dimension
—external_file	Dataset	Paths to one or more external file(s). The field is only present if format=’external’. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_files’] Shape: [None] Name: external_file
——starting_frame	Attribute	Each external image may contain one or more consecutive frames of the full ImageSeries. This attribute serves as an index to indicate which frames each file contains, to faciliate random access. The ‘starting_frame’ attribute, hence, contains a list of frame numbers within the full ImageSeries of the first frame of each file listed in the parent ‘external_file’ dataset. Zero-based indexing is used (hence, the first element will always be zero). For example, if the ‘external_file’ dataset has three paths to files and the first file has 5 frames, the second file has 10 frames, and the third file has 20 frames, then this attribute will have values [0, 5, 15]. If there is a single external file that holds all of the frames of the ImageSeries (and so there is a single element in the ‘external_file’ dataset), then this attribute should have value [0]. Data Type: int32 Dimensions: [‘num_files’] Shape: [None] Name: starting_frame
—format	Dataset	Format of image. If this is ‘external’, then the attribute ‘external_file’ contains the path information to the image files. If this is ‘raw’, then the raw (single-channel) binary data is stored in the ‘data’ dataset. If this attribute is not present, then the default format=’raw’ case is assumed. Quantity: 0 or 1 Data Type: text Name: format
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—masked_imageseries	Link	Link to ImageSeries object that this image mask is applied to. Target Type ImageSeries Name: masked_imageseries
—device	Link	Link to the Device object that was used to capture these images. Target Type Device Name: device

Table 2.17 Groups contained in <ImageMaskSeries>

Id	Type	Description
<ImageMaskSeries>	Group	Top level Group for <ImageMaskSeries> Neurodata Type: ImageMaskSeries Extends: ImageSeries
—masked_imageseries	Link	Link to ImageSeries object that this image mask is applied to. Target Type ImageSeries Name: masked_imageseries
—device	Link	Link to the Device object that was used to capture these images. Target Type Device Name: device
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.4.5.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.4.6. OpticalSeries

Overview: Image data that is presented or recorded. A stimulus template movie will be stored only as an image. When the image is presented as stimulus, additional data is required, such as field of view (e.g., how much of the visual field the image covers, or how what is the area of the target being imaged). If the OpticalSeries represents acquired imaging data, orientation is also important.

OpticalSeries extends ImageSeries and includes all elements of ImageSeries with the following additions or changes.

• Extends: ImageSeries

• Primitive Type: Group

• Inherits from: ImageSeries, TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.image.yaml

• Source Specification: see Section 3.5.6

Table 2.18 Datasets, Links, and Attributes contained in <OpticalSeries>

Id	Type	Description
<OpticalSeries>	Group	Top level Group for <OpticalSeries> Neurodata Type: OpticalSeries Extends: ImageSeries
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—distance	Dataset	Distance from camera/monitor to target/eye. Quantity: 0 or 1 Data Type: float32 Name: distance
—field_of_view	Dataset	Width, height and depth of image, or imaged area, in meters. Quantity: 0 or 1 Data Type: float32 Dimensions: [[‘width, height’], [‘width, height, depth’]] Shape: [[2], [3]] Name: field_of_view
—data	Dataset	Images presented to subject, either grayscale or RGB Data Type: numeric Dimensions: [[‘frame’, ‘x’, ‘y’], [‘frame’, ‘x’, ‘y’, ‘r, g, b’]] Shape: [[None, None, None], [None, None, None, 3]] Name: data
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——unit	Attribute	Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Name: unit
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—orientation	Dataset	Description of image relative to some reference frame (e.g., which way is up). Must also specify frame of reference. Quantity: 0 or 1 Data Type: text Name: orientation
—dimension	Dataset	Number of pixels on x, y, (and z) axes. Quantity: 0 or 1 Data Type: int32 Dimensions: [‘rank’] Shape: [None] Name: dimension
—external_file	Dataset	Paths to one or more external file(s). The field is only present if format=’external’. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_files’] Shape: [None] Name: external_file
——starting_frame	Attribute	Each external image may contain one or more consecutive frames of the full ImageSeries. This attribute serves as an index to indicate which frames each file contains, to faciliate random access. The ‘starting_frame’ attribute, hence, contains a list of frame numbers within the full ImageSeries of the first frame of each file listed in the parent ‘external_file’ dataset. Zero-based indexing is used (hence, the first element will always be zero). For example, if the ‘external_file’ dataset has three paths to files and the first file has 5 frames, the second file has 10 frames, and the third file has 20 frames, then this attribute will have values [0, 5, 15]. If there is a single external file that holds all of the frames of the ImageSeries (and so there is a single element in the ‘external_file’ dataset), then this attribute should have value [0]. Data Type: int32 Dimensions: [‘num_files’] Shape: [None] Name: starting_frame
—format	Dataset	Format of image. If this is ‘external’, then the attribute ‘external_file’ contains the path information to the image files. If this is ‘raw’, then the raw (single-channel) binary data is stored in the ‘data’ dataset. If this attribute is not present, then the default format=’raw’ case is assumed. Quantity: 0 or 1 Data Type: text Name: format
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—device	Link	Link to the Device object that was used to capture these images. Target Type Device Name: device

Table 2.19 Groups contained in <OpticalSeries>

Id	Type	Description
<OpticalSeries>	Group	Top level Group for <OpticalSeries> Neurodata Type: OpticalSeries Extends: ImageSeries
—device	Link	Link to the Device object that was used to capture these images. Target Type Device Name: device
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.4.6.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.4.7. IndexSeries

Overview: Stores indices to image frames stored in an ImageSeries. The purpose of the IndexSeries is to allow a static image stack to be stored in an Images object, and the images in the stack to be referenced out-of-order. This can be for the display of individual images, or of movie segments (as a movie is simply a series of images). The data field stores the index of the frame in the referenced Images object, and the timestamps array indicates when that image was displayed.

IndexSeries extends TimeSeries and includes all elements of TimeSeries with the following additions or changes.

• Extends: TimeSeries

• Primitive Type: Group

• Inherits from: TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.image.yaml

• Source Specification: see Section 3.5.7

Table 2.20 Datasets, Links, and Attributes contained in <IndexSeries>

Id	Type	Description
<IndexSeries>	Group	Top level Group for <IndexSeries> Neurodata Type: IndexSeries Extends: TimeSeries
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Index of the image (using zero-indexing) in the linked Images object. Data Type: uint32 Dimensions: [‘num_times’] Shape: [None] Name: data
——conversion	Attribute	This field is unused by IndexSeries. Data Type: float32 Required: False Name: conversion
——resolution	Attribute	This field is unused by IndexSeries. Data Type: float32 Required: False Name: resolution
——offset	Attribute	This field is unused by IndexSeries. Data Type: float32 Required: False Name: offset
——unit	Attribute	This field is unused by IndexSeries and has the value N/A. Data Type: text Value: N/A Name: unit
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—indexed_timeseries	Link	Link to ImageSeries object containing images that are indexed. Use of this link is discouraged and will be deprecated. Link to an Images type instead. Target Type ImageSeries Name: indexed_timeseries
—indexed_images	Link	Link to Images object containing an ordered set of images that are indexed. The Images object must contain a ‘ordered_images’ dataset specifying the order of the images in the Images type. Target Type Images Name: indexed_images

Table 2.21 Groups contained in <IndexSeries>

Id	Type	Description
<IndexSeries>	Group	Top level Group for <IndexSeries> Neurodata Type: IndexSeries Extends: TimeSeries
—indexed_timeseries	Link	Link to ImageSeries object containing images that are indexed. Use of this link is discouraged and will be deprecated. Link to an Images type instead. Target Type ImageSeries Name: indexed_timeseries
—indexed_images	Link	Link to Images object containing an ordered set of images that are indexed. The Images object must contain a ‘ordered_images’ dataset specifying the order of the images in the Images type. Target Type Images Name: indexed_images
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.4.7.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.5. NWB file

Main NWB file specification.

2.5.1. ScratchData

Overview: Any one-off datasets

ScratchData extends NWBData and includes all elements of NWBData with the following additions or changes.

• Extends: NWBData

• Primitive Type: Dataset

• Inherits from: NWBData, Data

• Source filename: nwb.file.yaml

• Source Specification: see Section 3.6.1

Table 2.22 Datasets, Links, and Attributes contained in <ScratchData>

Id	Type	Description
<ScratchData>	Dataset	Top level Dataset for <ScratchData> Neurodata Type: ScratchData Extends: NWBData
—notes	Attribute	Any notes the user has about the dataset being stored Data Type: text Name: notes

2.5.2. NWBFile

Overview: An NWB file storing cellular-based neurophysiology data from a single experimental session.

NWBFile extends NWBContainer and includes all elements of NWBContainer with the following additions or changes.

• Extends: NWBContainer

• Primitive Type: Group

• Name: root

• Inherits from: NWBContainer, Container

• Source filename: nwb.file.yaml

• Source Specification: see Section 3.6.2

Table 2.23 Datasets, Links, and Attributes contained in <NWBFile>

Id	Type	Description
root	Group	Top level Group for root Neurodata Type: NWBFile Extends: NWBContainer Name: root
—nwb_version	Attribute	File version string. Use semantic versioning, e.g. 1.2.1. This will be the name of the format with trailing major, minor and patch numbers. Data Type: text Value: 2.6.0 Name: nwb_version
—file_create_date	Dataset	A record of the date the file was created and of subsequent modifications. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted strings: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in “Z” with no timezone offset. Date accuracy is up to milliseconds. The file can be created after the experiment was run, so this may differ from the experiment start time. Each modification to the nwb file adds a new entry to the array. Data Type: isodatetime Dimensions: [‘num_modifications’] Shape: [None] Name: file_create_date
—identifier	Dataset	A unique text identifier for the file. For example, concatenated lab name, file creation date/time and experimentalist, or a hash of these and/or other values. The goal is that the string should be unique to all other files. Data Type: text Name: identifier
—session_description	Dataset	A description of the experimental session and data in the file. Data Type: text Name: session_description
—session_start_time	Dataset	Date and time of the experiment/session start. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in “Z” with no timezone offset. Date accuracy is up to milliseconds. Data Type: isodatetime Name: session_start_time
—timestamps_reference_time	Dataset	Date and time corresponding to time zero of all timestamps. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in “Z” with no timezone offset. Date accuracy is up to milliseconds. All times stored in the file use this time as reference (i.e., time zero). Data Type: isodatetime Name: timestamps_reference_time

Table 2.24 Groups contained in <NWBFile>

Id	Type	Description
root	Group	Top level Group for root Neurodata Type: NWBFile Extends: NWBContainer Name: root
—acquisition	Group	Data streams recorded from the system, including ephys, ophys, tracking, etc. This group should be read-only after the experiment is completed and timestamps are corrected to a common timebase. The data stored here may be links to raw data stored in external NWB files. This will allow keeping bulky raw data out of the file while preserving the option of keeping some/all in the file. Acquired data includes tracking and experimental data streams (i.e., everything measured from the system). If bulky data is stored in the /acquisition group, the data can exist in a separate NWB file that is linked to by the file being used for processing and analysis. Name: acquisition
—analysis	Group	Lab-specific and custom scientific analysis of data. There is no defined format for the content of this group - the format is up to the individual user/lab. To facilitate sharing analysis data between labs, the contents here should be stored in standard types (e.g., neurodata_types) and appropriately documented. The file can store lab-specific and custom data analysis without restriction on its form or schema, reducing data formatting restrictions on end users. Such data should be placed in the analysis group. The analysis data should be documented so that it could be shared with other labs. Name: analysis
—scratch	Group	A place to store one-off analysis results. Data placed here is not intended for sharing. By placing data here, users acknowledge that there is no guarantee that their data meets any standard. Quantity: 0 or 1 Name: scratch
—processing	Group	The home for ProcessingModules. These modules perform intermediate analysis of data that is necessary to perform before scientific analysis. Examples include spike clustering, extracting position from tracking data, stitching together image slices. ProcessingModules can be large and express many data sets from relatively complex analysis (e.g., spike detection and clustering) or small, representing extraction of position information from tracking video, or even binary lick/no-lick decisions. Common software tools (e.g., klustakwik, MClust) are expected to read/write data here. ‘Processing’ refers to intermediate analysis of the acquired data to make it more amenable to scientific analysis. Name: processing
—stimulus	Group	Data pushed into the system (eg, video stimulus, sound, voltage, etc) and secondary representations of that data (eg, measurements of something used as a stimulus). This group should be made read-only after experiment complete and timestamps are corrected to common timebase. Stores both presented stimuli and stimulus templates, the latter in case the same stimulus is presented multiple times, or is pulled from an external stimulus library. Stimuli are here defined as any signal that is pushed into the system as part of the experiment (eg, sound, video, voltage, etc). Many different experiments can use the same stimuli, and stimuli can be re-used during an experiment. The stimulus group is organized so that one version of template stimuli can be stored and these be used multiple times. These templates can exist in the present file or can be linked to a remote library file. Name: stimulus
—general	Group	Experimental metadata, including protocol, notes and description of hardware device(s). The metadata stored in this section should be used to describe the experiment. Metadata necessary for interpreting the data is stored with the data. General experimental metadata, including animal strain, experimental protocols, experimenter, devices, etc, are stored under ‘general’. Core metadata (e.g., that required to interpret data fields) is stored with the data itself, and implicitly defined by the file specification (e.g., time is in seconds). The strategy used here for storing non-core metadata is to use free-form text fields, such as would appear in sentences or paragraphs from a Methods section. Metadata fields are text to enable them to be more general, for example to represent ranges instead of numerical values. Machine-readable metadata is stored as attributes to these free-form datasets. All entries in the below table are to be included when data is present. Unused groups (e.g., intracellular_ephys in an optophysiology experiment) should not be created unless there is data to store within them. Name: general
—intervals	Group	Experimental intervals, whether that be logically distinct sub-experiments having a particular scientific goal, trials (see trials subgroup) during an experiment, or epochs (see epochs subgroup) deriving from analysis of data. Quantity: 0 or 1 Name: intervals
—units	Group	Data about sorted spike units. Extends: Units Quantity: 0 or 1 Name: units

2.5.2.1. Groups: /acquisition

Data streams recorded from the system, including ephys, ophys, tracking, etc. This group should be read-only after the experiment is completed and timestamps are corrected to a common timebase. The data stored here may be links to raw data stored in external NWB files. This will allow keeping bulky raw data out of the file while preserving the option of keeping some/all in the file. Acquired data includes tracking and experimental data streams (i.e., everything measured from the system). If bulky data is stored in the /acquisition group, the data can exist in a separate NWB file that is linked to by the file being used for processing and analysis.

• Name: acquisition

Table 2.25 Groups contained in <acquisition>

Id	Type	Description
acquisition	Group	Top level Group for acquisition Name: acquisition
—<NWBDataInterface>	Group	Acquired, raw data. Extends: NWBDataInterface Quantity: 0 or more
—<DynamicTable>	Group	Tabular data that is relevent to acquisition Extends: DynamicTable Quantity: 0 or more

2.5.2.2. Groups: /acquisition/<NWBDataInterface>

Acquired, raw data.

• Extends: NWBDataInterface

• Quantity: 0 or more

2.5.2.3. Groups: /acquisition/<DynamicTable>

Tabular data that is relevent to acquisition

• Extends: DynamicTable

• Quantity: 0 or more

2.5.2.4. Groups: /analysis

Lab-specific and custom scientific analysis of data. There is no defined format for the content of this group - the format is up to the individual user/lab. To facilitate sharing analysis data between labs, the contents here should be stored in standard types (e.g., neurodata_types) and appropriately documented. The file can store lab-specific and custom data analysis without restriction on its form or schema, reducing data formatting restrictions on end users. Such data should be placed in the analysis group. The analysis data should be documented so that it could be shared with other labs.

• Name: analysis

Table 2.26 Groups contained in <analysis>

Id	Type	Description
analysis	Group	Top level Group for analysis Name: analysis
—<NWBContainer>	Group	Custom analysis results. Extends: NWBContainer Quantity: 0 or more
—<DynamicTable>	Group	Tabular data that is relevent to data stored in analysis Extends: DynamicTable Quantity: 0 or more

2.5.2.5. Groups: /analysis/<NWBContainer>

Custom analysis results.

• Extends: NWBContainer

• Quantity: 0 or more

2.5.2.6. Groups: /analysis/<DynamicTable>

Tabular data that is relevent to data stored in analysis

• Extends: DynamicTable

• Quantity: 0 or more

2.5.2.7. Groups: /scratch

A place to store one-off analysis results. Data placed here is not intended for sharing. By placing data here, users acknowledge that there is no guarantee that their data meets any standard.

• Quantity: 0 or 1

• Name: scratch

Table 2.27 Datasets, Links, and Attributes contained in /scratch

Id	Type	Description
scratch	Group	Top level Group for scratch Quantity: 0 or 1 Name: scratch
—<ScratchData>	Dataset	Any one-off datasets Extends: ScratchData Quantity: 0 or more

Table 2.28 Groups contained in <scratch>

Id	Type	Description
scratch	Group	Top level Group for scratch Quantity: 0 or 1 Name: scratch
—<NWBContainer>	Group	Any one-off containers Extends: NWBContainer Quantity: 0 or more
—<DynamicTable>	Group	Any one-off tables Extends: DynamicTable Quantity: 0 or more

2.5.2.8. Groups: /scratch/<NWBContainer>

Any one-off containers

• Extends: NWBContainer

• Quantity: 0 or more

2.5.2.9. Groups: /scratch/<DynamicTable>

Any one-off tables

• Extends: DynamicTable

• Quantity: 0 or more

2.5.2.10. Groups: /processing

The home for ProcessingModules. These modules perform intermediate analysis of data that is necessary to perform before scientific analysis. Examples include spike clustering, extracting position from tracking data, stitching together image slices. ProcessingModules can be large and express many data sets from relatively complex analysis (e.g., spike detection and clustering) or small, representing extraction of position information from tracking video, or even binary lick/no-lick decisions. Common software tools (e.g., klustakwik, MClust) are expected to read/write data here. ‘Processing’ refers to intermediate analysis of the acquired data to make it more amenable to scientific analysis.

• Name: processing

Table 2.29 Groups contained in <processing>

Id	Type	Description
processing	Group	Top level Group for processing Name: processing
—<ProcessingModule>	Group	Intermediate analysis of acquired data. Extends: ProcessingModule Quantity: 0 or more

2.5.2.11. Groups: /processing/<ProcessingModule>

Intermediate analysis of acquired data.

• Extends: ProcessingModule

• Quantity: 0 or more

2.5.2.12. Groups: /stimulus

Data pushed into the system (eg, video stimulus, sound, voltage, etc) and secondary representations of that data (eg, measurements of something used as a stimulus). This group should be made read-only after experiment complete and timestamps are corrected to common timebase. Stores both presented stimuli and stimulus templates, the latter in case the same stimulus is presented multiple times, or is pulled from an external stimulus library. Stimuli are here defined as any signal that is pushed into the system as part of the experiment (eg, sound, video, voltage, etc). Many different experiments can use the same stimuli, and stimuli can be re-used during an experiment. The stimulus group is organized so that one version of template stimuli can be stored and these be used multiple times. These templates can exist in the present file or can be linked to a remote library file.

• Name: stimulus

Table 2.30 Groups contained in <stimulus>

Id	Type	Description
stimulus	Group	Top level Group for stimulus Name: stimulus
—presentation	Group	Stimuli presented during the experiment. Name: presentation
—templates	Group	Template stimuli. Timestamps in templates are based on stimulus design and are relative to the beginning of the stimulus. When templates are used, the stimulus instances must convert presentation times to the experiment`s time reference frame. Name: templates

2.5.2.13. Groups: /stimulus/presentation

Stimuli presented during the experiment.

• Name: presentation

Table 2.31 Groups contained in <presentation>

Id	Type	Description
presentation	Group	Top level Group for presentation Name: presentation
—<TimeSeries>	Group	TimeSeries objects containing data of presented stimuli. Extends: TimeSeries Quantity: 0 or more

2.5.2.14. Groups: /stimulus/presentation/<TimeSeries>

TimeSeries objects containing data of presented stimuli.

• Extends: TimeSeries

• Quantity: 0 or more

2.5.2.15. Groups: /stimulus/templates

Template stimuli. Timestamps in templates are based on stimulus design and are relative to the beginning of the stimulus. When templates are used, the stimulus instances must convert presentation times to the experiment`s time reference frame.

• Name: templates

Table 2.32 Groups contained in <templates>

Id	Type	Description
templates	Group	Top level Group for templates Name: templates
—<TimeSeries>	Group	TimeSeries objects containing template data of presented stimuli. Extends: TimeSeries Quantity: 0 or more
—<Images>	Group	Images objects containing images of presented stimuli. Extends: Images Quantity: 0 or more

2.5.2.16. Groups: /stimulus/templates/<TimeSeries>

TimeSeries objects containing template data of presented stimuli.

• Extends: TimeSeries

• Quantity: 0 or more

2.5.2.17. Groups: /stimulus/templates/<Images>

Images objects containing images of presented stimuli.

• Extends: Images

• Quantity: 0 or more

2.5.2.18. Groups: /general

Experimental metadata, including protocol, notes and description of hardware device(s). The metadata stored in this section should be used to describe the experiment. Metadata necessary for interpreting the data is stored with the data. General experimental metadata, including animal strain, experimental protocols, experimenter, devices, etc, are stored under ‘general’. Core metadata (e.g., that required to interpret data fields) is stored with the data itself, and implicitly defined by the file specification (e.g., time is in seconds). The strategy used here for storing non-core metadata is to use free-form text fields, such as would appear in sentences or paragraphs from a Methods section. Metadata fields are text to enable them to be more general, for example to represent ranges instead of numerical values. Machine-readable metadata is stored as attributes to these free-form datasets. All entries in the below table are to be included when data is present. Unused groups (e.g., intracellular_ephys in an optophysiology experiment) should not be created unless there is data to store within them.

• Name: general

Table 2.33 Datasets, Links, and Attributes contained in /general

Id	Type	Description
general	Group	Top level Group for general Name: general
—data_collection	Dataset	Notes about data collection and analysis. Quantity: 0 or 1 Data Type: text Name: data_collection
—experiment_description	Dataset	General description of the experiment. Quantity: 0 or 1 Data Type: text Name: experiment_description
—experimenter	Dataset	Name of person(s) who performed the experiment. Can also specify roles of different people involved. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_experimenters’] Shape: [None] Name: experimenter
—institution	Dataset	Institution(s) where experiment was performed. Quantity: 0 or 1 Data Type: text Name: institution
—keywords	Dataset	Terms to search over. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_keywords’] Shape: [None] Name: keywords
—lab	Dataset	Laboratory where experiment was performed. Quantity: 0 or 1 Data Type: text Name: lab
—notes	Dataset	Notes about the experiment. Quantity: 0 or 1 Data Type: text Name: notes
—pharmacology	Dataset	Description of drugs used, including how and when they were administered. Anesthesia(s), painkiller(s), etc., plus dosage, concentration, etc. Quantity: 0 or 1 Data Type: text Name: pharmacology
—protocol	Dataset	Experimental protocol, if applicable. e.g., include IACUC protocol number. Quantity: 0 or 1 Data Type: text Name: protocol
—related_publications	Dataset	Publication information. PMID, DOI, URL, etc. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_publications’] Shape: [None] Name: related_publications
—session_id	Dataset	Lab-specific ID for the session. Quantity: 0 or 1 Data Type: text Name: session_id
—slices	Dataset	Description of slices, including information about preparation thickness, orientation, temperature, and bath solution. Quantity: 0 or 1 Data Type: text Name: slices
—source_script	Dataset	Script file or link to public source code used to create this NWB file. Quantity: 0 or 1 Data Type: text Name: source_script
——file_name	Attribute	Name of script file. Data Type: text Name: file_name
—stimulus	Dataset	Notes about stimuli, such as how and where they were presented. Quantity: 0 or 1 Data Type: text Name: stimulus
—surgery	Dataset	Narrative description about surgery/surgeries, including date(s) and who performed surgery. Quantity: 0 or 1 Data Type: text Name: surgery
—virus	Dataset	Information about virus(es) used in experiments, including virus ID, source, date made, injection location, volume, etc. Quantity: 0 or 1 Data Type: text Name: virus

Table 2.34 Groups contained in <general>

Id	Type	Description
general	Group	Top level Group for general Name: general
—<LabMetaData>	Group	Place-holder than can be extended so that lab-specific meta-data can be placed in /general. Extends: LabMetaData Quantity: 0 or more
—devices	Group	Description of hardware devices used during experiment, e.g., monitors, ADC boards, microscopes, etc. Quantity: 0 or 1 Name: devices
—subject	Group	Information about the animal or person from which the data was measured. Extends: Subject Quantity: 0 or 1 Name: subject
—extracellular_ephys	Group	Metadata related to extracellular electrophysiology. Quantity: 0 or 1 Name: extracellular_ephys
—intracellular_ephys	Group	Metadata related to intracellular electrophysiology. Quantity: 0 or 1 Name: intracellular_ephys
—optogenetics	Group	Metadata describing optogenetic stimuluation. Quantity: 0 or 1 Name: optogenetics
—optophysiology	Group	Metadata related to optophysiology. Quantity: 0 or 1 Name: optophysiology

2.5.2.19. Groups: /general/<LabMetaData>

Place-holder than can be extended so that lab-specific meta-data can be placed in /general.

• Extends: LabMetaData

• Quantity: 0 or more

2.5.2.20. Groups: /general/devices

Description of hardware devices used during experiment, e.g., monitors, ADC boards, microscopes, etc.

• Quantity: 0 or 1

• Name: devices

Table 2.35 Groups contained in <devices>

Id	Type	Description
devices	Group	Top level Group for devices Quantity: 0 or 1 Name: devices
—<Device>	Group	Data acquisition devices. Extends: Device Quantity: 0 or more

2.5.2.21. Groups: /general/devices/<Device>

Data acquisition devices.

• Extends: Device

• Quantity: 0 or more

2.5.2.22. Groups: /general/subject

Information about the animal or person from which the data was measured.

• Extends: Subject

• Quantity: 0 or 1

• Name: subject

2.5.2.23. Groups: /general/extracellular_ephys

Metadata related to extracellular electrophysiology.

• Quantity: 0 or 1

• Name: extracellular_ephys

Table 2.36 Groups contained in <extracellular_ephys>

Id	Type	Description
extracellular_ephys	Group	Top level Group for extracellular_ephys Quantity: 0 or 1 Name: extracellular_ephys
—<ElectrodeGroup>	Group	Physical group of electrodes. Extends: ElectrodeGroup Quantity: 0 or more
—electrodes	Group	A table of all electrodes (i.e. channels) used for recording. Extends: DynamicTable Quantity: 0 or 1 Name: electrodes

2.5.2.24. Groups: /general/extracellular_ephys/<ElectrodeGroup>

Physical group of electrodes.

• Extends: ElectrodeGroup

• Quantity: 0 or more

2.5.2.25. Groups: /general/extracellular_ephys/electrodes

A table of all electrodes (i.e. channels) used for recording.

• Extends: DynamicTable

• Quantity: 0 or 1

• Name: electrodes

Table 2.37 Datasets, Links, and Attributes contained in /general/extracellular_ephys/electrodes

Id	Type	Description
electrodes	Group	Top level Group for electrodes Extends: DynamicTable Quantity: 0 or 1 Name: electrodes
—x	Dataset	x coordinate of the channel location in the brain (+x is posterior). Extends: VectorData Quantity: 0 or 1 Data Type: float32 Name: x
—y	Dataset	y coordinate of the channel location in the brain (+y is inferior). Extends: VectorData Quantity: 0 or 1 Data Type: float32 Name: y
—z	Dataset	z coordinate of the channel location in the brain (+z is right). Extends: VectorData Quantity: 0 or 1 Data Type: float32 Name: z
—imp	Dataset	Impedance of the channel, in ohms. Extends: VectorData Quantity: 0 or 1 Data Type: float32 Name: imp
—location	Dataset	Location of the electrode (channel). Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible. Extends: VectorData Data Type: text Name: location
—filtering	Dataset	Description of hardware filtering, including the filter name and frequency cutoffs. Extends: VectorData Quantity: 0 or 1 Data Type: text Name: filtering
—group	Dataset	Reference to the ElectrodeGroup this electrode is a part of. Extends: VectorData Data Type: object reference to ElectrodeGroup Name: group
—group_name	Dataset	Name of the ElectrodeGroup this electrode is a part of. Extends: VectorData Data Type: text Name: group_name
—rel_x	Dataset	x coordinate in electrode group Extends: VectorData Quantity: 0 or 1 Data Type: float32 Name: rel_x
—rel_y	Dataset	y coordinate in electrode group Extends: VectorData Quantity: 0 or 1 Data Type: float32 Name: rel_y
—rel_z	Dataset	z coordinate in electrode group Extends: VectorData Quantity: 0 or 1 Data Type: float32 Name: rel_z
—reference	Dataset	Description of the reference electrode and/or reference scheme used for this electrode, e.g., “stainless steel skull screw” or “online common average referencing”. Extends: VectorData Quantity: 0 or 1 Data Type: text Name: reference

2.5.2.26. Groups: /general/intracellular_ephys

Metadata related to intracellular electrophysiology.

• Quantity: 0 or 1

• Name: intracellular_ephys

Table 2.38 Datasets, Links, and Attributes contained in /general/intracellular_ephys

Id	Type	Description
intracellular_ephys	Group	Top level Group for intracellular_ephys Quantity: 0 or 1 Name: intracellular_ephys
—filtering	Dataset	[DEPRECATED] Use IntracellularElectrode.filtering instead. Description of filtering used. Includes filtering type and parameters, frequency fall-off, etc. If this changes between TimeSeries, filter description should be stored as a text attribute for each TimeSeries. Quantity: 0 or 1 Data Type: text Name: filtering

Table 2.39 Groups contained in <intracellular_ephys>

Id	Type	Description
intracellular_ephys	Group	Top level Group for intracellular_ephys Quantity: 0 or 1 Name: intracellular_ephys
—<IntracellularElectrode>	Group	An intracellular electrode. Extends: IntracellularElectrode Quantity: 0 or more
—sweep_table	Group	[DEPRECATED] Table used to group different PatchClampSeries. SweepTable is being replaced by IntracellularRecordingsTable and SimultaneousRecordingsTable tabels. Additional SequentialRecordingsTable, RepetitionsTable and ExperimentalConditions tables provide enhanced support for experiment metadata. Extends: SweepTable Quantity: 0 or 1 Name: sweep_table
—intracellular_recordings	Group	A table to group together a stimulus and response from a single electrode and a single simultaneous recording. Each row in the table represents a single recording consisting typically of a stimulus and a corresponding response. In some cases, however, only a stimulus or a response are recorded as as part of an experiment. In this case both, the stimulus and response will point to the same TimeSeries while the idx_start and count of the invalid column will be set to -1, thus, indicating that no values have been recorded for the stimulus or response, respectively. Note, a recording MUST contain at least a stimulus or a response. Typically the stimulus and response are PatchClampSeries. However, the use of AD/DA channels that are not associated to an electrode is also common in intracellular electrophysiology, in which case other TimeSeries may be used. Extends: IntracellularRecordingsTable Quantity: 0 or 1 Name: intracellular_recordings
—simultaneous_recordings	Group	A table for grouping different intracellular recordings from the IntracellularRecordingsTable table together that were recorded simultaneously from different electrodes Extends: SimultaneousRecordingsTable Quantity: 0 or 1 Name: simultaneous_recordings
—sequential_recordings	Group	A table for grouping different sequential recordings from the SimultaneousRecordingsTable table together. This is typically used to group together sequential recordings where the a sequence of stimuli of the same type with varying parameters have been presented in a sequence. Extends: SequentialRecordingsTable Quantity: 0 or 1 Name: sequential_recordings
—repetitions	Group	A table for grouping different sequential intracellular recordings together. With each SequentialRecording typically representing a particular type of stimulus, the RepetitionsTable table is typically used to group sets of stimuli applied in sequence. Extends: RepetitionsTable Quantity: 0 or 1 Name: repetitions
—experimental_conditions	Group	A table for grouping different intracellular recording repetitions together that belong to the same experimental experimental_conditions. Extends: ExperimentalConditionsTable Quantity: 0 or 1 Name: experimental_conditions

2.5.2.27. Groups: /general/intracellular_ephys/<IntracellularElectrode>

An intracellular electrode.

• Extends: IntracellularElectrode

• Quantity: 0 or more

2.5.2.28. Groups: /general/intracellular_ephys/sweep_table

[DEPRECATED] Table used to group different PatchClampSeries. SweepTable is being replaced by IntracellularRecordingsTable and SimultaneousRecordingsTable tabels. Additional SequentialRecordingsTable, RepetitionsTable and ExperimentalConditions tables provide enhanced support for experiment metadata.

• Extends: SweepTable

• Quantity: 0 or 1

• Name: sweep_table

2.5.2.29. Groups: /general/intracellular_ephys/intracellular_recordings

A table to group together a stimulus and response from a single electrode and a single simultaneous recording. Each row in the table represents a single recording consisting typically of a stimulus and a corresponding response. In some cases, however, only a stimulus or a response are recorded as as part of an experiment. In this case both, the stimulus and response will point to the same TimeSeries while the idx_start and count of the invalid column will be set to -1, thus, indicating that no values have been recorded for the stimulus or response, respectively. Note, a recording MUST contain at least a stimulus or a response. Typically the stimulus and response are PatchClampSeries. However, the use of AD/DA channels that are not associated to an electrode is also common in intracellular electrophysiology, in which case other TimeSeries may be used.

• Extends: IntracellularRecordingsTable

• Quantity: 0 or 1

• Name: intracellular_recordings

2.5.2.30. Groups: /general/intracellular_ephys/simultaneous_recordings

A table for grouping different intracellular recordings from the IntracellularRecordingsTable table together that were recorded simultaneously from different electrodes

• Extends: SimultaneousRecordingsTable

• Quantity: 0 or 1

• Name: simultaneous_recordings

2.5.2.31. Groups: /general/intracellular_ephys/sequential_recordings

A table for grouping different sequential recordings from the SimultaneousRecordingsTable table together. This is typically used to group together sequential recordings where the a sequence of stimuli of the same type with varying parameters have been presented in a sequence.

• Extends: SequentialRecordingsTable

• Quantity: 0 or 1

• Name: sequential_recordings

2.5.2.32. Groups: /general/intracellular_ephys/repetitions

A table for grouping different sequential intracellular recordings together. With each SequentialRecording typically representing a particular type of stimulus, the RepetitionsTable table is typically used to group sets of stimuli applied in sequence.

• Extends: RepetitionsTable

• Quantity: 0 or 1

• Name: repetitions

2.5.2.33. Groups: /general/intracellular_ephys/experimental_conditions

A table for grouping different intracellular recording repetitions together that belong to the same experimental experimental_conditions.

• Extends: ExperimentalConditionsTable

• Quantity: 0 or 1

• Name: experimental_conditions

2.5.2.34. Groups: /general/optogenetics

Metadata describing optogenetic stimuluation.

• Quantity: 0 or 1

• Name: optogenetics

Table 2.40 Groups contained in <optogenetics>

Id	Type	Description
optogenetics	Group	Top level Group for optogenetics Quantity: 0 or 1 Name: optogenetics
—<OptogeneticStimulusSite>	Group	An optogenetic stimulation site. Extends: OptogeneticStimulusSite Quantity: 0 or more

2.5.2.35. Groups: /general/optogenetics/<OptogeneticStimulusSite>

An optogenetic stimulation site.

• Extends: OptogeneticStimulusSite

• Quantity: 0 or more

2.5.2.36. Groups: /general/optophysiology

Metadata related to optophysiology.

• Quantity: 0 or 1

• Name: optophysiology

Table 2.41 Groups contained in <optophysiology>

Id	Type	Description
optophysiology	Group	Top level Group for optophysiology Quantity: 0 or 1 Name: optophysiology
—<ImagingPlane>	Group	An imaging plane. Extends: ImagingPlane Quantity: 0 or more

2.5.2.37. Groups: /general/optophysiology/<ImagingPlane>

An imaging plane.

• Extends: ImagingPlane

• Quantity: 0 or more

2.5.2.38. Groups: /intervals

Experimental intervals, whether that be logically distinct sub-experiments having a particular scientific goal, trials (see trials subgroup) during an experiment, or epochs (see epochs subgroup) deriving from analysis of data.

• Quantity: 0 or 1

• Name: intervals

Table 2.42 Groups contained in <intervals>

Id	Type	Description
intervals	Group	Top level Group for intervals Quantity: 0 or 1 Name: intervals
—epochs	Group	Divisions in time marking experimental stages or sub-divisions of a single recording session. Extends: TimeIntervals Quantity: 0 or 1 Name: epochs
—trials	Group	Repeated experimental events that have a logical grouping. Extends: TimeIntervals Quantity: 0 or 1 Name: trials
—invalid_times	Group	Time intervals that should be removed from analysis. Extends: TimeIntervals Quantity: 0 or 1 Name: invalid_times
—<TimeIntervals>	Group	Optional additional table(s) for describing other experimental time intervals. Extends: TimeIntervals Quantity: 0 or more

2.5.2.39. Groups: /intervals/epochs

Divisions in time marking experimental stages or sub-divisions of a single recording session.

• Extends: TimeIntervals

• Quantity: 0 or 1

• Name: epochs

2.5.2.40. Groups: /intervals/trials

Repeated experimental events that have a logical grouping.

• Extends: TimeIntervals

• Quantity: 0 or 1

• Name: trials

2.5.2.41. Groups: /intervals/invalid_times

Time intervals that should be removed from analysis.

• Extends: TimeIntervals

• Quantity: 0 or 1

• Name: invalid_times

2.5.2.42. Groups: /intervals/<TimeIntervals>

Optional additional table(s) for describing other experimental time intervals.

• Extends: TimeIntervals

• Quantity: 0 or more

2.5.2.43. Groups: /units

Data about sorted spike units.

• Extends: Units

• Quantity: 0 or 1

• Name: units

2.5.3. LabMetaData

Overview: Lab-specific meta-data.

LabMetaData extends NWBContainer and includes all elements of NWBContainer with the following additions or changes.

• Extends: NWBContainer

• Primitive Type: Group

• Inherits from: NWBContainer, Container

• Source filename: nwb.file.yaml

• Source Specification: see Section 3.6.3

2.5.4. Subject

Overview: Information about the animal or person from which the data was measured.

Subject extends NWBContainer and includes all elements of NWBContainer with the following additions or changes.

• Extends: NWBContainer

• Primitive Type: Group

• Inherits from: NWBContainer, Container

• Source filename: nwb.file.yaml

• Source Specification: see Section 3.6.4

Table 2.43 Datasets, Links, and Attributes contained in <Subject>

Id	Type	Description
<Subject>	Group	Top level Group for <Subject> Neurodata Type: Subject Extends: NWBContainer
—age	Dataset	Age of subject. Can be supplied instead of ‘date_of_birth’. Quantity: 0 or 1 Data Type: text Name: age
——reference	Attribute	Age is with reference to this event. Can be ‘birth’ or ‘gestational’. If reference is omitted, ‘birth’ is implied. Data Type: text Required: False Default Value: birth Name: reference
—date_of_birth	Dataset	Date of birth of subject. Can be supplied instead of ‘age’. Quantity: 0 or 1 Data Type: isodatetime Name: date_of_birth
—description	Dataset	Description of subject and where subject came from (e.g., breeder, if animal). Quantity: 0 or 1 Data Type: text Name: description
—genotype	Dataset	Genetic strain. If absent, assume Wild Type (WT). Quantity: 0 or 1 Data Type: text Name: genotype
—sex	Dataset	Gender of subject. Quantity: 0 or 1 Data Type: text Name: sex
—species	Dataset	Species of subject. Quantity: 0 or 1 Data Type: text Name: species
—strain	Dataset	Strain of subject. Quantity: 0 or 1 Data Type: text Name: strain
—subject_id	Dataset	ID of animal/person used/participating in experiment (lab convention). Quantity: 0 or 1 Data Type: text Name: subject_id
—weight	Dataset	Weight at time of experiment, at time of surgery and at other important times. Quantity: 0 or 1 Data Type: text Name: weight

2.6. Miscellaneous neurodata_types.

Miscellaneous types.

2.6.1. AbstractFeatureSeries

Overview: Abstract features, such as quantitative descriptions of sensory stimuli. The TimeSeries::data field is a 2D array, storing those features (e.g., for visual grating stimulus this might be orientation, spatial frequency and contrast). Null stimuli (eg, uniform gray) can be marked as being an independent feature (eg, 1.0 for gray, 0.0 for actual stimulus) or by storing NaNs for feature values, or through use of the TimeSeries::control fields. A set of features is considered to persist until the next set of features is defined. The final set of features stored should be the null set. This is useful when storing the raw stimulus is impractical.

AbstractFeatureSeries extends TimeSeries and includes all elements of TimeSeries with the following additions or changes.

• Extends: TimeSeries

• Primitive Type: Group

• Inherits from: TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.misc.yaml

• Source Specification: see Section 3.7.1

Table 2.44 Datasets, Links, and Attributes contained in <AbstractFeatureSeries>

Id	Type	Description
<AbstractFeatureSeries>	Group	Top level Group for <AbstractFeatureSeries> Neurodata Type: AbstractFeatureSeries Extends: TimeSeries
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Values of each feature at each time. Data Type: numeric Dimensions: [[‘num_times’], [‘num_times’, ‘num_features’]] Shape: [[None], [None, None]] Name: data
——unit	Attribute	Since there can be different units for different features, store the units in ‘feature_units’. The default value for this attribute is “see ‘feature_units’”. Data Type: text Required: False Default Value: see ‘feature_units’ Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—feature_units	Dataset	Units of each feature. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_features’] Shape: [None] Name: feature_units
—features	Dataset	Description of the features represented in TimeSeries::data. Data Type: text Dimensions: [‘num_features’] Shape: [None] Name: features
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description

Table 2.45 Groups contained in <AbstractFeatureSeries>

Id	Type	Description
<AbstractFeatureSeries>	Group	Top level Group for <AbstractFeatureSeries> Neurodata Type: AbstractFeatureSeries Extends: TimeSeries
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.6.1.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.6.2. AnnotationSeries

Overview: Stores user annotations made during an experiment. The data[] field stores a text array, and timestamps are stored for each annotation (ie, interval=1). This is largely an alias to a standard TimeSeries storing a text array but that is identifiable as storing annotations in a machine-readable way.

AnnotationSeries extends TimeSeries and includes all elements of TimeSeries with the following additions or changes.

• Extends: TimeSeries

• Primitive Type: Group

• Inherits from: TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.misc.yaml

• Source Specification: see Section 3.7.2

Table 2.46 Datasets, Links, and Attributes contained in <AnnotationSeries>

Id	Type	Description
<AnnotationSeries>	Group	Top level Group for <AnnotationSeries> Neurodata Type: AnnotationSeries Extends: TimeSeries
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Annotations made during an experiment. Data Type: text Dimensions: [‘num_times’] Shape: [None] Name: data
——resolution	Attribute	Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0. Data Type: float32 Value: -1.0 Name: resolution
——unit	Attribute	Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to ‘n/a’. Data Type: text Value: n/a Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description

Table 2.47 Groups contained in <AnnotationSeries>

Id	Type	Description
<AnnotationSeries>	Group	Top level Group for <AnnotationSeries> Neurodata Type: AnnotationSeries Extends: TimeSeries
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.6.2.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.6.3. IntervalSeries

Overview: Stores intervals of data. The timestamps field stores the beginning and end of intervals. The data field stores whether the interval just started (>0 value) or ended (<0 value). Different interval types can be represented in the same series by using multiple key values (eg, 1 for feature A, 2 for feature B, 3 for feature C, etc). The field data stores an 8-bit integer. This is largely an alias of a standard TimeSeries but that is identifiable as representing time intervals in a machine-readable way.

IntervalSeries extends TimeSeries and includes all elements of TimeSeries with the following additions or changes.

• Extends: TimeSeries

• Primitive Type: Group

• Inherits from: TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.misc.yaml

• Source Specification: see Section 3.7.3

Table 2.48 Datasets, Links, and Attributes contained in <IntervalSeries>

Id	Type	Description
<IntervalSeries>	Group	Top level Group for <IntervalSeries> Neurodata Type: IntervalSeries Extends: TimeSeries
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Use values >0 if interval started, <0 if interval ended. Data Type: int8 Dimensions: [‘num_times’] Shape: [None] Name: data
——resolution	Attribute	Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0. Data Type: float32 Value: -1.0 Name: resolution
——unit	Attribute	Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to ‘n/a’. Data Type: text Value: n/a Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description

Table 2.49 Groups contained in <IntervalSeries>

Id	Type	Description
<IntervalSeries>	Group	Top level Group for <IntervalSeries> Neurodata Type: IntervalSeries Extends: TimeSeries
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.6.3.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.6.4. DecompositionSeries

Overview: Spectral analysis of a time series, e.g. of an LFP or a speech signal.

DecompositionSeries extends TimeSeries and includes all elements of TimeSeries with the following additions or changes.

• Extends: TimeSeries

• Primitive Type: Group

• Inherits from: TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.misc.yaml

• Source Specification: see Section 3.7.4

Table 2.50 Datasets, Links, and Attributes contained in <DecompositionSeries>

Id	Type	Description
<DecompositionSeries>	Group	Top level Group for <DecompositionSeries> Neurodata Type: DecompositionSeries Extends: TimeSeries
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Data decomposed into frequency bands. Data Type: numeric Dimensions: [‘num_times’, ‘num_channels’, ‘num_bands’] Shape: [None, None, None] Name: data
——unit	Attribute	Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’. Data Type: text Required: False Default Value: no unit Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—metric	Dataset	The metric used, e.g. phase, amplitude, power. Data Type: text Name: metric
—source_channels	Dataset	DynamicTableRegion pointer to the channels that this decomposition series was generated from. Extends: DynamicTableRegion Quantity: 0 or 1 Name: source_channels
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—source_timeseries	Link	Link to TimeSeries object that this data was calculated from. Metadata about electrodes and their position can be read from that ElectricalSeries so it is not necessary to store that information here. Target Type TimeSeries Name: source_timeseries

Table 2.51 Groups contained in <DecompositionSeries>

Id	Type	Description
<DecompositionSeries>	Group	Top level Group for <DecompositionSeries> Neurodata Type: DecompositionSeries Extends: TimeSeries
—source_timeseries	Link	Link to TimeSeries object that this data was calculated from. Metadata about electrodes and their position can be read from that ElectricalSeries so it is not necessary to store that information here. Target Type TimeSeries Name: source_timeseries
—bands	Group	Table for describing the bands that this series was generated from. There should be one row in this table for each band. Extends: DynamicTable Name: bands
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.6.4.1. Groups: bands

Table for describing the bands that this series was generated from. There should be one row in this table for each band.

• Extends: DynamicTable

• Name: bands

Table 2.52 Datasets, Links, and Attributes contained in bands

Id	Type	Description
bands	Group	Top level Group for bands Extends: DynamicTable Name: bands
—band_name	Dataset	Name of the band, e.g. theta. Extends: VectorData Data Type: text Name: band_name
—band_limits	Dataset	Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center. Extends: VectorData Data Type: float32 Dimensions: [‘num_bands’, ‘low, high’] Shape: [None, 2] Name: band_limits
—band_mean	Dataset	The mean Gaussian filters, in Hz. Extends: VectorData Data Type: float32 Dimensions: [‘num_bands’] Shape: [None] Name: band_mean
—band_stdev	Dataset	The standard deviation of Gaussian filters, in Hz. Extends: VectorData Data Type: float32 Dimensions: [‘num_bands’] Shape: [None] Name: band_stdev

2.6.4.2. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.6.5. Units

Overview: Data about spiking units. Event times of observed units (e.g. cell, synapse, etc.) should be concatenated and stored in spike_times.

Units extends DynamicTable and includes all elements of DynamicTable with the following additions or changes.

• Extends: DynamicTable

• Primitive Type: Group

• Default Name: Units

• Inherits from: DynamicTable, Container

• Source filename: nwb.misc.yaml

• Source Specification: see Section 3.7.5

Table 2.53 Datasets, Links, and Attributes contained in <Units>

Id	Type	Description
<Units>	Group	Top level Group for <Units> Neurodata Type: Units Extends: DynamicTable Default Name: Units
—colnames	Attribute	The names of the columns in this table. This should be used to specify an order to the columns. Data Type: text Dimensions: [‘num_columns’] Shape: [None] Name: colnames
—description	Attribute	Description of what is in this dynamic table. Data Type: text Name: description
—spike_times_index	Dataset	Index into the spike_times dataset. Extends: VectorIndex Quantity: 0 or 1 Name: spike_times_index
—spike_times	Dataset	Spike times for each unit in seconds. Extends: VectorData Quantity: 0 or 1 Data Type: float64 Name: spike_times
——resolution	Attribute	The smallest possible difference between two spike times. Usually 1 divided by the acquisition sampling rate from which spike times were extracted, but could be larger if the acquisition time series was downsampled or smaller if the acquisition time series was smoothed/interpolated and it is possible for the spike time to be between samples. Data Type: float64 Required: False Name: resolution
—obs_intervals_index	Dataset	Index into the obs_intervals dataset. Extends: VectorIndex Quantity: 0 or 1 Name: obs_intervals_index
—obs_intervals	Dataset	Observation intervals for each unit. Extends: VectorData Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_intervals’, ‘start|end’] Shape: [None, 2] Name: obs_intervals
—electrodes_index	Dataset	Index into electrodes. Extends: VectorIndex Quantity: 0 or 1 Name: electrodes_index
—electrodes	Dataset	Electrode that each spike unit came from, specified using a DynamicTableRegion. Extends: DynamicTableRegion Quantity: 0 or 1 Name: electrodes
—electrode_group	Dataset	Electrode group that each spike unit came from. Extends: VectorData Quantity: 0 or 1 Data Type: object reference to ElectrodeGroup Name: electrode_group
—waveform_mean	Dataset	Spike waveform mean for each spike unit. Extends: VectorData Quantity: 0 or 1 Data Type: float32 Dimensions: [[‘num_units’, ‘num_samples’], [‘num_units’, ‘num_samples’, ‘num_electrodes’]] Shape: [[None, None], [None, None, None]] Name: waveform_mean
——sampling_rate	Attribute	Sampling rate, in hertz. Data Type: float32 Required: False Name: sampling_rate
——unit	Attribute	Unit of measurement. This value is fixed to ‘volts’. Data Type: text Value: volts Name: unit
—waveform_sd	Dataset	Spike waveform standard deviation for each spike unit. Extends: VectorData Quantity: 0 or 1 Data Type: float32 Dimensions: [[‘num_units’, ‘num_samples’], [‘num_units’, ‘num_samples’, ‘num_electrodes’]] Shape: [[None, None], [None, None, None]] Name: waveform_sd
——sampling_rate	Attribute	Sampling rate, in hertz. Data Type: float32 Required: False Name: sampling_rate
——unit	Attribute	Unit of measurement. This value is fixed to ‘volts’. Data Type: text Value: volts Name: unit
—waveforms	Dataset	Individual waveforms for each spike on each electrode. This is a doubly indexed column. The ‘waveforms_index’ column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The ‘waveforms_index_index’ column indexes the ‘waveforms_index’ column to indicate which spike events belong to a given unit. For example, if the ‘waveforms_index_index’ column has values [2, 5, 6], then the first 2 elements of the ‘waveforms_index’ column correspond to the 2 spike events of the first unit, the next 3 elements of the ‘waveforms_index’ column correspond to the 3 spike events of the second unit, and the next 1 element of the ‘waveforms_index’ column corresponds to the 1 spike event of the third unit. If the ‘waveforms_index’ column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the ‘waveforms’ column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the ‘waveforms_index’ column will have values 1, 2, …, N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The ‘electrodes’ column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the ‘electrodes’ column of this table. The number of samples for each waveform must be the same. Extends: VectorData Quantity: 0 or 1 Data Type: numeric Dimensions: [‘num_waveforms’, ‘num_samples’] Shape: [None, None] Name: waveforms
——sampling_rate	Attribute	Sampling rate, in hertz. Data Type: float32 Required: False Name: sampling_rate
——unit	Attribute	Unit of measurement. This value is fixed to ‘volts’. Data Type: text Value: volts Name: unit
—waveforms_index	Dataset	Index into the waveforms dataset. One value for every spike event. See ‘waveforms’ for more detail. Extends: VectorIndex Quantity: 0 or 1 Name: waveforms_index
—waveforms_index_index	Dataset	Index into the waveforms_index dataset. One value for every unit (row in the table). See ‘waveforms’ for more detail. Extends: VectorIndex Quantity: 0 or 1 Name: waveforms_index_index
—id	Dataset	Array of unique identifiers for the rows of this dynamic table. Extends: ElementIdentifiers Data Type: int Dimensions: [‘num_rows’] Shape: [None] Name: id
—<VectorData>	Dataset	Vector columns, including index columns, of this dynamic table. Extends: VectorData Quantity: 0 or more

2.7. Behavior

This source module contains neurodata_types for behavior data.

2.7.1. SpatialSeries

Overview: Direction, e.g., of gaze or travel, or position. The TimeSeries::data field is a 2D array storing position or direction relative to some reference frame. Array structure: [num measurements] [num dimensions]. Each SpatialSeries has a text dataset reference_frame that indicates the zero-position, or the zero-axes for direction. For example, if representing gaze direction, ‘straight-ahead’ might be a specific pixel on the monitor, or some other point in space. For position data, the 0,0 point might be the top-left corner of an enclosure, as viewed from the tracking camera. The unit of data will indicate how to interpret SpatialSeries values.

SpatialSeries extends TimeSeries and includes all elements of TimeSeries with the following additions or changes.

• Extends: TimeSeries

• Primitive Type: Group

• Inherits from: TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.behavior.yaml

• Source Specification: see Section 3.8.1

Table 2.54 Datasets, Links, and Attributes contained in <SpatialSeries>

Id	Type	Description
<SpatialSeries>	Group	Top level Group for <SpatialSeries> Neurodata Type: SpatialSeries Extends: TimeSeries
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	1-D or 2-D array storing position or direction relative to some reference frame. Data Type: numeric Dimensions: [[‘num_times’], [‘num_times’, ‘x’], [‘num_times’, ‘x,y’], [‘num_times’, ‘x,y,z’]] Shape: [[None], [None, 1], [None, 2], [None, 3]] Name: data
——unit	Attribute	Base unit of measurement for working with the data. The default value is ‘meters’. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Required: False Default Value: meters Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—reference_frame	Dataset	Description defining what exactly ‘straight-ahead’ means. Quantity: 0 or 1 Data Type: text Name: reference_frame
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description

Table 2.55 Groups contained in <SpatialSeries>

Id	Type	Description
<SpatialSeries>	Group	Top level Group for <SpatialSeries> Neurodata Type: SpatialSeries Extends: TimeSeries
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.7.1.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.7.2. BehavioralEpochs

Overview: TimeSeries for storing behavioral epochs. The objective of this and the other two Behavioral interfaces (e.g. BehavioralEvents and BehavioralTimeSeries) is to provide generic hooks for software tools/scripts. This allows a tool/script to take the output one specific interface (e.g., UnitTimes) and plot that data relative to another data modality (e.g., behavioral events) without having to define all possible modalities in advance. Declaring one of these interfaces means that one or more TimeSeries of the specified type is published. These TimeSeries should reside in a group having the same name as the interface. For example, if a BehavioralTimeSeries interface is declared, the module will have one or more TimeSeries defined in the module sub-group ‘BehavioralTimeSeries’. BehavioralEpochs should use IntervalSeries. BehavioralEvents is used for irregular events. BehavioralTimeSeries is for continuous data.

BehavioralEpochs extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: BehavioralEpochs

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.behavior.yaml

• Source Specification: see Section 3.8.2

Table 2.56 Groups contained in <BehavioralEpochs>

Id	Type	Description
<BehavioralEpochs>	Group	Top level Group for <BehavioralEpochs> Neurodata Type: BehavioralEpochs Extends: NWBDataInterface Default Name: BehavioralEpochs
—<IntervalSeries>	Group	IntervalSeries object containing start and stop times of epochs. Extends: IntervalSeries Quantity: 0 or more

2.7.2.1. Groups: <IntervalSeries>

IntervalSeries object containing start and stop times of epochs.

• Extends: IntervalSeries

• Quantity: 0 or more

2.7.3. BehavioralEvents

Overview: TimeSeries for storing behavioral events. See description of <a href=”#BehavioralEpochs”>BehavioralEpochs</a> for more details.

BehavioralEvents extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: BehavioralEvents

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.behavior.yaml

• Source Specification: see Section 3.8.3

Table 2.57 Groups contained in <BehavioralEvents>

Id	Type	Description
<BehavioralEvents>	Group	Top level Group for <BehavioralEvents> Neurodata Type: BehavioralEvents Extends: NWBDataInterface Default Name: BehavioralEvents
—<TimeSeries>	Group	TimeSeries object containing behavioral events. Extends: TimeSeries Quantity: 0 or more

2.7.3.1. Groups: <TimeSeries>

TimeSeries object containing behavioral events.

• Extends: TimeSeries

• Quantity: 0 or more

2.7.4. BehavioralTimeSeries

Overview: TimeSeries for storing Behavoioral time series data. See description of <a href=”#BehavioralEpochs”>BehavioralEpochs</a> for more details.

BehavioralTimeSeries extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: BehavioralTimeSeries

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.behavior.yaml

• Source Specification: see Section 3.8.4

Table 2.58 Groups contained in <BehavioralTimeSeries>

Id	Type	Description
<BehavioralTimeSeries>	Group	Top level Group for <BehavioralTimeSeries> Neurodata Type: BehavioralTimeSeries Extends: NWBDataInterface Default Name: BehavioralTimeSeries
—<TimeSeries>	Group	TimeSeries object containing continuous behavioral data. Extends: TimeSeries Quantity: 0 or more

2.7.4.1. Groups: <TimeSeries>

TimeSeries object containing continuous behavioral data.

• Extends: TimeSeries

• Quantity: 0 or more

2.7.5. PupilTracking

Overview: Eye-tracking data, representing pupil size.

PupilTracking extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: PupilTracking

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.behavior.yaml

• Source Specification: see Section 3.8.5

Table 2.59 Groups contained in <PupilTracking>

Id	Type	Description
<PupilTracking>	Group	Top level Group for <PupilTracking> Neurodata Type: PupilTracking Extends: NWBDataInterface Default Name: PupilTracking
—<TimeSeries>	Group	TimeSeries object containing time series data on pupil size. Extends: TimeSeries Quantity: 1 or more

2.7.5.1. Groups: <TimeSeries>

TimeSeries object containing time series data on pupil size.

• Extends: TimeSeries

• Quantity: 1 or more

2.7.6. EyeTracking

Overview: Eye-tracking data, representing direction of gaze.

EyeTracking extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: EyeTracking

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.behavior.yaml

• Source Specification: see Section 3.8.6

Table 2.60 Groups contained in <EyeTracking>

Id	Type	Description
<EyeTracking>	Group	Top level Group for <EyeTracking> Neurodata Type: EyeTracking Extends: NWBDataInterface Default Name: EyeTracking
—<SpatialSeries>	Group	SpatialSeries object containing data measuring direction of gaze. Extends: SpatialSeries Quantity: 0 or more

2.7.6.1. Groups: <SpatialSeries>

SpatialSeries object containing data measuring direction of gaze.

• Extends: SpatialSeries

• Quantity: 0 or more

2.7.7. CompassDirection

Overview: With a CompassDirection interface, a module publishes a SpatialSeries object representing a floating point value for theta. The SpatialSeries::reference_frame field should indicate what direction corresponds to 0 and which is the direction of rotation (this should be clockwise). The si_unit for the SpatialSeries should be radians or degrees.

CompassDirection extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: CompassDirection

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.behavior.yaml

• Source Specification: see Section 3.8.7

Table 2.61 Groups contained in <CompassDirection>

Id	Type	Description
<CompassDirection>	Group	Top level Group for <CompassDirection> Neurodata Type: CompassDirection Extends: NWBDataInterface Default Name: CompassDirection
—<SpatialSeries>	Group	SpatialSeries object containing direction of gaze travel. Extends: SpatialSeries Quantity: 0 or more

2.7.7.1. Groups: <SpatialSeries>

SpatialSeries object containing direction of gaze travel.

• Extends: SpatialSeries

• Quantity: 0 or more

2.7.8. Position

Overview: Position data, whether along the x, x/y or x/y/z axis.

Position extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: Position

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.behavior.yaml

• Source Specification: see Section 3.8.8

Table 2.62 Groups contained in <Position>

Id	Type	Description
<Position>	Group	Top level Group for <Position> Neurodata Type: Position Extends: NWBDataInterface Default Name: Position
—<SpatialSeries>	Group	SpatialSeries object containing position data. Extends: SpatialSeries Quantity: 1 or more

2.7.8.1. Groups: <SpatialSeries>

SpatialSeries object containing position data.

• Extends: SpatialSeries

• Quantity: 1 or more

2.8. Extracellular electrophysiology

This source module contains neurodata_types for extracellular electrophysiology data.

2.8.1. ElectricalSeries

Overview: A time series of acquired voltage data from extracellular recordings. The data field is an int or float array storing data in volts. The first dimension should always represent time. The second dimension, if present, should represent channels.

ElectricalSeries extends TimeSeries and includes all elements of TimeSeries with the following additions or changes.

• Extends: TimeSeries

• Primitive Type: Group

• Inherits from: TimeSeries, NWBDataInterface, NWBContainer, Container

• Subtypes: SpikeEventSeries

• Source filename: nwb.ecephys.yaml

• Source Specification: see Section 3.9.1

Table 2.63 Datasets, Links, and Attributes contained in <ElectricalSeries>

Id	Type	Description
<ElectricalSeries>	Group	Top level Group for <ElectricalSeries> Neurodata Type: ElectricalSeries Extends: TimeSeries
—filtering	Attribute	Filtering applied to all channels of the data. For example, if this ElectricalSeries represents high-pass-filtered data (also known as AP Band), then this value could be “High-pass 4-pole Bessel filter at 500 Hz”. If this ElectricalSeries represents low-pass-filtered LFP data and the type of filter is unknown, then this value could be “Low-pass filter at 300 Hz”. If a non-standard filter type is used, provide as much detail about the filter properties as possible. Data Type: text Required: False Name: filtering
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Recorded voltage data. Data Type: numeric Dimensions: [[‘num_times’], [‘num_times’, ‘num_channels’], [‘num_times’, ‘num_channels’, ‘num_samples’]] Shape: [[None], [None, None], [None, None, None]] Name: data
——unit	Attribute	Base unit of measurement for working with the data. This value is fixed to ‘volts’. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’, followed by ‘channel_conversion’ (if present), and then add ‘offset’. Data Type: text Value: volts Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—electrodes	Dataset	DynamicTableRegion pointer to the electrodes that this time series was generated from. Extends: DynamicTableRegion Name: electrodes
—channel_conversion	Dataset	Channel-specific conversion factor. Multiply the data in the ‘data’ dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the ‘conversion’ attribute of ‘data’ to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels. Quantity: 0 or 1 Data Type: float32 Dimensions: [‘num_channels’] Shape: [None] Name: channel_conversion
——axis	Attribute	The zero-indexed axis of the ‘data’ dataset that the channel-specific conversion factor corresponds to. This value is fixed to 1. Data Type: int32 Value: 1 Name: axis
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description

Table 2.64 Groups contained in <ElectricalSeries>

Id	Type	Description
<ElectricalSeries>	Group	Top level Group for <ElectricalSeries> Neurodata Type: ElectricalSeries Extends: TimeSeries
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.8.1.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.8.2. SpikeEventSeries

Overview: Stores snapshots/snippets of recorded spike events (i.e., threshold crossings). This may also be raw data, as reported by ephys hardware. If so, the TimeSeries::description field should describe how events were detected. All SpikeEventSeries should reside in a module (under EventWaveform interface) even if the spikes were reported and stored by hardware. All events span the same recording channels and store snapshots of equal duration. TimeSeries::data array structure: [num events] [num channels] [num samples] (or [num events] [num samples] for single electrode).

SpikeEventSeries extends ElectricalSeries and includes all elements of ElectricalSeries with the following additions or changes.

• Extends: ElectricalSeries

• Primitive Type: Group

• Inherits from: ElectricalSeries, TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ecephys.yaml

• Source Specification: see Section 3.9.2

Table 2.65 Datasets, Links, and Attributes contained in <SpikeEventSeries>

Id	Type	Description
<SpikeEventSeries>	Group	Top level Group for <SpikeEventSeries> Neurodata Type: SpikeEventSeries Extends: ElectricalSeries
—filtering	Attribute	Filtering applied to all channels of the data. For example, if this ElectricalSeries represents high-pass-filtered data (also known as AP Band), then this value could be “High-pass 4-pole Bessel filter at 500 Hz”. If this ElectricalSeries represents low-pass-filtered LFP data and the type of filter is unknown, then this value could be “Low-pass filter at 300 Hz”. If a non-standard filter type is used, provide as much detail about the filter properties as possible. Data Type: text Required: False Name: filtering
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Spike waveforms. Data Type: numeric Dimensions: [[‘num_events’, ‘num_samples’], [‘num_events’, ‘num_channels’, ‘num_samples’]] Shape: [[None, None], [None, None, None]] Name: data
——unit	Attribute	Unit of measurement for waveforms, which is fixed to ‘volts’. Data Type: text Value: volts Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Timestamps are required for the events. Unlike for TimeSeries, timestamps are required for SpikeEventSeries and are thus re-specified here. Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—electrodes	Dataset	DynamicTableRegion pointer to the electrodes that this time series was generated from. Extends: DynamicTableRegion Name: electrodes
—channel_conversion	Dataset	Channel-specific conversion factor. Multiply the data in the ‘data’ dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the ‘conversion’ attribute of ‘data’ to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels. Quantity: 0 or 1 Data Type: float32 Dimensions: [‘num_channels’] Shape: [None] Name: channel_conversion
——axis	Attribute	The zero-indexed axis of the ‘data’ dataset that the channel-specific conversion factor corresponds to. This value is fixed to 1. Data Type: int32 Value: 1 Name: axis
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description

Table 2.66 Groups contained in <SpikeEventSeries>

Id	Type	Description
<SpikeEventSeries>	Group	Top level Group for <SpikeEventSeries> Neurodata Type: SpikeEventSeries Extends: ElectricalSeries
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.8.2.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.8.3. FeatureExtraction

Overview: Features, such as PC1 and PC2, that are extracted from signals stored in a SpikeEventSeries or other source.

FeatureExtraction extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: FeatureExtraction

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ecephys.yaml

• Source Specification: see Section 3.9.3

Table 2.67 Datasets, Links, and Attributes contained in <FeatureExtraction>

Id	Type	Description
<FeatureExtraction>	Group	Top level Group for <FeatureExtraction> Neurodata Type: FeatureExtraction Extends: NWBDataInterface Default Name: FeatureExtraction
—description	Dataset	Description of features (eg, ‘’PC1’’) for each of the extracted features. Data Type: text Dimensions: [‘num_features’] Shape: [None] Name: description
—features	Dataset	Multi-dimensional array of features extracted from each event. Data Type: float32 Dimensions: [‘num_events’, ‘num_channels’, ‘num_features’] Shape: [None, None, None] Name: features
—times	Dataset	Times of events that features correspond to (can be a link). Data Type: float64 Dimensions: [‘num_events’] Shape: [None] Name: times
—electrodes	Dataset	DynamicTableRegion pointer to the electrodes that this time series was generated from. Extends: DynamicTableRegion Name: electrodes

2.8.4. EventDetection

Overview: Detected spike events from voltage trace(s).

EventDetection extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: EventDetection

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ecephys.yaml

• Source Specification: see Section 3.9.4

Table 2.68 Datasets, Links, and Attributes contained in <EventDetection>

Id	Type	Description
<EventDetection>	Group	Top level Group for <EventDetection> Neurodata Type: EventDetection Extends: NWBDataInterface Default Name: EventDetection
—detection_method	Dataset	Description of how events were detected, such as voltage threshold, or dV/dT threshold, as well as relevant values. Data Type: text Name: detection_method
—source_idx	Dataset	Indices (zero-based) into source ElectricalSeries::data array corresponding to time of event. ‘’description’’ should define what is meant by time of event (e.g., .25 ms before action potential peak, zero-crossing time, etc). The index points to each event from the raw data. Data Type: int32 Dimensions: [‘num_events’] Shape: [None] Name: source_idx
—times	Dataset	Timestamps of events, in seconds. Data Type: float64 Dimensions: [‘num_events’] Shape: [None] Name: times
——unit	Attribute	Unit of measurement for event times, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—source_electricalseries	Link	Link to the ElectricalSeries that this data was calculated from. Metadata about electrodes and their position can be read from that ElectricalSeries so it’s not necessary to include that information here. Target Type ElectricalSeries Name: source_electricalseries

Table 2.69 Groups contained in <EventDetection>

Id	Type	Description
<EventDetection>	Group	Top level Group for <EventDetection> Neurodata Type: EventDetection Extends: NWBDataInterface Default Name: EventDetection
—source_electricalseries	Link	Link to the ElectricalSeries that this data was calculated from. Metadata about electrodes and their position can be read from that ElectricalSeries so it’s not necessary to include that information here. Target Type ElectricalSeries Name: source_electricalseries

2.8.5. EventWaveform

Overview: Represents either the waveforms of detected events, as extracted from a raw data trace in /acquisition, or the event waveforms that were stored during experiment acquisition.

EventWaveform extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: EventWaveform

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ecephys.yaml

• Source Specification: see Section 3.9.5

Table 2.70 Groups contained in <EventWaveform>

Id	Type	Description
<EventWaveform>	Group	Top level Group for <EventWaveform> Neurodata Type: EventWaveform Extends: NWBDataInterface Default Name: EventWaveform
—<SpikeEventSeries>	Group	SpikeEventSeries object(s) containing detected spike event waveforms. Extends: SpikeEventSeries Quantity: 0 or more

2.8.5.1. Groups: <SpikeEventSeries>

SpikeEventSeries object(s) containing detected spike event waveforms.

• Extends: SpikeEventSeries

• Quantity: 0 or more

2.8.6. FilteredEphys

Overview: Electrophysiology data from one or more channels that has been subjected to filtering. Examples of filtered data include Theta and Gamma (LFP has its own interface). FilteredEphys modules publish an ElectricalSeries for each filtered channel or set of channels. The name of each ElectricalSeries is arbitrary but should be informative. The source of the filtered data, whether this is from analysis of another time series or as acquired by hardware, should be noted in each’s TimeSeries::description field. There is no assumed 1::1 correspondence between filtered ephys signals and electrodes, as a single signal can apply to many nearby electrodes, and one electrode may have different filtered (e.g., theta and/or gamma) signals represented. Filter properties should be noted in the ElectricalSeries ‘filtering’ attribute.

FilteredEphys extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: FilteredEphys

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ecephys.yaml

• Source Specification: see Section 3.9.6

Table 2.71 Groups contained in <FilteredEphys>

Id	Type	Description
<FilteredEphys>	Group	Top level Group for <FilteredEphys> Neurodata Type: FilteredEphys Extends: NWBDataInterface Default Name: FilteredEphys
—<ElectricalSeries>	Group	ElectricalSeries object(s) containing filtered electrophysiology data. Extends: ElectricalSeries Quantity: 1 or more

2.8.6.1. Groups: <ElectricalSeries>

ElectricalSeries object(s) containing filtered electrophysiology data.

• Extends: ElectricalSeries

• Quantity: 1 or more

2.8.7. LFP

Overview: LFP data from one or more channels. The electrode map in each published ElectricalSeries will identify which channels are providing LFP data. Filter properties should be noted in the ElectricalSeries ‘filtering’ attribute.

LFP extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: LFP

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ecephys.yaml

• Source Specification: see Section 3.9.7

Table 2.72 Groups contained in <LFP>

Id	Type	Description
<LFP>	Group	Top level Group for <LFP> Neurodata Type: LFP Extends: NWBDataInterface Default Name: LFP
—<ElectricalSeries>	Group	ElectricalSeries object(s) containing LFP data for one or more channels. Extends: ElectricalSeries Quantity: 1 or more

2.8.7.1. Groups: <ElectricalSeries>

ElectricalSeries object(s) containing LFP data for one or more channels.

• Extends: ElectricalSeries

• Quantity: 1 or more

2.8.8. ElectrodeGroup

Overview: A physical grouping of electrodes, e.g. a shank of an array.

ElectrodeGroup extends NWBContainer and includes all elements of NWBContainer with the following additions or changes.

• Extends: NWBContainer

• Primitive Type: Group

• Inherits from: NWBContainer, Container

• Source filename: nwb.ecephys.yaml

• Source Specification: see Section 3.9.8

Table 2.73 Datasets, Links, and Attributes contained in <ElectrodeGroup>

Id	Type	Description
<ElectrodeGroup>	Group	Top level Group for <ElectrodeGroup> Neurodata Type: ElectrodeGroup Extends: NWBContainer
—description	Attribute	Description of this electrode group. Data Type: text Name: description
—location	Attribute	Location of electrode group. Specify the area, layer, comments on estimation of area/layer, etc. Use standard atlas names for anatomical regions when possible. Data Type: text Name: location
—position	Dataset	stereotaxic or common framework coordinates Quantity: 0 or 1 Data Type: Compound data type with the following elements: x: x coordinate (dtype= float32 ) y: y coordinate (dtype= float32 ) z: z coordinate (dtype= float32 ) Name: position
—device	Link	Link to the device that was used to record from this electrode group. Target Type Device Name: device

Table 2.74 Groups contained in <ElectrodeGroup>

Id	Type	Description
<ElectrodeGroup>	Group	Top level Group for <ElectrodeGroup> Neurodata Type: ElectrodeGroup Extends: NWBContainer
—device	Link	Link to the device that was used to record from this electrode group. Target Type Device Name: device

2.8.9. ClusterWaveforms

Overview: DEPRECATED The mean waveform shape, including standard deviation, of the different clusters. Ideally, the waveform analysis should be performed on data that is only high-pass filtered. This is a separate module because it is expected to require updating. For example, IMEC probes may require different storage requirements to store/display mean waveforms, requiring a new interface or an extension of this one.

ClusterWaveforms extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: ClusterWaveforms

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ecephys.yaml

• Source Specification: see Section 3.9.9

Table 2.75 Datasets, Links, and Attributes contained in <ClusterWaveforms>

Id	Type	Description
<ClusterWaveforms>	Group	Top level Group for <ClusterWaveforms> Neurodata Type: ClusterWaveforms Extends: NWBDataInterface Default Name: ClusterWaveforms
—waveform_filtering	Dataset	Filtering applied to data before generating mean/sd Data Type: text Name: waveform_filtering
—waveform_mean	Dataset	The mean waveform for each cluster, using the same indices for each wave as cluster numbers in the associated Clustering module (i.e, cluster 3 is in array slot [3]). Waveforms corresponding to gaps in cluster sequence should be empty (e.g., zero- filled) Data Type: float32 Dimensions: [‘num_clusters’, ‘num_samples’] Shape: [None, None] Name: waveform_mean
—waveform_sd	Dataset	Stdev of waveforms for each cluster, using the same indices as in mean Data Type: float32 Dimensions: [‘num_clusters’, ‘num_samples’] Shape: [None, None] Name: waveform_sd
—clustering_interface	Link	Link to Clustering interface that was the source of the clustered data Target Type Clustering Name: clustering_interface

Table 2.76 Groups contained in <ClusterWaveforms>

Id	Type	Description
<ClusterWaveforms>	Group	Top level Group for <ClusterWaveforms> Neurodata Type: ClusterWaveforms Extends: NWBDataInterface Default Name: ClusterWaveforms
—clustering_interface	Link	Link to Clustering interface that was the source of the clustered data Target Type Clustering Name: clustering_interface

2.8.10. Clustering

Overview: DEPRECATED Clustered spike data, whether from automatic clustering tools (e.g., klustakwik) or as a result of manual sorting.

Clustering extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: Clustering

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ecephys.yaml

• Source Specification: see Section 3.9.10

Table 2.77 Datasets, Links, and Attributes contained in <Clustering>

Id	Type	Description
<Clustering>	Group	Top level Group for <Clustering> Neurodata Type: Clustering Extends: NWBDataInterface Default Name: Clustering
—description	Dataset	Description of clusters or clustering, (e.g. cluster 0 is noise, clusters curated using Klusters, etc) Data Type: text Name: description
—num	Dataset	Cluster number of each event Data Type: int32 Dimensions: [‘num_events’] Shape: [None] Name: num
—peak_over_rms	Dataset	Maximum ratio of waveform peak to RMS on any channel in the cluster (provides a basic clustering metric). Data Type: float32 Dimensions: [‘num_clusters’] Shape: [None] Name: peak_over_rms
—times	Dataset	Times of clustered events, in seconds. This may be a link to times field in associated FeatureExtraction module. Data Type: float64 Dimensions: [‘num_events’] Shape: [None] Name: times

2.9. Intracellular electrophysiology

This source module contains neurodata_types for intracellular electrophysiology data.

2.9.1. PatchClampSeries

Overview: An abstract base class for patch-clamp data - stimulus or response, current or voltage.

PatchClampSeries extends TimeSeries and includes all elements of TimeSeries with the following additions or changes.

• Extends: TimeSeries

• Primitive Type: Group

• Inherits from: TimeSeries, NWBDataInterface, NWBContainer, Container

• Subtypes: VoltageClampSeries, IZeroClampSeries, CurrentClampSeries, VoltageClampStimulusSeries, CurrentClampStimulusSeries

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.1

Table 2.78 Datasets, Links, and Attributes contained in <PatchClampSeries>

Id	Type	Description
<PatchClampSeries>	Group	Top level Group for <PatchClampSeries> Neurodata Type: PatchClampSeries Extends: TimeSeries
—stimulus_description	Attribute	Protocol/stimulus name for this patch-clamp dataset. Data Type: text Name: stimulus_description
—sweep_number	Attribute	Sweep number, allows to group different PatchClampSeries together. Data Type: uint32 Required: False Name: sweep_number
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Recorded voltage or current. Data Type: numeric Dimensions: [‘num_times’] Shape: [None] Name: data
——unit	Attribute	Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—gain	Dataset	Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp). Quantity: 0 or 1 Data Type: float32 Name: gain
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—electrode	Link	Link to IntracellularElectrode object that describes the electrode that was used to apply or record this data. Target Type IntracellularElectrode Name: electrode

Table 2.79 Groups contained in <PatchClampSeries>

Id	Type	Description
<PatchClampSeries>	Group	Top level Group for <PatchClampSeries> Neurodata Type: PatchClampSeries Extends: TimeSeries
—electrode	Link	Link to IntracellularElectrode object that describes the electrode that was used to apply or record this data. Target Type IntracellularElectrode Name: electrode
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.9.1.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.9.2. CurrentClampSeries

Overview: Voltage data from an intracellular current-clamp recording. A corresponding CurrentClampStimulusSeries (stored separately as a stimulus) is used to store the current injected.

CurrentClampSeries extends PatchClampSeries and includes all elements of PatchClampSeries with the following additions or changes.

• Extends: PatchClampSeries

• Primitive Type: Group

• Inherits from: PatchClampSeries, TimeSeries, NWBDataInterface, NWBContainer, Container

• Subtypes: IZeroClampSeries

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.2

Table 2.80 Datasets, Links, and Attributes contained in <CurrentClampSeries>

Id	Type	Description
<CurrentClampSeries>	Group	Top level Group for <CurrentClampSeries> Neurodata Type: CurrentClampSeries Extends: PatchClampSeries
—stimulus_description	Attribute	Protocol/stimulus name for this patch-clamp dataset. Data Type: text Name: stimulus_description
—sweep_number	Attribute	Sweep number, allows to group different PatchClampSeries together. Data Type: uint32 Required: False Name: sweep_number
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Recorded voltage. Name: data
——unit	Attribute	Base unit of measurement for working with the data. which is fixed to ‘volts’. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Value: volts Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—bias_current	Dataset	Bias current, in amps. Quantity: 0 or 1 Data Type: float32 Name: bias_current
—bridge_balance	Dataset	Bridge balance, in ohms. Quantity: 0 or 1 Data Type: float32 Name: bridge_balance
—capacitance_compensation	Dataset	Capacitance compensation, in farads. Quantity: 0 or 1 Data Type: float32 Name: capacitance_compensation
—gain	Dataset	Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp). Quantity: 0 or 1 Data Type: float32 Name: gain
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—electrode	Link	Link to IntracellularElectrode object that describes the electrode that was used to apply or record this data. Target Type IntracellularElectrode Name: electrode

Table 2.81 Groups contained in <CurrentClampSeries>

Id	Type	Description
<CurrentClampSeries>	Group	Top level Group for <CurrentClampSeries> Neurodata Type: CurrentClampSeries Extends: PatchClampSeries
—electrode	Link	Link to IntracellularElectrode object that describes the electrode that was used to apply or record this data. Target Type IntracellularElectrode Name: electrode
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.9.2.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.9.3. IZeroClampSeries

Overview: Voltage data from an intracellular recording when all current and amplifier settings are off (i.e., CurrentClampSeries fields will be zero). There is no CurrentClampStimulusSeries associated with an IZero series because the amplifier is disconnected and no stimulus can reach the cell.

IZeroClampSeries extends CurrentClampSeries and includes all elements of CurrentClampSeries with the following additions or changes.

• Extends: CurrentClampSeries

• Primitive Type: Group

• Inherits from: CurrentClampSeries, PatchClampSeries, TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.3

Table 2.82 Datasets, Links, and Attributes contained in <IZeroClampSeries>

Id	Type	Description
<IZeroClampSeries>	Group	Top level Group for <IZeroClampSeries> Neurodata Type: IZeroClampSeries Extends: CurrentClampSeries
—stimulus_description	Attribute	An IZeroClampSeries has no stimulus, so this attribute is automatically set to “N/A” Data Type: text Value: N/A Name: stimulus_description
—sweep_number	Attribute	Sweep number, allows to group different PatchClampSeries together. Data Type: uint32 Required: False Name: sweep_number
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—bias_current	Dataset	Bias current, in amps, fixed to 0.0. Data Type: float32 Name: bias_current
—bridge_balance	Dataset	Bridge balance, in ohms, fixed to 0.0. Data Type: float32 Name: bridge_balance
—capacitance_compensation	Dataset	Capacitance compensation, in farads, fixed to 0.0. Data Type: float32 Name: capacitance_compensation
—data	Dataset	Recorded voltage. Name: data
——unit	Attribute	Base unit of measurement for working with the data. which is fixed to ‘volts’. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Value: volts Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—gain	Dataset	Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp). Quantity: 0 or 1 Data Type: float32 Name: gain
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—electrode	Link	Link to IntracellularElectrode object that describes the electrode that was used to apply or record this data. Target Type IntracellularElectrode Name: electrode

Table 2.83 Groups contained in <IZeroClampSeries>

Id	Type	Description
<IZeroClampSeries>	Group	Top level Group for <IZeroClampSeries> Neurodata Type: IZeroClampSeries Extends: CurrentClampSeries
—electrode	Link	Link to IntracellularElectrode object that describes the electrode that was used to apply or record this data. Target Type IntracellularElectrode Name: electrode
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.9.3.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.9.4. CurrentClampStimulusSeries

Overview: Stimulus current applied during current clamp recording.

CurrentClampStimulusSeries extends PatchClampSeries and includes all elements of PatchClampSeries with the following additions or changes.

• Extends: PatchClampSeries

• Primitive Type: Group

• Inherits from: PatchClampSeries, TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.4

Table 2.84 Datasets, Links, and Attributes contained in <CurrentClampStimulusSeries>

Id	Type	Description
<CurrentClampStimulusSeries>	Group	Top level Group for <CurrentClampStimulusSeries> Neurodata Type: CurrentClampStimulusSeries Extends: PatchClampSeries
—stimulus_description	Attribute	Protocol/stimulus name for this patch-clamp dataset. Data Type: text Name: stimulus_description
—sweep_number	Attribute	Sweep number, allows to group different PatchClampSeries together. Data Type: uint32 Required: False Name: sweep_number
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Stimulus current applied. Name: data
——unit	Attribute	Base unit of measurement for working with the data. which is fixed to ‘amperes’. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Value: amperes Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—gain	Dataset	Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp). Quantity: 0 or 1 Data Type: float32 Name: gain
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—electrode	Link	Link to IntracellularElectrode object that describes the electrode that was used to apply or record this data. Target Type IntracellularElectrode Name: electrode

Table 2.85 Groups contained in <CurrentClampStimulusSeries>

Id	Type	Description
<CurrentClampStimulusSeries>	Group	Top level Group for <CurrentClampStimulusSeries> Neurodata Type: CurrentClampStimulusSeries Extends: PatchClampSeries
—electrode	Link	Link to IntracellularElectrode object that describes the electrode that was used to apply or record this data. Target Type IntracellularElectrode Name: electrode
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.9.4.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.9.5. VoltageClampSeries

Overview: Current data from an intracellular voltage-clamp recording. A corresponding VoltageClampStimulusSeries (stored separately as a stimulus) is used to store the voltage injected.

VoltageClampSeries extends PatchClampSeries and includes all elements of PatchClampSeries with the following additions or changes.

• Extends: PatchClampSeries

• Primitive Type: Group

• Inherits from: PatchClampSeries, TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.5

Table 2.86 Datasets, Links, and Attributes contained in <VoltageClampSeries>

Id	Type	Description
<VoltageClampSeries>	Group	Top level Group for <VoltageClampSeries> Neurodata Type: VoltageClampSeries Extends: PatchClampSeries
—stimulus_description	Attribute	Protocol/stimulus name for this patch-clamp dataset. Data Type: text Name: stimulus_description
—sweep_number	Attribute	Sweep number, allows to group different PatchClampSeries together. Data Type: uint32 Required: False Name: sweep_number
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Recorded current. Name: data
——unit	Attribute	Base unit of measurement for working with the data. which is fixed to ‘amperes’. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Value: amperes Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—capacitance_fast	Dataset	Fast capacitance, in farads. Quantity: 0 or 1 Data Type: float32 Name: capacitance_fast
——unit	Attribute	Unit of measurement for capacitance_fast, which is fixed to ‘farads’. Data Type: text Value: farads Name: unit
—capacitance_slow	Dataset	Slow capacitance, in farads. Quantity: 0 or 1 Data Type: float32 Name: capacitance_slow
——unit	Attribute	Unit of measurement for capacitance_fast, which is fixed to ‘farads’. Data Type: text Value: farads Name: unit
—resistance_comp_bandwidth	Dataset	Resistance compensation bandwidth, in hertz. Quantity: 0 or 1 Data Type: float32 Name: resistance_comp_bandwidth
——unit	Attribute	Unit of measurement for resistance_comp_bandwidth, which is fixed to ‘hertz’. Data Type: text Value: hertz Name: unit
—resistance_comp_correction	Dataset	Resistance compensation correction, in percent. Quantity: 0 or 1 Data Type: float32 Name: resistance_comp_correction
——unit	Attribute	Unit of measurement for resistance_comp_correction, which is fixed to ‘percent’. Data Type: text Value: percent Name: unit
—resistance_comp_prediction	Dataset	Resistance compensation prediction, in percent. Quantity: 0 or 1 Data Type: float32 Name: resistance_comp_prediction
——unit	Attribute	Unit of measurement for resistance_comp_prediction, which is fixed to ‘percent’. Data Type: text Value: percent Name: unit
—whole_cell_capacitance_comp	Dataset	Whole cell capacitance compensation, in farads. Quantity: 0 or 1 Data Type: float32 Name: whole_cell_capacitance_comp
——unit	Attribute	Unit of measurement for whole_cell_capacitance_comp, which is fixed to ‘farads’. Data Type: text Value: farads Name: unit
—whole_cell_series_resistance_comp	Dataset	Whole cell series resistance compensation, in ohms. Quantity: 0 or 1 Data Type: float32 Name: whole_cell_series_resistance_comp
——unit	Attribute	Unit of measurement for whole_cell_series_resistance_comp, which is fixed to ‘ohms’. Data Type: text Value: ohms Name: unit
—gain	Dataset	Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp). Quantity: 0 or 1 Data Type: float32 Name: gain
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—electrode	Link	Link to IntracellularElectrode object that describes the electrode that was used to apply or record this data. Target Type IntracellularElectrode Name: electrode

Table 2.87 Groups contained in <VoltageClampSeries>

Id	Type	Description
<VoltageClampSeries>	Group	Top level Group for <VoltageClampSeries> Neurodata Type: VoltageClampSeries Extends: PatchClampSeries
—electrode	Link	Link to IntracellularElectrode object that describes the electrode that was used to apply or record this data. Target Type IntracellularElectrode Name: electrode
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.9.5.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.9.6. VoltageClampStimulusSeries

Overview: Stimulus voltage applied during a voltage clamp recording.

VoltageClampStimulusSeries extends PatchClampSeries and includes all elements of PatchClampSeries with the following additions or changes.

• Extends: PatchClampSeries

• Primitive Type: Group

• Inherits from: PatchClampSeries, TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.6

Table 2.88 Datasets, Links, and Attributes contained in <VoltageClampStimulusSeries>

Id	Type	Description
<VoltageClampStimulusSeries>	Group	Top level Group for <VoltageClampStimulusSeries> Neurodata Type: VoltageClampStimulusSeries Extends: PatchClampSeries
—stimulus_description	Attribute	Protocol/stimulus name for this patch-clamp dataset. Data Type: text Name: stimulus_description
—sweep_number	Attribute	Sweep number, allows to group different PatchClampSeries together. Data Type: uint32 Required: False Name: sweep_number
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Stimulus voltage applied. Name: data
——unit	Attribute	Base unit of measurement for working with the data. which is fixed to ‘volts’. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Value: volts Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—gain	Dataset	Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp). Quantity: 0 or 1 Data Type: float32 Name: gain
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—electrode	Link	Link to IntracellularElectrode object that describes the electrode that was used to apply or record this data. Target Type IntracellularElectrode Name: electrode

Table 2.89 Groups contained in <VoltageClampStimulusSeries>

Id	Type	Description
<VoltageClampStimulusSeries>	Group	Top level Group for <VoltageClampStimulusSeries> Neurodata Type: VoltageClampStimulusSeries Extends: PatchClampSeries
—electrode	Link	Link to IntracellularElectrode object that describes the electrode that was used to apply or record this data. Target Type IntracellularElectrode Name: electrode
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.9.6.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.9.7. IntracellularElectrode

Overview: An intracellular electrode and its metadata.

IntracellularElectrode extends NWBContainer and includes all elements of NWBContainer with the following additions or changes.

• Extends: NWBContainer

• Primitive Type: Group

• Inherits from: NWBContainer, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.7

Table 2.90 Datasets, Links, and Attributes contained in <IntracellularElectrode>

Id	Type	Description
<IntracellularElectrode>	Group	Top level Group for <IntracellularElectrode> Neurodata Type: IntracellularElectrode Extends: NWBContainer
—cell_id	Dataset	unique ID of the cell Quantity: 0 or 1 Data Type: text Name: cell_id
—description	Dataset	Description of electrode (e.g., whole-cell, sharp, etc.). Data Type: text Name: description
—filtering	Dataset	Electrode specific filtering. Quantity: 0 or 1 Data Type: text Name: filtering
—initial_access_resistance	Dataset	Initial access resistance. Quantity: 0 or 1 Data Type: text Name: initial_access_resistance
—location	Dataset	Location of the electrode. Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible. Quantity: 0 or 1 Data Type: text Name: location
—resistance	Dataset	Electrode resistance, in ohms. Quantity: 0 or 1 Data Type: text Name: resistance
—seal	Dataset	Information about seal used for recording. Quantity: 0 or 1 Data Type: text Name: seal
—slice	Dataset	Information about slice used for recording. Quantity: 0 or 1 Data Type: text Name: slice
—device	Link	Device that was used to record from this electrode. Target Type Device Name: device

Table 2.91 Groups contained in <IntracellularElectrode>

Id	Type	Description
<IntracellularElectrode>	Group	Top level Group for <IntracellularElectrode> Neurodata Type: IntracellularElectrode Extends: NWBContainer
—device	Link	Device that was used to record from this electrode. Target Type Device Name: device

2.9.8. SweepTable

Overview: [DEPRECATED] Table used to group different PatchClampSeries. SweepTable is being replaced by IntracellularRecordingsTable and SimultaneousRecordingsTable tables. Additional SequentialRecordingsTable, RepetitionsTable, and ExperimentalConditions tables provide enhanced support for experiment metadata.

SweepTable extends DynamicTable and includes all elements of DynamicTable with the following additions or changes.

• Extends: DynamicTable

• Primitive Type: Group

• Inherits from: DynamicTable, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.8

Table 2.92 Datasets, Links, and Attributes contained in <SweepTable>

Id	Type	Description
<SweepTable>	Group	Top level Group for <SweepTable> Neurodata Type: SweepTable Extends: DynamicTable
—colnames	Attribute	The names of the columns in this table. This should be used to specify an order to the columns. Data Type: text Dimensions: [‘num_columns’] Shape: [None] Name: colnames
—description	Attribute	Description of what is in this dynamic table. Data Type: text Name: description
—sweep_number	Dataset	Sweep number of the PatchClampSeries in that row. Extends: VectorData Data Type: uint32 Name: sweep_number
—series	Dataset	The PatchClampSeries with the sweep number in that row. Extends: VectorData Data Type: object reference to PatchClampSeries Name: series
—series_index	Dataset	Index for series. Extends: VectorIndex Name: series_index
—id	Dataset	Array of unique identifiers for the rows of this dynamic table. Extends: ElementIdentifiers Data Type: int Dimensions: [‘num_rows’] Shape: [None] Name: id
—<VectorData>	Dataset	Vector columns, including index columns, of this dynamic table. Extends: VectorData Quantity: 0 or more

2.9.9. IntracellularElectrodesTable

Overview: Table for storing intracellular electrode related metadata.

IntracellularElectrodesTable extends DynamicTable and includes all elements of DynamicTable with the following additions or changes.

• Extends: DynamicTable

• Primitive Type: Group

• Inherits from: DynamicTable, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.9

Table 2.93 Datasets, Links, and Attributes contained in <IntracellularElectrodesTable>

Id	Type	Description
<IntracellularElectrodesTable>	Group	Top level Group for <IntracellularElectrodesTable> Neurodata Type: IntracellularElectrodesTable Extends: DynamicTable
—description	Attribute	Description of what is in this dynamic table. Data Type: text Value: Table for storing intracellular electrode related metadata. Name: description
—colnames	Attribute	The names of the columns in this table. This should be used to specify an order to the columns. Data Type: text Dimensions: [‘num_columns’] Shape: [None] Name: colnames
—electrode	Dataset	Column for storing the reference to the intracellular electrode. Extends: VectorData Data Type: object reference to IntracellularElectrode Name: electrode
—id	Dataset	Array of unique identifiers for the rows of this dynamic table. Extends: ElementIdentifiers Data Type: int Dimensions: [‘num_rows’] Shape: [None] Name: id
—<VectorData>	Dataset	Vector columns, including index columns, of this dynamic table. Extends: VectorData Quantity: 0 or more

2.9.10. IntracellularStimuliTable

Overview: Table for storing intracellular stimulus related metadata.

IntracellularStimuliTable extends DynamicTable and includes all elements of DynamicTable with the following additions or changes.

• Extends: DynamicTable

• Primitive Type: Group

• Inherits from: DynamicTable, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.10

Table 2.94 Datasets, Links, and Attributes contained in <IntracellularStimuliTable>

Id	Type	Description
<IntracellularStimuliTable>	Group	Top level Group for <IntracellularStimuliTable> Neurodata Type: IntracellularStimuliTable Extends: DynamicTable
—description	Attribute	Description of what is in this dynamic table. Data Type: text Value: Table for storing intracellular stimulus related metadata. Name: description
—colnames	Attribute	The names of the columns in this table. This should be used to specify an order to the columns. Data Type: text Dimensions: [‘num_columns’] Shape: [None] Name: colnames
—stimulus	Dataset	Column storing the reference to the recorded stimulus for the recording (rows). Extends: TimeSeriesReferenceVectorData Name: stimulus
—id	Dataset	Array of unique identifiers for the rows of this dynamic table. Extends: ElementIdentifiers Data Type: int Dimensions: [‘num_rows’] Shape: [None] Name: id
—<VectorData>	Dataset	Vector columns, including index columns, of this dynamic table. Extends: VectorData Quantity: 0 or more

2.9.11. IntracellularResponsesTable

Overview: Table for storing intracellular response related metadata.

IntracellularResponsesTable extends DynamicTable and includes all elements of DynamicTable with the following additions or changes.

• Extends: DynamicTable

• Primitive Type: Group

• Inherits from: DynamicTable, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.11

Table 2.95 Datasets, Links, and Attributes contained in <IntracellularResponsesTable>

Id	Type	Description
<IntracellularResponsesTable>	Group	Top level Group for <IntracellularResponsesTable> Neurodata Type: IntracellularResponsesTable Extends: DynamicTable
—description	Attribute	Description of what is in this dynamic table. Data Type: text Value: Table for storing intracellular response related metadata. Name: description
—colnames	Attribute	The names of the columns in this table. This should be used to specify an order to the columns. Data Type: text Dimensions: [‘num_columns’] Shape: [None] Name: colnames
—response	Dataset	Column storing the reference to the recorded response for the recording (rows) Extends: TimeSeriesReferenceVectorData Name: response
—id	Dataset	Array of unique identifiers for the rows of this dynamic table. Extends: ElementIdentifiers Data Type: int Dimensions: [‘num_rows’] Shape: [None] Name: id
—<VectorData>	Dataset	Vector columns, including index columns, of this dynamic table. Extends: VectorData Quantity: 0 or more

2.9.12. IntracellularRecordingsTable

Overview: A table to group together a stimulus and response from a single electrode and a single simultaneous recording. Each row in the table represents a single recording consisting typically of a stimulus and a corresponding response. In some cases, however, only a stimulus or a response is recorded as part of an experiment. In this case, both the stimulus and response will point to the same TimeSeries while the idx_start and count of the invalid column will be set to -1, thus, indicating that no values have been recorded for the stimulus or response, respectively. Note, a recording MUST contain at least a stimulus or a response. Typically the stimulus and response are PatchClampSeries. However, the use of AD/DA channels that are not associated to an electrode is also common in intracellular electrophysiology, in which case other TimeSeries may be used.

IntracellularRecordingsTable extends AlignedDynamicTable and includes all elements of AlignedDynamicTable with the following additions or changes.

• Extends: AlignedDynamicTable

• Primitive Type: Group

• Name: intracellular_recordings

• Inherits from: AlignedDynamicTable, DynamicTable, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.12

Table 2.96 Datasets, Links, and Attributes contained in <IntracellularRecordingsTable>

Id	Type	Description
intracellular_recordings	Group	Top level Group for intracellular_recordings Neurodata Type: IntracellularRecordingsTable Extends: AlignedDynamicTable Name: intracellular_recordings
—description	Attribute	Description of the contents of this table. Inherited from AlignedDynamicTable and overwritten here to fix the value of the attribute. Data Type: text Value: A table to group together a stimulus and response from a single electrode and a single simultaneous recording and for storing metadata about the intracellular recording. Name: description
—categories	Attribute	The names of the categories in this AlignedDynamicTable. Each category is represented by one DynamicTable stored in the parent group. This attribute should be used to specify an order of categories and the category names must match the names of the corresponding DynamicTable in the group. Data Type: text Dimensions: [‘num_categories’] Shape: [None] Name: categories
—colnames	Attribute	The names of the columns in this table. This should be used to specify an order to the columns. Data Type: text Dimensions: [‘num_columns’] Shape: [None] Name: colnames
—id	Dataset	Array of unique identifiers for the rows of this dynamic table. Extends: ElementIdentifiers Data Type: int Dimensions: [‘num_rows’] Shape: [None] Name: id
—<VectorData>	Dataset	Vector columns, including index columns, of this dynamic table. Extends: VectorData Quantity: 0 or more

Table 2.97 Groups contained in <IntracellularRecordingsTable>

Id	Type	Description
intracellular_recordings	Group	Top level Group for intracellular_recordings Neurodata Type: IntracellularRecordingsTable Extends: AlignedDynamicTable Name: intracellular_recordings
—electrodes	Group	Table for storing intracellular electrode related metadata. Extends: IntracellularElectrodesTable Name: electrodes
—stimuli	Group	Table for storing intracellular stimulus related metadata. Extends: IntracellularStimuliTable Name: stimuli
—responses	Group	Table for storing intracellular response related metadata. Extends: IntracellularResponsesTable Name: responses
—<DynamicTable>	Group	A DynamicTable representing a particular category for columns in the AlignedDynamicTable parent container. The table MUST be aligned with (i.e., have the same number of rows) as all other DynamicTables stored in the AlignedDynamicTable parent container. The name of the category is given by the name of the DynamicTable and its description by the description attribute of the DynamicTable. Extends: DynamicTable Quantity: 0 or more

2.9.12.1. Groups: electrodes

Table for storing intracellular electrode related metadata.

• Extends: IntracellularElectrodesTable

• Name: electrodes

2.9.12.2. Groups: stimuli

Table for storing intracellular stimulus related metadata.

• Extends: IntracellularStimuliTable

• Name: stimuli

2.9.12.3. Groups: responses

Table for storing intracellular response related metadata.

• Extends: IntracellularResponsesTable

• Name: responses

2.9.12.4. Groups: <DynamicTable>

A DynamicTable representing a particular category for columns in the AlignedDynamicTable parent container. The table MUST be aligned with (i.e., have the same number of rows) as all other DynamicTables stored in the AlignedDynamicTable parent container. The name of the category is given by the name of the DynamicTable and its description by the description attribute of the DynamicTable.

• Extends: DynamicTable

• Quantity: 0 or more

2.9.13. SimultaneousRecordingsTable

Overview: A table for grouping different intracellular recordings from the IntracellularRecordingsTable table together that were recorded simultaneously from different electrodes.

SimultaneousRecordingsTable extends DynamicTable and includes all elements of DynamicTable with the following additions or changes.

• Extends: DynamicTable

• Primitive Type: Group

• Name: simultaneous_recordings

• Inherits from: DynamicTable, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.13

Table 2.98 Datasets, Links, and Attributes contained in <SimultaneousRecordingsTable>

Id	Type	Description
simultaneous_recordings	Group	Top level Group for simultaneous_recordings Neurodata Type: SimultaneousRecordingsTable Extends: DynamicTable Name: simultaneous_recordings
—colnames	Attribute	The names of the columns in this table. This should be used to specify an order to the columns. Data Type: text Dimensions: [‘num_columns’] Shape: [None] Name: colnames
—description	Attribute	Description of what is in this dynamic table. Data Type: text Name: description
—recordings	Dataset	A reference to one or more rows in the IntracellularRecordingsTable table. Extends: DynamicTableRegion Name: recordings
——table	Attribute	Reference to the IntracellularRecordingsTable table that this table region applies to. This specializes the attribute inherited from DynamicTableRegion to fix the type of table that can be referenced here. Data Type: object reference to IntracellularRecordingsTable Name: table
—recordings_index	Dataset	Index dataset for the recordings column. Extends: VectorIndex Name: recordings_index
—id	Dataset	Array of unique identifiers for the rows of this dynamic table. Extends: ElementIdentifiers Data Type: int Dimensions: [‘num_rows’] Shape: [None] Name: id
—<VectorData>	Dataset	Vector columns, including index columns, of this dynamic table. Extends: VectorData Quantity: 0 or more

2.9.14. SequentialRecordingsTable

Overview: A table for grouping different sequential recordings from the SimultaneousRecordingsTable table together. This is typically used to group together sequential recordings where a sequence of stimuli of the same type with varying parameters have been presented in a sequence.

SequentialRecordingsTable extends DynamicTable and includes all elements of DynamicTable with the following additions or changes.

• Extends: DynamicTable

• Primitive Type: Group

• Name: sequential_recordings

• Inherits from: DynamicTable, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.14

Table 2.99 Datasets, Links, and Attributes contained in <SequentialRecordingsTable>

Id	Type	Description
sequential_recordings	Group	Top level Group for sequential_recordings Neurodata Type: SequentialRecordingsTable Extends: DynamicTable Name: sequential_recordings
—colnames	Attribute	The names of the columns in this table. This should be used to specify an order to the columns. Data Type: text Dimensions: [‘num_columns’] Shape: [None] Name: colnames
—description	Attribute	Description of what is in this dynamic table. Data Type: text Name: description
—simultaneous_recordings	Dataset	A reference to one or more rows in the SimultaneousRecordingsTable table. Extends: DynamicTableRegion Name: simultaneous_recordings
——table	Attribute	Reference to the SimultaneousRecordingsTable table that this table region applies to. This specializes the attribute inherited from DynamicTableRegion to fix the type of table that can be referenced here. Data Type: object reference to SimultaneousRecordingsTable Name: table
—simultaneous_recordings_index	Dataset	Index dataset for the simultaneous_recordings column. Extends: VectorIndex Name: simultaneous_recordings_index
—stimulus_type	Dataset	The type of stimulus used for the sequential recording. Extends: VectorData Data Type: text Name: stimulus_type
—id	Dataset	Array of unique identifiers for the rows of this dynamic table. Extends: ElementIdentifiers Data Type: int Dimensions: [‘num_rows’] Shape: [None] Name: id
—<VectorData>	Dataset	Vector columns, including index columns, of this dynamic table. Extends: VectorData Quantity: 0 or more

2.9.15. RepetitionsTable

Overview: A table for grouping different sequential intracellular recordings together. With each SequentialRecording typically representing a particular type of stimulus, the RepetitionsTable table is typically used to group sets of stimuli applied in sequence.

RepetitionsTable extends DynamicTable and includes all elements of DynamicTable with the following additions or changes.

• Extends: DynamicTable

• Primitive Type: Group

• Name: repetitions

• Inherits from: DynamicTable, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.15

Table 2.100 Datasets, Links, and Attributes contained in <RepetitionsTable>

Id	Type	Description
repetitions	Group	Top level Group for repetitions Neurodata Type: RepetitionsTable Extends: DynamicTable Name: repetitions
—colnames	Attribute	The names of the columns in this table. This should be used to specify an order to the columns. Data Type: text Dimensions: [‘num_columns’] Shape: [None] Name: colnames
—description	Attribute	Description of what is in this dynamic table. Data Type: text Name: description
—sequential_recordings	Dataset	A reference to one or more rows in the SequentialRecordingsTable table. Extends: DynamicTableRegion Name: sequential_recordings
——table	Attribute	Reference to the SequentialRecordingsTable table that this table region applies to. This specializes the attribute inherited from DynamicTableRegion to fix the type of table that can be referenced here. Data Type: object reference to SequentialRecordingsTable Name: table
—sequential_recordings_index	Dataset	Index dataset for the sequential_recordings column. Extends: VectorIndex Name: sequential_recordings_index
—id	Dataset	Array of unique identifiers for the rows of this dynamic table. Extends: ElementIdentifiers Data Type: int Dimensions: [‘num_rows’] Shape: [None] Name: id
—<VectorData>	Dataset	Vector columns, including index columns, of this dynamic table. Extends: VectorData Quantity: 0 or more

2.9.16. ExperimentalConditionsTable

Overview: A table for grouping different intracellular recording repetitions together that belong to the same experimental condition.

ExperimentalConditionsTable extends DynamicTable and includes all elements of DynamicTable with the following additions or changes.

• Extends: DynamicTable

• Primitive Type: Group

• Name: experimental_conditions

• Inherits from: DynamicTable, Container

• Source filename: nwb.icephys.yaml

• Source Specification: see Section 3.10.16

Table 2.101 Datasets, Links, and Attributes contained in <ExperimentalConditionsTable>

Id	Type	Description
experimental_conditions	Group	Top level Group for experimental_conditions Neurodata Type: ExperimentalConditionsTable Extends: DynamicTable Name: experimental_conditions
—colnames	Attribute	The names of the columns in this table. This should be used to specify an order to the columns. Data Type: text Dimensions: [‘num_columns’] Shape: [None] Name: colnames
—description	Attribute	Description of what is in this dynamic table. Data Type: text Name: description
—repetitions	Dataset	A reference to one or more rows in the RepetitionsTable table. Extends: DynamicTableRegion Name: repetitions
——table	Attribute	Reference to the RepetitionsTable table that this table region applies to. This specializes the attribute inherited from DynamicTableRegion to fix the type of table that can be referenced here. Data Type: object reference to RepetitionsTable Name: table
—repetitions_index	Dataset	Index dataset for the repetitions column. Extends: VectorIndex Name: repetitions_index
—id	Dataset	Array of unique identifiers for the rows of this dynamic table. Extends: ElementIdentifiers Data Type: int Dimensions: [‘num_rows’] Shape: [None] Name: id
—<VectorData>	Dataset	Vector columns, including index columns, of this dynamic table. Extends: VectorData Quantity: 0 or more

2.10. Optogenetics

This source module contains neurodata_types for opto-genetics data.

2.10.1. OptogeneticSeries

Overview: An optogenetic stimulus.

OptogeneticSeries extends TimeSeries and includes all elements of TimeSeries with the following additions or changes.

• Extends: TimeSeries

• Primitive Type: Group

• Inherits from: TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ogen.yaml

• Source Specification: see Section 3.11.1

Table 2.102 Datasets, Links, and Attributes contained in <OptogeneticSeries>

Id	Type	Description
<OptogeneticSeries>	Group	Top level Group for <OptogeneticSeries> Neurodata Type: OptogeneticSeries Extends: TimeSeries
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Applied power for optogenetic stimulus, in watts. Data Type: numeric Dimensions: [‘num_times’] Shape: [None] Name: data
——unit	Attribute	Unit of measurement for data, which is fixed to ‘watts’. Data Type: text Value: watts Name: unit
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—site	Link	Link to OptogeneticStimulusSite object that describes the site to which this stimulus was applied. Target Type OptogeneticStimulusSite Name: site

Table 2.103 Groups contained in <OptogeneticSeries>

Id	Type	Description
<OptogeneticSeries>	Group	Top level Group for <OptogeneticSeries> Neurodata Type: OptogeneticSeries Extends: TimeSeries
—site	Link	Link to OptogeneticStimulusSite object that describes the site to which this stimulus was applied. Target Type OptogeneticStimulusSite Name: site
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.10.1.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.10.2. OptogeneticStimulusSite

Overview: A site of optogenetic stimulation.

OptogeneticStimulusSite extends NWBContainer and includes all elements of NWBContainer with the following additions or changes.

• Extends: NWBContainer

• Primitive Type: Group

• Inherits from: NWBContainer, Container

• Source filename: nwb.ogen.yaml

• Source Specification: see Section 3.11.2

Table 2.104 Datasets, Links, and Attributes contained in <OptogeneticStimulusSite>

Id	Type	Description
<OptogeneticStimulusSite>	Group	Top level Group for <OptogeneticStimulusSite> Neurodata Type: OptogeneticStimulusSite Extends: NWBContainer
—description	Dataset	Description of stimulation site. Data Type: text Name: description
—excitation_lambda	Dataset	Excitation wavelength, in nm. Data Type: float32 Name: excitation_lambda
—location	Dataset	Location of the stimulation site. Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible. Data Type: text Name: location
—device	Link	Device that generated the stimulus. Target Type Device Name: device

Table 2.105 Groups contained in <OptogeneticStimulusSite>

Id	Type	Description
<OptogeneticStimulusSite>	Group	Top level Group for <OptogeneticStimulusSite> Neurodata Type: OptogeneticStimulusSite Extends: NWBContainer
—device	Link	Device that generated the stimulus. Target Type Device Name: device

2.11. Optical physiology

This source module contains neurodata_types for optical physiology data.

2.11.1. OnePhotonSeries

Overview: Image stack recorded over time from 1-photon microscope.

OnePhotonSeries extends ImageSeries and includes all elements of ImageSeries with the following additions or changes.

• Extends: ImageSeries

• Primitive Type: Group

• Inherits from: ImageSeries, TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ophys.yaml

• Source Specification: see Section 3.12.1

Table 2.106 Datasets, Links, and Attributes contained in <OnePhotonSeries>

Id	Type	Description
<OnePhotonSeries>	Group	Top level Group for <OnePhotonSeries> Neurodata Type: OnePhotonSeries Extends: ImageSeries
—pmt_gain	Attribute	Photomultiplier gain. Data Type: float32 Required: False Name: pmt_gain
—scan_line_rate	Attribute	Lines imaged per second. This is also stored in /general/optophysiology but is kept here as it is useful information for analysis, and so good to be stored w/ the actual data. Data Type: float32 Required: False Name: scan_line_rate
—exposure_time	Attribute	Exposure time of the sample; often the inverse of the frequency. Data Type: float32 Required: False Name: exposure_time
—binning	Attribute	Amount of pixels combined into ‘bins’; could be 1, 2, 4, 8, etc. Data Type: uint8 Required: False Name: binning
—power	Attribute	Power of the excitation in mW, if known. Data Type: float32 Required: False Name: power
—intensity	Attribute	Intensity of the excitation in mW/mm^2, if known. Data Type: float32 Required: False Name: intensity
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Binary data representing images across frames. If data are stored in an external file, this should be an empty 3D array. Data Type: numeric Dimensions: [[‘frame’, ‘x’, ‘y’], [‘frame’, ‘x’, ‘y’, ‘z’]] Shape: [[None, None, None], [None, None, None, None]] Name: data
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——unit	Attribute	Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Name: unit
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—dimension	Dataset	Number of pixels on x, y, (and z) axes. Quantity: 0 or 1 Data Type: int32 Dimensions: [‘rank’] Shape: [None] Name: dimension
—external_file	Dataset	Paths to one or more external file(s). The field is only present if format=’external’. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_files’] Shape: [None] Name: external_file
——starting_frame	Attribute	Each external image may contain one or more consecutive frames of the full ImageSeries. This attribute serves as an index to indicate which frames each file contains, to faciliate random access. The ‘starting_frame’ attribute, hence, contains a list of frame numbers within the full ImageSeries of the first frame of each file listed in the parent ‘external_file’ dataset. Zero-based indexing is used (hence, the first element will always be zero). For example, if the ‘external_file’ dataset has three paths to files and the first file has 5 frames, the second file has 10 frames, and the third file has 20 frames, then this attribute will have values [0, 5, 15]. If there is a single external file that holds all of the frames of the ImageSeries (and so there is a single element in the ‘external_file’ dataset), then this attribute should have value [0]. Data Type: int32 Dimensions: [‘num_files’] Shape: [None] Name: starting_frame
—format	Dataset	Format of image. If this is ‘external’, then the attribute ‘external_file’ contains the path information to the image files. If this is ‘raw’, then the raw (single-channel) binary data is stored in the ‘data’ dataset. If this attribute is not present, then the default format=’raw’ case is assumed. Quantity: 0 or 1 Data Type: text Name: format
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—imaging_plane	Link	Link to ImagingPlane object from which this TimeSeries data was generated. Target Type ImagingPlane Name: imaging_plane
—device	Link	Link to the Device object that was used to capture these images. Target Type Device Name: device

Table 2.107 Groups contained in <OnePhotonSeries>

Id	Type	Description
<OnePhotonSeries>	Group	Top level Group for <OnePhotonSeries> Neurodata Type: OnePhotonSeries Extends: ImageSeries
—imaging_plane	Link	Link to ImagingPlane object from which this TimeSeries data was generated. Target Type ImagingPlane Name: imaging_plane
—device	Link	Link to the Device object that was used to capture these images. Target Type Device Name: device
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.11.1.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.11.2. TwoPhotonSeries

Overview: Image stack recorded over time from 2-photon microscope.

TwoPhotonSeries extends ImageSeries and includes all elements of ImageSeries with the following additions or changes.

• Extends: ImageSeries

• Primitive Type: Group

• Inherits from: ImageSeries, TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ophys.yaml

• Source Specification: see Section 3.12.2

Table 2.108 Datasets, Links, and Attributes contained in <TwoPhotonSeries>

Id	Type	Description
<TwoPhotonSeries>	Group	Top level Group for <TwoPhotonSeries> Neurodata Type: TwoPhotonSeries Extends: ImageSeries
—pmt_gain	Attribute	Photomultiplier gain. Data Type: float32 Required: False Name: pmt_gain
—scan_line_rate	Attribute	Lines imaged per second. This is also stored in /general/optophysiology but is kept here as it is useful information for analysis, and so good to be stored w/ the actual data. Data Type: float32 Required: False Name: scan_line_rate
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—field_of_view	Dataset	Width, height and depth of image, or imaged area, in meters. Quantity: 0 or 1 Data Type: float32 Dimensions: [[‘width|height’], [‘width|height|depth’]] Shape: [[2], [3]] Name: field_of_view
—data	Dataset	Binary data representing images across frames. If data are stored in an external file, this should be an empty 3D array. Data Type: numeric Dimensions: [[‘frame’, ‘x’, ‘y’], [‘frame’, ‘x’, ‘y’, ‘z’]] Shape: [[None, None, None], [None, None, None, None]] Name: data
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——unit	Attribute	Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Name: unit
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—dimension	Dataset	Number of pixels on x, y, (and z) axes. Quantity: 0 or 1 Data Type: int32 Dimensions: [‘rank’] Shape: [None] Name: dimension
—external_file	Dataset	Paths to one or more external file(s). The field is only present if format=’external’. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_files’] Shape: [None] Name: external_file
——starting_frame	Attribute	Each external image may contain one or more consecutive frames of the full ImageSeries. This attribute serves as an index to indicate which frames each file contains, to faciliate random access. The ‘starting_frame’ attribute, hence, contains a list of frame numbers within the full ImageSeries of the first frame of each file listed in the parent ‘external_file’ dataset. Zero-based indexing is used (hence, the first element will always be zero). For example, if the ‘external_file’ dataset has three paths to files and the first file has 5 frames, the second file has 10 frames, and the third file has 20 frames, then this attribute will have values [0, 5, 15]. If there is a single external file that holds all of the frames of the ImageSeries (and so there is a single element in the ‘external_file’ dataset), then this attribute should have value [0]. Data Type: int32 Dimensions: [‘num_files’] Shape: [None] Name: starting_frame
—format	Dataset	Format of image. If this is ‘external’, then the attribute ‘external_file’ contains the path information to the image files. If this is ‘raw’, then the raw (single-channel) binary data is stored in the ‘data’ dataset. If this attribute is not present, then the default format=’raw’ case is assumed. Quantity: 0 or 1 Data Type: text Name: format
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description
—imaging_plane	Link	Link to ImagingPlane object from which this TimeSeries data was generated. Target Type ImagingPlane Name: imaging_plane
—device	Link	Link to the Device object that was used to capture these images. Target Type Device Name: device

Table 2.109 Groups contained in <TwoPhotonSeries>

Id	Type	Description
<TwoPhotonSeries>	Group	Top level Group for <TwoPhotonSeries> Neurodata Type: TwoPhotonSeries Extends: ImageSeries
—imaging_plane	Link	Link to ImagingPlane object from which this TimeSeries data was generated. Target Type ImagingPlane Name: imaging_plane
—device	Link	Link to the Device object that was used to capture these images. Target Type Device Name: device
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.11.2.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.11.3. RoiResponseSeries

Overview: ROI responses over an imaging plane. The first dimension represents time. The second dimension, if present, represents ROIs.

RoiResponseSeries extends TimeSeries and includes all elements of TimeSeries with the following additions or changes.

• Extends: TimeSeries

• Primitive Type: Group

• Inherits from: TimeSeries, NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ophys.yaml

• Source Specification: see Section 3.12.3

Table 2.110 Datasets, Links, and Attributes contained in <RoiResponseSeries>

Id	Type	Description
<RoiResponseSeries>	Group	Top level Group for <RoiResponseSeries> Neurodata Type: RoiResponseSeries Extends: TimeSeries
—description	Attribute	Description of the time series. Data Type: text Required: False Default Value: no description Name: description
—comments	Attribute	Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string. Data Type: text Required: False Default Value: no comments Name: comments
—data	Dataset	Signals from ROIs. Data Type: numeric Dimensions: [[‘num_times’], [‘num_times’, ‘num_ROIs’]] Shape: [[None], [None, None]] Name: data
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the ‘conversion’ multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——offset	Attribute	Scalar to add to the data after scaling by ‘conversion’ to finalize its coercion to the specified ‘unit’. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units. Data Type: float32 Required: False Default Value: 0.0 Name: offset
——resolution	Attribute	Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0. Data Type: float32 Required: False Default Value: -1.0 Name: resolution
——unit	Attribute	Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply ‘data’ by ‘conversion’ and add ‘offset’. Data Type: text Name: unit
——continuity	Attribute	Optionally describe the continuity of the data. Can be “continuous”, “instantaneous”, or “step”. For example, a voltage trace would be “continuous”, because samples are recorded from a continuous process. An array of lick times would be “instantaneous”, because the data represents distinct moments in time. Times of image presentations would be “step” because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. Data Type: text Required: False Name: continuity
—rois	Dataset	DynamicTableRegion referencing into an ROITable containing information on the ROIs stored in this timeseries. Extends: DynamicTableRegion Name: rois
—starting_time	Dataset	Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute. Quantity: 0 or 1 Data Type: float64 Name: starting_time
——rate	Attribute	Sampling rate, in Hz. Data Type: float32 Name: rate
——unit	Attribute	Unit of measurement for time, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—timestamps	Dataset	Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Quantity: 0 or 1 Data Type: float64 Dimensions: [‘num_times’] Shape: [None] Name: timestamps
——interval	Attribute	Value is ‘1’ Data Type: int32 Value: 1 Name: interval
——unit	Attribute	Unit of measurement for timestamps, which is fixed to ‘seconds’. Data Type: text Value: seconds Name: unit
—control	Dataset	Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data. Quantity: 0 or 1 Data Type: uint8 Dimensions: [‘num_times’] Shape: [None] Name: control
—control_description	Dataset	Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0. Quantity: 0 or 1 Data Type: text Dimensions: [‘num_control_values’] Shape: [None] Name: control_description

Table 2.111 Groups contained in <RoiResponseSeries>

Id	Type	Description
<RoiResponseSeries>	Group	Top level Group for <RoiResponseSeries> Neurodata Type: RoiResponseSeries Extends: TimeSeries
—sync	Group	Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes. Quantity: 0 or 1 Name: sync

2.11.3.1. Groups: sync

Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of ‘sync’ are mostly for archival purposes.

• Quantity: 0 or 1

• Name: sync

2.11.4. DfOverF

Overview: dF/F information about a region of interest (ROI). Storage hierarchy of dF/F should be the same as for segmentation (i.e., same names for ROIs and for image planes).

DfOverF extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: DfOverF

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ophys.yaml

• Source Specification: see Section 3.12.4

Table 2.112 Groups contained in <DfOverF>

Id	Type	Description
<DfOverF>	Group	Top level Group for <DfOverF> Neurodata Type: DfOverF Extends: NWBDataInterface Default Name: DfOverF
—<RoiResponseSeries>	Group	RoiResponseSeries object(s) containing dF/F for a ROI. Extends: RoiResponseSeries Quantity: 1 or more

2.11.4.1. Groups: <RoiResponseSeries>

RoiResponseSeries object(s) containing dF/F for a ROI.

• Extends: RoiResponseSeries

• Quantity: 1 or more

2.11.5. Fluorescence

Overview: Fluorescence information about a region of interest (ROI). Storage hierarchy of fluorescence should be the same as for segmentation (ie, same names for ROIs and for image planes).

Fluorescence extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: Fluorescence

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ophys.yaml

• Source Specification: see Section 3.12.5

Table 2.113 Groups contained in <Fluorescence>

Id	Type	Description
<Fluorescence>	Group	Top level Group for <Fluorescence> Neurodata Type: Fluorescence Extends: NWBDataInterface Default Name: Fluorescence
—<RoiResponseSeries>	Group	RoiResponseSeries object(s) containing fluorescence data for a ROI. Extends: RoiResponseSeries Quantity: 1 or more

2.11.5.1. Groups: <RoiResponseSeries>

RoiResponseSeries object(s) containing fluorescence data for a ROI.

• Extends: RoiResponseSeries

• Quantity: 1 or more

2.11.6. ImageSegmentation

Overview: Stores pixels in an image that represent different regions of interest (ROIs) or masks. All segmentation for a given imaging plane is stored together, with storage for multiple imaging planes (masks) supported. Each ROI is stored in its own subgroup, with the ROI group containing both a 2D mask and a list of pixels that make up this mask. Segments can also be used for masking neuropil. If segmentation is allowed to change with time, a new imaging plane (or module) is required and ROI names should remain consistent between them.

ImageSegmentation extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: ImageSegmentation

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ophys.yaml

• Source Specification: see Section 3.12.6

Table 2.114 Groups contained in <ImageSegmentation>

Id	Type	Description
<ImageSegmentation>	Group	Top level Group for <ImageSegmentation> Neurodata Type: ImageSegmentation Extends: NWBDataInterface Default Name: ImageSegmentation
—<PlaneSegmentation>	Group	Results from image segmentation of a specific imaging plane. Extends: PlaneSegmentation Quantity: 1 or more

2.11.6.1. Groups: <PlaneSegmentation>

Results from image segmentation of a specific imaging plane.

• Extends: PlaneSegmentation

• Quantity: 1 or more

2.11.7. PlaneSegmentation

Overview: Results from image segmentation of a specific imaging plane.

PlaneSegmentation extends DynamicTable and includes all elements of DynamicTable with the following additions or changes.

• Extends: DynamicTable

• Primitive Type: Group

• Inherits from: DynamicTable, Container

• Source filename: nwb.ophys.yaml

• Source Specification: see Section 3.12.7

Table 2.115 Datasets, Links, and Attributes contained in <PlaneSegmentation>

Id	Type	Description
<PlaneSegmentation>	Group	Top level Group for <PlaneSegmentation> Neurodata Type: PlaneSegmentation Extends: DynamicTable
—colnames	Attribute	The names of the columns in this table. This should be used to specify an order to the columns. Data Type: text Dimensions: [‘num_columns’] Shape: [None] Name: colnames
—description	Attribute	Description of what is in this dynamic table. Data Type: text Name: description
—image_mask	Dataset	ROI masks for each ROI. Each image mask is the size of the original imaging plane (or volume) and members of the ROI are finite non-zero. Extends: VectorData Quantity: 0 or 1 Dimensions: [[‘num_roi’, ‘num_x’, ‘num_y’], [‘num_roi’, ‘num_x’, ‘num_y’, ‘num_z’]] Shape: [[None, None, None], [None, None, None, None]] Name: image_mask
—pixel_mask_index	Dataset	Index into pixel_mask. Extends: VectorIndex Quantity: 0 or 1 Name: pixel_mask_index
—pixel_mask	Dataset	Pixel masks for each ROI: a list of indices and weights for the ROI. Pixel masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation Extends: VectorData Quantity: 0 or 1 Data Type: Compound data type with the following elements: x: Pixel x-coordinate. (dtype= uint32 ) y: Pixel y-coordinate. (dtype= uint32 ) weight: Weight of the pixel. (dtype= float32 ) Name: pixel_mask
—voxel_mask_index	Dataset	Index into voxel_mask. Extends: VectorIndex Quantity: 0 or 1 Name: voxel_mask_index
—voxel_mask	Dataset	Voxel masks for each ROI: a list of indices and weights for the ROI. Voxel masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation Extends: VectorData Quantity: 0 or 1 Data Type: Compound data type with the following elements: x: Voxel x-coordinate. (dtype= uint32 ) y: Voxel y-coordinate. (dtype= uint32 ) z: Voxel z-coordinate. (dtype= uint32 ) weight: Weight of the voxel. (dtype= float32 ) Name: voxel_mask
—id	Dataset	Array of unique identifiers for the rows of this dynamic table. Extends: ElementIdentifiers Data Type: int Dimensions: [‘num_rows’] Shape: [None] Name: id
—<VectorData>	Dataset	Vector columns, including index columns, of this dynamic table. Extends: VectorData Quantity: 0 or more
—imaging_plane	Link	Link to ImagingPlane object from which this data was generated. Target Type ImagingPlane Name: imaging_plane

Table 2.116 Groups contained in <PlaneSegmentation>

Id	Type	Description
<PlaneSegmentation>	Group	Top level Group for <PlaneSegmentation> Neurodata Type: PlaneSegmentation Extends: DynamicTable
—imaging_plane	Link	Link to ImagingPlane object from which this data was generated. Target Type ImagingPlane Name: imaging_plane
—reference_images	Group	Image stacks that the segmentation masks apply to. Name: reference_images

2.11.7.1. Groups: reference_images

Image stacks that the segmentation masks apply to.

• Name: reference_images

Table 2.117 Groups contained in <reference_images>

Id	Type	Description
reference_images	Group	Top level Group for reference_images Name: reference_images
—<ImageSeries>	Group	One or more image stacks that the masks apply to (can be one-element stack). Extends: ImageSeries Quantity: 0 or more

2.11.7.2. Groups: reference_images/<ImageSeries>

One or more image stacks that the masks apply to (can be one-element stack).

• Extends: ImageSeries

• Quantity: 0 or more

2.11.8. ImagingPlane

Overview: An imaging plane and its metadata.

ImagingPlane extends NWBContainer and includes all elements of NWBContainer with the following additions or changes.

• Extends: NWBContainer

• Primitive Type: Group

• Inherits from: NWBContainer, Container

• Source filename: nwb.ophys.yaml

• Source Specification: see Section 3.12.8

Table 2.118 Datasets, Links, and Attributes contained in <ImagingPlane>

Id	Type	Description
<ImagingPlane>	Group	Top level Group for <ImagingPlane> Neurodata Type: ImagingPlane Extends: NWBContainer
—description	Dataset	Description of the imaging plane. Quantity: 0 or 1 Data Type: text Name: description
—excitation_lambda	Dataset	Excitation wavelength, in nm. Data Type: float32 Name: excitation_lambda
—imaging_rate	Dataset	Rate that images are acquired, in Hz. If the corresponding TimeSeries is present, the rate should be stored there instead. Quantity: 0 or 1 Data Type: float32 Name: imaging_rate
—indicator	Dataset	Calcium indicator. Data Type: text Name: indicator
—location	Dataset	Location of the imaging plane. Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible. Data Type: text Name: location
—manifold	Dataset	DEPRECATED Physical position of each pixel. ‘xyz’ represents the position of the pixel relative to the defined coordinate space. Deprecated in favor of origin_coords and grid_spacing. Quantity: 0 or 1 Data Type: float32 Dimensions: [[‘height’, ‘width’, ‘x, y, z’], [‘height’, ‘width’, ‘depth’, ‘x, y, z’]] Shape: [[None, None, 3], [None, None, None, 3]] Name: manifold
——conversion	Attribute	Scalar to multiply each element in data to convert it to the specified ‘unit’. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by ‘conversion’ to convert the data to the specified ‘unit’. e.g. if the data acquisition system stores values in this object as pixels from x = -500 to 499, y = -500 to 499 that correspond to a 2 m x 2 m range, then the ‘conversion’ multiplier to get from raw data acquisition pixel units to meters is 2/1000. Data Type: float32 Required: False Default Value: 1.0 Name: conversion
——unit	Attribute	Base unit of measurement for working with the data. The default value is ‘meters’. Data Type: text Required: False Default Value: meters Name: unit
—origin_coords	Dataset	Physical location of the first element of the imaging plane (0, 0) for 2-D data or (0, 0, 0) for 3-D data. See also reference_frame for what the physical location is relative to (e.g., bregma). Quantity: 0 or 1 Data Type: float32 Dimensions: [[‘x, y’], [‘x, y, z’]] Shape: [[2], [3]] Name: origin_coords
——unit	Attribute	Measurement units for origin_coords. The default value is ‘meters’. Data Type: text Required: False Default Value: meters Name: unit
—grid_spacing	Dataset	Space between pixels in (x, y) or voxels in (x, y, z) directions, in the specified unit. Assumes imaging plane is a regular grid. See also reference_frame to interpret the grid. Quantity: 0 or 1 Data Type: float32 Dimensions: [[‘x, y’], [‘x, y, z’]] Shape: [[2], [3]] Name: grid_spacing
——unit	Attribute	Measurement units for grid_spacing. The default value is ‘meters’. Data Type: text Required: False Default Value: meters Name: unit
—reference_frame	Dataset	Describes reference frame of origin_coords and grid_spacing. For example, this can be a text description of the anatomical location and orientation of the grid defined by origin_coords and grid_spacing or the vectors needed to transform or rotate the grid to a common anatomical axis (e.g., AP/DV/ML). This field is necessary to interpret origin_coords and grid_spacing. If origin_coords and grid_spacing are not present, then this field is not required. For example, if the microscope takes 10 x 10 x 2 images, where the first value of the data matrix (index (0, 0, 0)) corresponds to (-1.2, -0.6, -2) mm relative to bregma, the spacing between pixels is 0.2 mm in x, 0.2 mm in y and 0.5 mm in z, and larger numbers in x means more anterior, larger numbers in y means more rightward, and larger numbers in z means more ventral, then enter the following – origin_coords = (-1.2, -0.6, -2) grid_spacing = (0.2, 0.2, 0.5) reference_frame = “Origin coordinates are relative to bregma. First dimension corresponds to anterior-posterior axis (larger index = more anterior). Second dimension corresponds to medial-lateral axis (larger index = more rightward). Third dimension corresponds to dorsal-ventral axis (larger index = more ventral).” Quantity: 0 or 1 Data Type: text Name: reference_frame
—device	Link	Link to the Device object that was used to record from this electrode. Target Type Device Name: device

Table 2.119 Groups contained in <ImagingPlane>

Id	Type	Description
<ImagingPlane>	Group	Top level Group for <ImagingPlane> Neurodata Type: ImagingPlane Extends: NWBContainer
—device	Link	Link to the Device object that was used to record from this electrode. Target Type Device Name: device
—<OpticalChannel>	Group	An optical channel used to record from an imaging plane. Extends: OpticalChannel Quantity: 1 or more

2.11.8.1. Groups: <OpticalChannel>

An optical channel used to record from an imaging plane.

• Extends: OpticalChannel

• Quantity: 1 or more

2.11.9. OpticalChannel

Overview: An optical channel used to record from an imaging plane.

OpticalChannel extends NWBContainer and includes all elements of NWBContainer with the following additions or changes.

• Extends: NWBContainer

• Primitive Type: Group

• Inherits from: NWBContainer, Container

• Source filename: nwb.ophys.yaml

• Source Specification: see Section 3.12.9

Table 2.120 Datasets, Links, and Attributes contained in <OpticalChannel>

Id	Type	Description
<OpticalChannel>	Group	Top level Group for <OpticalChannel> Neurodata Type: OpticalChannel Extends: NWBContainer
—description	Dataset	Description or other notes about the channel. Data Type: text Name: description
—emission_lambda	Dataset	Emission wavelength for channel, in nm. Data Type: float32 Name: emission_lambda

2.11.10. MotionCorrection

Overview: An image stack where all frames are shifted (registered) to a common coordinate system, to account for movement and drift between frames. Note: each frame at each point in time is assumed to be 2-D (has only x & y dimensions).

MotionCorrection extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: MotionCorrection

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ophys.yaml

• Source Specification: see Section 3.12.10

Table 2.121 Groups contained in <MotionCorrection>

Id	Type	Description
<MotionCorrection>	Group	Top level Group for <MotionCorrection> Neurodata Type: MotionCorrection Extends: NWBDataInterface Default Name: MotionCorrection
—<CorrectedImageStack>	Group	Reuslts from motion correction of an image stack. Extends: CorrectedImageStack Quantity: 1 or more

2.11.10.1. Groups: <CorrectedImageStack>

Reuslts from motion correction of an image stack.

• Extends: CorrectedImageStack

• Quantity: 1 or more

2.11.11. CorrectedImageStack

Overview: Reuslts from motion correction of an image stack.

CorrectedImageStack extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.ophys.yaml

• Source Specification: see Section 3.12.11

Table 2.122 Datasets, Links, and Attributes contained in <CorrectedImageStack>

Id	Type	Description
<CorrectedImageStack>	Group	Top level Group for <CorrectedImageStack> Neurodata Type: CorrectedImageStack Extends: NWBDataInterface
—original	Link	Link to ImageSeries object that is being registered. Target Type ImageSeries Name: original

Table 2.123 Groups contained in <CorrectedImageStack>

Id	Type	Description
<CorrectedImageStack>	Group	Top level Group for <CorrectedImageStack> Neurodata Type: CorrectedImageStack Extends: NWBDataInterface
—original	Link	Link to ImageSeries object that is being registered. Target Type ImageSeries Name: original
—corrected	Group	Image stack with frames shifted to the common coordinates. Extends: ImageSeries Name: corrected
—xy_translation	Group	Stores the x,y delta necessary to align each frame to the common coordinates, for example, to align each frame to a reference image. Extends: TimeSeries Name: xy_translation

2.11.11.1. Groups: corrected

Image stack with frames shifted to the common coordinates.

• Extends: ImageSeries

• Name: corrected

2.11.11.2. Groups: xy_translation

Stores the x,y delta necessary to align each frame to the common coordinates, for example, to align each frame to a reference image.

• Extends: TimeSeries

• Name: xy_translation

2.12. Retinotopy

This source module contains neurodata_type for retinotopy data.

2.12.1. ImagingRetinotopy

Overview: Intrinsic signal optical imaging or widefield imaging for measuring retinotopy. Stores orthogonal maps (e.g., altitude/azimuth; radius/theta) of responses to specific stimuli and a combined polarity map from which to identify visual areas. This group does not store the raw responses imaged during retinotopic mapping or the stimuli presented, but rather the resulting phase and power maps after applying a Fourier transform on the averaged responses. Note: for data consistency, all images and arrays are stored in the format [row][column] and [row, col], which equates to [y][x]. Field of view and dimension arrays may appear backward (i.e., y before x).

ImagingRetinotopy extends NWBDataInterface and includes all elements of NWBDataInterface with the following additions or changes.

• Extends: NWBDataInterface

• Primitive Type: Group

• Default Name: ImagingRetinotopy

• Inherits from: NWBDataInterface, NWBContainer, Container

• Source filename: nwb.retinotopy.yaml

• Source Specification: see Section 3.13.1

Table 2.124 Datasets, Links, and Attributes contained in <ImagingRetinotopy>

Id	Type	Description
<ImagingRetinotopy>	Group	Top level Group for <ImagingRetinotopy> Neurodata Type: ImagingRetinotopy Extends: NWBDataInterface Default Name: ImagingRetinotopy
—axis_1_phase_map	Dataset	Phase response to stimulus on the first measured axis. Data Type: float32 Dimensions: [‘num_rows’, ‘num_cols’] Shape: [None, None] Name: axis_1_phase_map
——dimension	Attribute	Number of rows and columns in the image. Additional Information: row, column representation is equivalent to height, width. Data Type: int32 Dimensions: [‘num_rows, num_cols’] Shape: [2] Name: dimension
——field_of_view	Attribute	Size of viewing area, in meters. Data Type: float32 Dimensions: [‘height, width’] Shape: [2] Name: field_of_view
——unit	Attribute	Unit that axis data is stored in (e.g., degrees). Data Type: text Name: unit
—axis_1_power_map	Dataset	Power response on the first measured axis. Response is scaled so 0.0 is no power in the response and 1.0 is maximum relative power. Quantity: 0 or 1 Data Type: float32 Dimensions: [‘num_rows’, ‘num_cols’] Shape: [None, None] Name: axis_1_power_map
——dimension	Attribute	Number of rows and columns in the image. Additional Information: row, column representation is equivalent to height, width. Data Type: int32 Dimensions: [‘num_rows, num_cols’] Shape: [2] Name: dimension
——field_of_view	Attribute	Size of viewing area, in meters. Data Type: float32 Dimensions: [‘height, width’] Shape: [2] Name: field_of_view
——unit	Attribute	Unit that axis data is stored in (e.g., degrees). Data Type: text Name: unit
—axis_2_phase_map	Dataset	Phase response to stimulus on the second measured axis. Data Type: float32 Dimensions: [‘num_rows’, ‘num_cols’] Shape: [None, None] Name: axis_2_phase_map
——dimension	Attribute	Number of rows and columns in the image. Additional Information: row, column representation is equivalent to height, width. Data Type: int32 Dimensions: [‘num_rows, num_cols’] Shape: [2] Name: dimension
——field_of_view	Attribute	Size of viewing area, in meters. Data Type: float32 Dimensions: [‘height, width’] Shape: [2] Name: field_of_view
——unit	Attribute	Unit that axis data is stored in (e.g., degrees). Data Type: text Name: unit
—axis_2_power_map	Dataset	Power response on the second measured axis. Response is scaled so 0.0 is no power in the response and 1.0 is maximum relative power. Quantity: 0 or 1 Data Type: float32 Dimensions: [‘num_rows’, ‘num_cols’] Shape: [None, None] Name: axis_2_power_map
——dimension	Attribute	Number of rows and columns in the image. Additional Information: row, column representation is equivalent to height, width. Data Type: int32 Dimensions: [‘num_rows, num_cols’] Shape: [2] Name: dimension
——field_of_view	Attribute	Size of viewing area, in meters. Data Type: float32 Dimensions: [‘height, width’] Shape: [2] Name: field_of_view
——unit	Attribute	Unit that axis data is stored in (e.g., degrees). Data Type: text Name: unit
—axis_descriptions	Dataset	Two-element array describing the contents of the two response axis fields. Description should be something like [‘altitude’, ‘azimuth’] or ‘[‘radius’, ‘theta’]. Data Type: text Dimensions: [‘axis_1, axis_2’] Shape: [2] Name: axis_descriptions
—focal_depth_image	Dataset	Gray-scale image taken with same settings/parameters (e.g., focal depth, wavelength) as data collection. Array format: [rows][columns]. Quantity: 0 or 1 Data Type: uint16 Dimensions: [‘num_rows’, ‘num_cols’] Shape: [None, None] Name: focal_depth_image
——bits_per_pixel	Attribute	Number of bits used to represent each value. This is necessary to determine maximum (white) pixel value. Data Type: int32 Name: bits_per_pixel
——dimension	Attribute	Number of rows and columns in the image. Additional Information: row, column representation is equivalent to height, width. Data Type: int32 Dimensions: [‘num_rows, num_cols’] Shape: [2] Name: dimension
——field_of_view	Attribute	Size of viewing area, in meters. Data Type: float32 Dimensions: [‘height, width’] Shape: [2] Name: field_of_view
——focal_depth	Attribute	Focal depth offset, in meters. Data Type: float32 Name: focal_depth
——format	Attribute	Format of image. Right now only ‘raw’ is supported. Data Type: text Name: format
—sign_map	Dataset	Sine of the angle between the direction of the gradient in axis_1 and axis_2. Quantity: 0 or 1 Data Type: float32 Dimensions: [‘num_rows’, ‘num_cols’] Shape: [None, None] Name: sign_map
——dimension	Attribute	Number of rows and columns in the image. Additional Information: row, column representation is equivalent to height, width. Data Type: int32 Dimensions: [‘num_rows, num_cols’] Shape: [2] Name: dimension
——field_of_view	Attribute	Size of viewing area, in meters. Data Type: float32 Dimensions: [‘height, width’] Shape: [2] Name: field_of_view
—vasculature_image	Dataset	Gray-scale anatomical image of cortical surface. Array structure: [rows][columns] Data Type: uint16 Dimensions: [‘num_rows’, ‘num_cols’] Shape: [None, None] Name: vasculature_image
——bits_per_pixel	Attribute	Number of bits used to represent each value. This is necessary to determine maximum (white) pixel value Data Type: int32 Name: bits_per_pixel
——dimension	Attribute	Number of rows and columns in the image. Additional Information: row, column representation is equivalent to height, width. Data Type: int32 Dimensions: [‘num_rows, num_cols’] Shape: [2] Name: dimension
——field_of_view	Attribute	Size of viewing area, in meters. Data Type: float32 Dimensions: [‘height, width’] Shape: [2] Name: field_of_view
——format	Attribute	Format of image. Right now only ‘raw’ is supported. Data Type: text Name: format

3. Schema Sources

Source Specification: see Section 3.1

3.1. Namespace – NWB core

Description: see Section 1.1

YAML Specification:

author:
- Andrew Tritt
- Oliver Ruebel
- Ryan Ly
- Ben Dichter
- Keith Godfrey
- Jeff Teeters
contact:
- ajtritt@lbl.gov
- oruebel@lbl.gov
- rly@lbl.gov
- bdichter@lbl.gov
- keithg@alleninstitute.org
- jteeters@berkeley.edu
doc: NWB namespace
full_name: NWB core
name: core
schema:
- namespace: hdmf-common
- doc: This source module contains base data types used throughout the NWB data format.
  source: nwb.base.yaml
  title: Base data types
- doc: This source module contains neurodata_types for device data.
  source: nwb.device.yaml
  title: Devices
- doc: This source module contains neurodata_types for epoch data.
  source: nwb.epoch.yaml
  title: Epochs
- doc: This source module contains neurodata_types for image data.
  source: nwb.image.yaml
  title: Image data
- doc: Main NWB file specification.
  source: nwb.file.yaml
  title: NWB file
- doc: Miscellaneous types.
  source: nwb.misc.yaml
  title: Miscellaneous neurodata_types.
- doc: This source module contains neurodata_types for behavior data.
  source: nwb.behavior.yaml
  title: Behavior
- doc: This source module contains neurodata_types for extracellular electrophysiology
    data.
  source: nwb.ecephys.yaml
  title: Extracellular electrophysiology
- doc: This source module contains neurodata_types for intracellular electrophysiology
    data.
  source: nwb.icephys.yaml
  title: Intracellular electrophysiology
- doc: This source module contains neurodata_types for opto-genetics data.
  source: nwb.ogen.yaml
  title: Optogenetics
- doc: This source module contains neurodata_types for optical physiology data.
  source: nwb.ophys.yaml
  title: Optical physiology
- doc: This source module contains neurodata_type for retinotopy data.
  source: nwb.retinotopy.yaml
  title: Retinotopy
version: 2.6.0-alpha

3.2. Base data types

This source module contains base data types used throughout the NWB data format.

3.2.1. NWBData

Extends: Data

Description: see Section 2.1.1

YAML Specification:

doc: An abstract data type for a dataset.
neurodata_type_def: NWBData
neurodata_type_inc: Data

3.2.2. TimeSeriesReferenceVectorData

Extends: VectorData

Description: see Section 2.1.2

YAML Specification:

attributes:
- doc: Description of what these vectors represent.
  dtype: text
  name: description
default_name: timeseries
doc: Column storing references to a TimeSeries (rows). For each TimeSeries this VectorData
  column stores the start_index and count to indicate the range in time to be selected
  as well as an object reference to the TimeSeries.
dtype:
- doc: Start index into the TimeSeries 'data' and 'timestamp' datasets of the referenced
    TimeSeries. The first dimension of those arrays is always time.
  dtype: int32
  name: idx_start
- doc: Number of data samples available in this time series, during this epoch
  dtype: int32
  name: count
- doc: The TimeSeries that this index applies to
  dtype:
    reftype: object
    target_type: TimeSeries
  name: timeseries
neurodata_type_def: TimeSeriesReferenceVectorData
neurodata_type_inc: VectorData

3.2.3. Image

Extends: NWBData

Description: see Section 2.1.3

YAML Specification:

attributes:
- doc: Pixel resolution of the image, in pixels per centimeter.
  dtype: float32
  name: resolution
  required: false
- doc: Description of the image.
  dtype: text
  name: description
  required: false
dims:
- - x
  - y
- - x
  - y
  - r, g, b
- - x
  - y
  - r, g, b, a
doc: An abstract data type for an image. Shape can be 2-D (x, y), or 3-D where the
  third dimension can have three or four elements, e.g. (x, y, (r, g, b)) or (x, y,
  (r, g, b, a)).
dtype: numeric
neurodata_type_def: Image
neurodata_type_inc: NWBData
shape:
- -
  -
- -
  -
  - 3
- -
  -
  - 4

3.2.4. ImageReferences

Extends: NWBData

Description: see Section 2.1.4

YAML Specification:

dims:
- num_images
doc: Ordered dataset of references to Image objects.
dtype:
  reftype: object
  target_type: Image
neurodata_type_def: ImageReferences
neurodata_type_inc: NWBData
shape:
-

3.2.5. NWBContainer

Extends: Container

Description: see Section 2.1.5

YAML Specification:

doc: An abstract data type for a generic container storing collections of data and
  metadata. Base type for all data and metadata containers.
neurodata_type_def: NWBContainer
neurodata_type_inc: Container

3.2.6. NWBDataInterface

Extends: NWBContainer

Description: see Section 2.1.6

YAML Specification:

doc: An abstract data type for a generic container storing collections of data, as
  opposed to metadata.
neurodata_type_def: NWBDataInterface
neurodata_type_inc: NWBContainer

3.2.7. TimeSeries

Extends: NWBDataInterface

Description: see Section 2.1.7

YAML Specification:

attributes:
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Base unit of measurement for working with the data. Actual stored values
      are not necessarily stored in these units. To access the data in these units,
      multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - - num_times
  - - num_times
    - num_DIM2
  - - num_times
    - num_DIM2
    - num_DIM3
  - - num_times
    - num_DIM2
    - num_DIM3
    - num_DIM4
  doc: Data values. Data can be in 1-D, 2-D, 3-D, or 4-D. The first dimension should
    always represent time. This can also be used to store binary data (e.g., image
    frames). This can also be a link to data stored in an external file.
  name: data
  shape:
  - -
  - -
    -
  - -
    -
    -
  - -
    -
    -
    -
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: General purpose time series.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
neurodata_type_def: TimeSeries
neurodata_type_inc: NWBDataInterface

3.2.8. ProcessingModule

Extends: NWBContainer

Description: see Section 2.1.8

YAML Specification:

attributes:
- doc: Description of this collection of processed data.
  dtype: text
  name: description
doc: A collection of processed data.
groups:
- doc: Data objects stored in this collection.
  neurodata_type_inc: NWBDataInterface
  quantity: '*'
- doc: Tables stored in this collection.
  neurodata_type_inc: DynamicTable
  quantity: '*'
neurodata_type_def: ProcessingModule
neurodata_type_inc: NWBContainer

3.2.9. Images

Extends: NWBDataInterface

Description: see Section 2.1.9

YAML Specification:

attributes:
- doc: Description of this collection of images.
  dtype: text
  name: description
datasets:
- doc: Images stored in this collection.
  neurodata_type_inc: Image
  quantity: +
- doc: Ordered dataset of references to Image objects stored in the parent group.
    Each Image object in the Images group should be stored once and only once, so
    the dataset should have the same length as the number of images.
  name: order_of_images
  neurodata_type_inc: ImageReferences
  quantity: '?'
default_name: Images
doc: A collection of images with an optional way to specify the order of the images
  using the "order_of_images" dataset. An order must be specified if the images are
  referenced by index, e.g., from an IndexSeries.
neurodata_type_def: Images
neurodata_type_inc: NWBDataInterface

3.3. Devices

This source module contains neurodata_types for device data.

3.3.1. Device

Extends: NWBContainer

Description: see Section 2.2.1

YAML Specification:

attributes:
- doc: Description of the device (e.g., model, firmware version, processing software
    version, etc.) as free-form text.
  dtype: text
  name: description
  required: false
- doc: The name of the manufacturer of the device.
  dtype: text
  name: manufacturer
  required: false
doc: Metadata about a data acquisition device, e.g., recording system, electrode,
  microscope.
neurodata_type_def: Device
neurodata_type_inc: NWBContainer

3.4. Epochs

This source module contains neurodata_types for epoch data.

3.4.1. TimeIntervals

Extends: DynamicTable

Description: see Section 2.3.1

YAML Specification:

attributes:
- dims:
  - num_columns
  doc: The names of the columns in this table. This should be used to specify an order
    to the columns.
  dtype: text
  name: colnames
  shape:
  -
- doc: Description of what is in this dynamic table.
  dtype: text
  name: description
datasets:
- doc: Start time of epoch, in seconds.
  dtype: float32
  name: start_time
  neurodata_type_inc: VectorData
- doc: Stop time of epoch, in seconds.
  dtype: float32
  name: stop_time
  neurodata_type_inc: VectorData
- doc: User-defined tags that identify or categorize events.
  dtype: text
  name: tags
  neurodata_type_inc: VectorData
  quantity: '?'
- doc: Index for tags.
  name: tags_index
  neurodata_type_inc: VectorIndex
  quantity: '?'
- doc: An index into a TimeSeries object.
  name: timeseries
  neurodata_type_inc: TimeSeriesReferenceVectorData
  quantity: '?'
- doc: Index for timeseries.
  name: timeseries_index
  neurodata_type_inc: VectorIndex
  quantity: '?'
- dims:
  - num_rows
  doc: Array of unique identifiers for the rows of this dynamic table.
  dtype: int
  name: id
  neurodata_type_inc: ElementIdentifiers
  shape:
  -
- doc: Vector columns, including index columns, of this dynamic table.
  neurodata_type_inc: VectorData
  quantity: '*'
doc: A container for aggregating epoch data and the TimeSeries that each epoch applies
  to.
neurodata_type_def: TimeIntervals
neurodata_type_inc: DynamicTable

3.5. Image data

This source module contains neurodata_types for image data.

3.5.1. GrayscaleImage

Extends: Image

Description: see Section 2.4.1

YAML Specification:

attributes:
- doc: Pixel resolution of the image, in pixels per centimeter.
  dtype: float32
  name: resolution
  required: false
- doc: Description of the image.
  dtype: text
  name: description
  required: false
dims:
- x
- y
doc: A grayscale image.
dtype: numeric
neurodata_type_def: GrayscaleImage
neurodata_type_inc: Image
shape:
-
-

3.5.2. RGBImage

Extends: Image

Description: see Section 2.4.2

YAML Specification:

attributes:
- doc: Pixel resolution of the image, in pixels per centimeter.
  dtype: float32
  name: resolution
  required: false
- doc: Description of the image.
  dtype: text
  name: description
  required: false
dims:
- x
- y
- r, g, b
doc: A color image.
dtype: numeric
neurodata_type_def: RGBImage
neurodata_type_inc: Image
shape:
-
-
- 3

3.5.3. RGBAImage

Extends: Image

Description: see Section 2.4.3

YAML Specification:

attributes:
- doc: Pixel resolution of the image, in pixels per centimeter.
  dtype: float32
  name: resolution
  required: false
- doc: Description of the image.
  dtype: text
  name: description
  required: false
dims:
- x
- y
- r, g, b, a
doc: A color image with transparency.
dtype: numeric
neurodata_type_def: RGBAImage
neurodata_type_inc: Image
shape:
-
-
- 4

3.5.4. ImageSeries

Extends: TimeSeries

Description: see Section 2.4.4

YAML Specification:

attributes:
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Base unit of measurement for working with the data. Actual stored values
      are not necessarily stored in these units. To access the data in these units,
      multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - - frame
    - x
    - y
  - - frame
    - x
    - y
    - z
  doc: Binary data representing images across frames. If data are stored in an external
    file, this should be an empty 3D array.
  dtype: numeric
  name: data
  shape:
  - -
    -
    -
  - -
    -
    -
    -
- dims:
  - rank
  doc: Number of pixels on x, y, (and z) axes.
  dtype: int32
  name: dimension
  quantity: '?'
  shape:
  -
- attributes:
  - dims:
    - num_files
    doc: Each external image may contain one or more consecutive frames of the full
      ImageSeries. This attribute serves as an index to indicate which frames each
      file contains, to faciliate random access. The 'starting_frame' attribute, hence,
      contains a list of frame numbers within the full ImageSeries of the first frame
      of each file listed in the parent 'external_file' dataset. Zero-based indexing
      is used (hence, the first element will always be zero). For example, if the
      'external_file' dataset has three paths to files and the first file has 5 frames,
      the second file has 10 frames, and the third file has 20 frames, then this attribute
      will have values [0, 5, 15]. If there is a single external file that holds all
      of the frames of the ImageSeries (and so there is a single element in the 'external_file'
      dataset), then this attribute should have value [0].
    dtype: int32
    name: starting_frame
    shape:
    -
  dims:
  - num_files
  doc: Paths to one or more external file(s). The field is only present if format='external'.
    This is only relevant if the image series is stored in the file system as one
    or more image file(s). This field should NOT be used if the image is stored in
    another NWB file and that file is linked to this file.
  dtype: text
  name: external_file
  quantity: '?'
  shape:
  -
- default_value: raw
  doc: Format of image. If this is 'external', then the attribute 'external_file'
    contains the path information to the image files. If this is 'raw', then the raw
    (single-channel) binary data is stored in the 'data' dataset. If this attribute
    is not present, then the default format='raw' case is assumed.
  dtype: text
  name: format
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: General image data that is common between acquisition and stimulus time series.
  Sometimes the image data is stored in the file in a raw format while other times
  it will be stored as a series of external image files in the host file system. The
  data field will either be binary data, if the data is stored in the NWB file, or
  empty, if the data is stored in an external image stack. [frame][x][y] or [frame][x][y][z].
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to the Device object that was used to capture these images.
  name: device
  quantity: '?'
  target_type: Device
neurodata_type_def: ImageSeries
neurodata_type_inc: TimeSeries

3.5.5. ImageMaskSeries

Extends: ImageSeries

Description: see Section 2.4.5

YAML Specification:

attributes:
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Base unit of measurement for working with the data. Actual stored values
      are not necessarily stored in these units. To access the data in these units,
      multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - - frame
    - x
    - y
  - - frame
    - x
    - y
    - z
  doc: Binary data representing images across frames. If data are stored in an external
    file, this should be an empty 3D array.
  dtype: numeric
  name: data
  shape:
  - -
    -
    -
  - -
    -
    -
    -
- dims:
  - rank
  doc: Number of pixels on x, y, (and z) axes.
  dtype: int32
  name: dimension
  quantity: '?'
  shape:
  -
- attributes:
  - dims:
    - num_files
    doc: Each external image may contain one or more consecutive frames of the full
      ImageSeries. This attribute serves as an index to indicate which frames each
      file contains, to faciliate random access. The 'starting_frame' attribute, hence,
      contains a list of frame numbers within the full ImageSeries of the first frame
      of each file listed in the parent 'external_file' dataset. Zero-based indexing
      is used (hence, the first element will always be zero). For example, if the
      'external_file' dataset has three paths to files and the first file has 5 frames,
      the second file has 10 frames, and the third file has 20 frames, then this attribute
      will have values [0, 5, 15]. If there is a single external file that holds all
      of the frames of the ImageSeries (and so there is a single element in the 'external_file'
      dataset), then this attribute should have value [0].
    dtype: int32
    name: starting_frame
    shape:
    -
  dims:
  - num_files
  doc: Paths to one or more external file(s). The field is only present if format='external'.
    This is only relevant if the image series is stored in the file system as one
    or more image file(s). This field should NOT be used if the image is stored in
    another NWB file and that file is linked to this file.
  dtype: text
  name: external_file
  quantity: '?'
  shape:
  -
- default_value: raw
  doc: Format of image. If this is 'external', then the attribute 'external_file'
    contains the path information to the image files. If this is 'raw', then the raw
    (single-channel) binary data is stored in the 'data' dataset. If this attribute
    is not present, then the default format='raw' case is assumed.
  dtype: text
  name: format
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: An alpha mask that is applied to a presented visual stimulus. The 'data' array
  contains an array of mask values that are applied to the displayed image. Mask values
  are stored as RGBA. Mask can vary with time. The timestamps array indicates the
  starting time of a mask, and that mask pattern continues until it's explicitly changed.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to ImageSeries object that this image mask is applied to.
  name: masked_imageseries
  target_type: ImageSeries
- doc: Link to the Device object that was used to capture these images.
  name: device
  quantity: '?'
  target_type: Device
neurodata_type_def: ImageMaskSeries
neurodata_type_inc: ImageSeries

3.5.6. OpticalSeries

Extends: ImageSeries

Description: see Section 2.4.6

YAML Specification:

attributes:
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- doc: Distance from camera/monitor to target/eye.
  dtype: float32
  name: distance
  quantity: '?'
- dims:
  - - width, height
  - - width, height, depth
  doc: Width, height and depth of image, or imaged area, in meters.
  dtype: float32
  name: field_of_view
  quantity: '?'
  shape:
  - - 2
  - - 3
- attributes:
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Base unit of measurement for working with the data. Actual stored values
      are not necessarily stored in these units. To access the data in these units,
      multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - - frame
    - x
    - y
  - - frame
    - x
    - y
    - r, g, b
  doc: Images presented to subject, either grayscale or RGB
  dtype: numeric
  name: data
  shape:
  - -
    -
    -
  - -
    -
    -
    - 3
- doc: Description of image relative to some reference frame (e.g., which way is up).
    Must also specify frame of reference.
  dtype: text
  name: orientation
  quantity: '?'
- dims:
  - rank
  doc: Number of pixels on x, y, (and z) axes.
  dtype: int32
  name: dimension
  quantity: '?'
  shape:
  -
- attributes:
  - dims:
    - num_files
    doc: Each external image may contain one or more consecutive frames of the full
      ImageSeries. This attribute serves as an index to indicate which frames each
      file contains, to faciliate random access. The 'starting_frame' attribute, hence,
      contains a list of frame numbers within the full ImageSeries of the first frame
      of each file listed in the parent 'external_file' dataset. Zero-based indexing
      is used (hence, the first element will always be zero). For example, if the
      'external_file' dataset has three paths to files and the first file has 5 frames,
      the second file has 10 frames, and the third file has 20 frames, then this attribute
      will have values [0, 5, 15]. If there is a single external file that holds all
      of the frames of the ImageSeries (and so there is a single element in the 'external_file'
      dataset), then this attribute should have value [0].
    dtype: int32
    name: starting_frame
    shape:
    -
  dims:
  - num_files
  doc: Paths to one or more external file(s). The field is only present if format='external'.
    This is only relevant if the image series is stored in the file system as one
    or more image file(s). This field should NOT be used if the image is stored in
    another NWB file and that file is linked to this file.
  dtype: text
  name: external_file
  quantity: '?'
  shape:
  -
- default_value: raw
  doc: Format of image. If this is 'external', then the attribute 'external_file'
    contains the path information to the image files. If this is 'raw', then the raw
    (single-channel) binary data is stored in the 'data' dataset. If this attribute
    is not present, then the default format='raw' case is assumed.
  dtype: text
  name: format
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Image data that is presented or recorded. A stimulus template movie will be stored
  only as an image. When the image is presented as stimulus, additional data is required,
  such as field of view (e.g., how much of the visual field the image covers, or how
  what is the area of the target being imaged). If the OpticalSeries represents acquired
  imaging data, orientation is also important.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to the Device object that was used to capture these images.
  name: device
  quantity: '?'
  target_type: Device
neurodata_type_def: OpticalSeries
neurodata_type_inc: ImageSeries

3.5.7. IndexSeries

Extends: TimeSeries

Description: see Section 2.4.7

YAML Specification:

attributes:
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - doc: This field is unused by IndexSeries.
    dtype: float32
    name: conversion
    required: false
  - doc: This field is unused by IndexSeries.
    dtype: float32
    name: resolution
    required: false
  - doc: This field is unused by IndexSeries.
    dtype: float32
    name: offset
    required: false
  - doc: This field is unused by IndexSeries and has the value N/A.
    dtype: text
    name: unit
    value: N/A
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - num_times
  doc: Index of the image (using zero-indexing) in the linked Images object.
  dtype: uint32
  name: data
  shape:
  -
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Stores indices to image frames stored in an ImageSeries. The purpose of the IndexSeries
  is to allow a static image stack to be stored in an Images object, and the images
  in the stack to be referenced out-of-order. This can be for the display of individual
  images, or of movie segments (as a movie is simply a series of images). The data
  field stores the index of the frame in the referenced Images object, and the timestamps
  array indicates when that image was displayed.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to ImageSeries object containing images that are indexed. Use of this
    link is discouraged and will be deprecated. Link to an Images type instead.
  name: indexed_timeseries
  quantity: '?'
  target_type: ImageSeries
- doc: Link to Images object containing an ordered set of images that are indexed.
    The Images object must contain a 'ordered_images' dataset specifying the order
    of the images in the Images type.
  name: indexed_images
  quantity: '?'
  target_type: Images
neurodata_type_def: IndexSeries
neurodata_type_inc: TimeSeries

3.6. NWB file

Main NWB file specification.

3.6.1. ScratchData

Extends: NWBData

Description: see Section 2.5.1

YAML Specification:

attributes:
- doc: Any notes the user has about the dataset being stored
  dtype: text
  name: notes
doc: Any one-off datasets
neurodata_type_def: ScratchData
neurodata_type_inc: NWBData

3.6.2. NWBFile

Extends: NWBContainer

Description: see Section 2.5.2

YAML Specification:

attributes:
- doc: File version string. Use semantic versioning, e.g. 1.2.1. This will be the
    name of the format with trailing major, minor and patch numbers.
  dtype: text
  name: nwb_version
  value: 2.6.0
datasets:
- dims:
  - num_modifications
  doc: 'A record of the date the file was created and of subsequent modifications.
    The date is stored in UTC with local timezone offset as ISO 8601 extended formatted
    strings: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in "Z" with no
    timezone offset. Date accuracy is up to milliseconds. The file can be created
    after the experiment was run, so this may differ from the experiment start time.
    Each modification to the nwb file adds a new entry to the array.'
  dtype: isodatetime
  name: file_create_date
  shape:
  -
- doc: A unique text identifier for the file. For example, concatenated lab name,
    file creation date/time and experimentalist, or a hash of these and/or other values.
    The goal is that the string should be unique to all other files.
  dtype: text
  name: identifier
- doc: A description of the experimental session and data in the file.
  dtype: text
  name: session_description
- doc: 'Date and time of the experiment/session start. The date is stored in UTC with
    local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00.
    Dates stored in UTC end in "Z" with no timezone offset. Date accuracy is up to
    milliseconds.'
  dtype: isodatetime
  name: session_start_time
- doc: 'Date and time corresponding to time zero of all timestamps. The date is stored
    in UTC with local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00.
    Dates stored in UTC end in "Z" with no timezone offset. Date accuracy is up to
    milliseconds. All times stored in the file use this time as reference (i.e., time
    zero).'
  dtype: isodatetime
  name: timestamps_reference_time
doc: An NWB file storing cellular-based neurophysiology data from a single experimental
  session.
groups:
- doc: Data streams recorded from the system, including ephys, ophys, tracking, etc.
    This group should be read-only after the experiment is completed and timestamps
    are corrected to a common timebase. The data stored here may be links to raw data
    stored in external NWB files. This will allow keeping bulky raw data out of the
    file while preserving the option of keeping some/all in the file. Acquired data
    includes tracking and experimental data streams (i.e., everything measured from
    the system). If bulky data is stored in the /acquisition group, the data can exist
    in a separate NWB file that is linked to by the file being used for processing
    and analysis.
  groups:
  - doc: Acquired, raw data.
    neurodata_type_inc: NWBDataInterface
    quantity: '*'
  - doc: Tabular data that is relevent to acquisition
    neurodata_type_inc: DynamicTable
    quantity: '*'
  name: acquisition
- doc: Lab-specific and custom scientific analysis of data. There is no defined format
    for the content of this group - the format is up to the individual user/lab. To
    facilitate sharing analysis data between labs, the contents here should be stored
    in standard types (e.g., neurodata_types) and appropriately documented. The file
    can store lab-specific and custom data analysis without restriction on its form
    or schema, reducing data formatting restrictions on end users. Such data should
    be placed in the analysis group. The analysis data should be documented so that
    it could be shared with other labs.
  groups:
  - doc: Custom analysis results.
    neurodata_type_inc: NWBContainer
    quantity: '*'
  - doc: Tabular data that is relevent to data stored in analysis
    neurodata_type_inc: DynamicTable
    quantity: '*'
  name: analysis
- datasets:
  - doc: Any one-off datasets
    neurodata_type_inc: ScratchData
    quantity: '*'
  doc: A place to store one-off analysis results. Data placed here is not intended
    for sharing. By placing data here, users acknowledge that there is no guarantee
    that their data meets any standard.
  groups:
  - doc: Any one-off containers
    neurodata_type_inc: NWBContainer
    quantity: '*'
  - doc: Any one-off tables
    neurodata_type_inc: DynamicTable
    quantity: '*'
  name: scratch
  quantity: '?'
- doc: The home for ProcessingModules. These modules perform intermediate analysis
    of data that is necessary to perform before scientific analysis. Examples include
    spike clustering, extracting position from tracking data, stitching together image
    slices. ProcessingModules can be large and express many data sets from relatively
    complex analysis (e.g., spike detection and clustering) or small, representing
    extraction of position information from tracking video, or even binary lick/no-lick
    decisions. Common software tools (e.g., klustakwik, MClust) are expected to read/write
    data here.  'Processing' refers to intermediate analysis of the acquired data
    to make it more amenable to scientific analysis.
  groups:
  - doc: Intermediate analysis of acquired data.
    neurodata_type_inc: ProcessingModule
    quantity: '*'
  name: processing
- doc: Data pushed into the system (eg, video stimulus, sound, voltage, etc) and secondary
    representations of that data (eg, measurements of something used as a stimulus).
    This group should be made read-only after experiment complete and timestamps are
    corrected to common timebase. Stores both presented stimuli and stimulus templates,
    the latter in case the same stimulus is presented multiple times, or is pulled
    from an external stimulus library. Stimuli are here defined as any signal that
    is pushed into the system as part of the experiment (eg, sound, video, voltage,
    etc). Many different experiments can use the same stimuli, and stimuli can be
    re-used during an experiment. The stimulus group is organized so that one version
    of template stimuli can be stored and these be used multiple times. These templates
    can exist in the present file or can be linked to a remote library file.
  groups:
  - doc: Stimuli presented during the experiment.
    groups:
    - doc: TimeSeries objects containing data of presented stimuli.
      neurodata_type_inc: TimeSeries
      quantity: '*'
    name: presentation
  - doc: Template stimuli. Timestamps in templates are based on stimulus design and
      are relative to the beginning of the stimulus. When templates are used, the
      stimulus instances must convert presentation times to the experiment`s time
      reference frame.
    groups:
    - doc: TimeSeries objects containing template data of presented stimuli.
      neurodata_type_inc: TimeSeries
      quantity: '*'
    - doc: Images objects containing images of presented stimuli.
      neurodata_type_inc: Images
      quantity: '*'
    name: templates
  name: stimulus
- datasets:
  - doc: Notes about data collection and analysis.
    dtype: text
    name: data_collection
    quantity: '?'
  - doc: General description of the experiment.
    dtype: text
    name: experiment_description
    quantity: '?'
  - dims:
    - num_experimenters
    doc: Name of person(s) who performed the experiment. Can also specify roles of
      different people involved.
    dtype: text
    name: experimenter
    quantity: '?'
    shape:
    -
  - doc: Institution(s) where experiment was performed.
    dtype: text
    name: institution
    quantity: '?'
  - dims:
    - num_keywords
    doc: Terms to search over.
    dtype: text
    name: keywords
    quantity: '?'
    shape:
    -
  - doc: Laboratory where experiment was performed.
    dtype: text
    name: lab
    quantity: '?'
  - doc: Notes about the experiment.
    dtype: text
    name: notes
    quantity: '?'
  - doc: Description of drugs used, including how and when they were administered.
      Anesthesia(s), painkiller(s), etc., plus dosage, concentration, etc.
    dtype: text
    name: pharmacology
    quantity: '?'
  - doc: Experimental protocol, if applicable. e.g., include IACUC protocol number.
    dtype: text
    name: protocol
    quantity: '?'
  - dims:
    - num_publications
    doc: Publication information. PMID, DOI, URL, etc.
    dtype: text
    name: related_publications
    quantity: '?'
    shape:
    -
  - doc: Lab-specific ID for the session.
    dtype: text
    name: session_id
    quantity: '?'
  - doc: Description of slices, including information about preparation thickness,
      orientation, temperature, and bath solution.
    dtype: text
    name: slices
    quantity: '?'
  - attributes:
    - doc: Name of script file.
      dtype: text
      name: file_name
    doc: Script file or link to public source code used to create this NWB file.
    dtype: text
    name: source_script
    quantity: '?'
  - doc: Notes about stimuli, such as how and where they were presented.
    dtype: text
    name: stimulus
    quantity: '?'
  - doc: Narrative description about surgery/surgeries, including date(s) and who
      performed surgery.
    dtype: text
    name: surgery
    quantity: '?'
  - doc: Information about virus(es) used in experiments, including virus ID, source,
      date made, injection location, volume, etc.
    dtype: text
    name: virus
    quantity: '?'
  doc: Experimental metadata, including protocol, notes and description of hardware
    device(s).  The metadata stored in this section should be used to describe the
    experiment. Metadata necessary for interpreting the data is stored with the data.
    General experimental metadata, including animal strain, experimental protocols,
    experimenter, devices, etc, are stored under 'general'. Core metadata (e.g., that
    required to interpret data fields) is stored with the data itself, and implicitly
    defined by the file specification (e.g., time is in seconds). The strategy used
    here for storing non-core metadata is to use free-form text fields, such as would
    appear in sentences or paragraphs from a Methods section. Metadata fields are
    text to enable them to be more general, for example to represent ranges instead
    of numerical values. Machine-readable metadata is stored as attributes to these
    free-form datasets. All entries in the below table are to be included when data
    is present. Unused groups (e.g., intracellular_ephys in an optophysiology experiment)
    should not be created unless there is data to store within them.
  groups:
  - doc: Place-holder than can be extended so that lab-specific meta-data can be placed
      in /general.
    neurodata_type_inc: LabMetaData
    quantity: '*'
  - doc: Description of hardware devices used during experiment, e.g., monitors, ADC
      boards, microscopes, etc.
    groups:
    - doc: Data acquisition devices.
      neurodata_type_inc: Device
      quantity: '*'
    name: devices
    quantity: '?'
  - doc: Information about the animal or person from which the data was measured.
    name: subject
    neurodata_type_inc: Subject
    quantity: '?'
  - doc: Metadata related to extracellular electrophysiology.
    groups:
    - doc: Physical group of electrodes.
      neurodata_type_inc: ElectrodeGroup
      quantity: '*'
    - datasets:
      - doc: x coordinate of the channel location in the brain (+x is posterior).
        dtype: float32
        name: x
        neurodata_type_inc: VectorData
        quantity: '?'
      - doc: y coordinate of the channel location in the brain (+y is inferior).
        dtype: float32
        name: y
        neurodata_type_inc: VectorData
        quantity: '?'
      - doc: z coordinate of the channel location in the brain (+z is right).
        dtype: float32
        name: z
        neurodata_type_inc: VectorData
        quantity: '?'
      - doc: Impedance of the channel, in ohms.
        dtype: float32
        name: imp
        neurodata_type_inc: VectorData
        quantity: '?'
      - doc: Location of the electrode (channel). Specify the area, layer, comments
          on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use
          standard atlas names for anatomical regions when possible.
        dtype: text
        name: location
        neurodata_type_inc: VectorData
      - doc: Description of hardware filtering, including the filter name and frequency
          cutoffs.
        dtype: text
        name: filtering
        neurodata_type_inc: VectorData
        quantity: '?'
      - doc: Reference to the ElectrodeGroup this electrode is a part of.
        dtype:
          reftype: object
          target_type: ElectrodeGroup
        name: group
        neurodata_type_inc: VectorData
      - doc: Name of the ElectrodeGroup this electrode is a part of.
        dtype: text
        name: group_name
        neurodata_type_inc: VectorData
      - doc: x coordinate in electrode group
        dtype: float32
        name: rel_x
        neurodata_type_inc: VectorData
        quantity: '?'
      - doc: y coordinate in electrode group
        dtype: float32
        name: rel_y
        neurodata_type_inc: VectorData
        quantity: '?'
      - doc: z coordinate in electrode group
        dtype: float32
        name: rel_z
        neurodata_type_inc: VectorData
        quantity: '?'
      - doc: Description of the reference electrode and/or reference scheme used for
          this electrode, e.g., "stainless steel skull screw" or "online common average
          referencing".
        dtype: text
        name: reference
        neurodata_type_inc: VectorData
        quantity: '?'
      doc: A table of all electrodes (i.e. channels) used for recording.
      name: electrodes
      neurodata_type_inc: DynamicTable
      quantity: '?'
    name: extracellular_ephys
    quantity: '?'
  - datasets:
    - doc: '[DEPRECATED] Use IntracellularElectrode.filtering instead. Description
        of filtering used. Includes filtering type and parameters, frequency fall-off,
        etc. If this changes between TimeSeries, filter description should be stored
        as a text attribute for each TimeSeries.'
      dtype: text
      name: filtering
      quantity: '?'
    doc: Metadata related to intracellular electrophysiology.
    groups:
    - doc: An intracellular electrode.
      neurodata_type_inc: IntracellularElectrode
      quantity: '*'
    - doc: '[DEPRECATED] Table used to group different PatchClampSeries. SweepTable
        is being replaced by IntracellularRecordingsTable and SimultaneousRecordingsTable
        tabels. Additional SequentialRecordingsTable, RepetitionsTable and ExperimentalConditions
        tables provide enhanced support for experiment metadata.'
      name: sweep_table
      neurodata_type_inc: SweepTable
      quantity: '?'
    - doc: A table to group together a stimulus and response from a single electrode
        and a single simultaneous recording. Each row in the table represents a single
        recording consisting typically of a stimulus and a corresponding response.
        In some cases, however, only a stimulus or a response are recorded as as part
        of an experiment. In this case both, the stimulus and response will point
        to the same TimeSeries while the idx_start and count of the invalid column
        will be set to -1, thus, indicating that no values have been recorded for
        the stimulus or response, respectively. Note, a recording MUST contain at
        least a stimulus or a response. Typically the stimulus and response are PatchClampSeries.
        However, the use of AD/DA channels that are not associated to an electrode
        is also common in intracellular electrophysiology, in which case other TimeSeries
        may be used.
      name: intracellular_recordings
      neurodata_type_inc: IntracellularRecordingsTable
      quantity: '?'
    - doc: A table for grouping different intracellular recordings from the IntracellularRecordingsTable
        table together that were recorded simultaneously from different electrodes
      name: simultaneous_recordings
      neurodata_type_inc: SimultaneousRecordingsTable
      quantity: '?'
    - doc: A table for grouping different sequential recordings from the SimultaneousRecordingsTable
        table together. This is typically used to group together sequential recordings
        where the a sequence of stimuli of the same type with varying parameters have
        been presented in a sequence.
      name: sequential_recordings
      neurodata_type_inc: SequentialRecordingsTable
      quantity: '?'
    - doc: A table for grouping different sequential intracellular recordings together.
        With each SequentialRecording typically representing a particular type of
        stimulus, the RepetitionsTable table is typically used to group sets of stimuli
        applied in sequence.
      name: repetitions
      neurodata_type_inc: RepetitionsTable
      quantity: '?'
    - doc: A table for grouping different intracellular recording repetitions together
        that belong to the same experimental experimental_conditions.
      name: experimental_conditions
      neurodata_type_inc: ExperimentalConditionsTable
      quantity: '?'
    name: intracellular_ephys
    quantity: '?'
  - doc: Metadata describing optogenetic stimuluation.
    groups:
    - doc: An optogenetic stimulation site.
      neurodata_type_inc: OptogeneticStimulusSite
      quantity: '*'
    name: optogenetics
    quantity: '?'
  - doc: Metadata related to optophysiology.
    groups:
    - doc: An imaging plane.
      neurodata_type_inc: ImagingPlane
      quantity: '*'
    name: optophysiology
    quantity: '?'
  name: general
- doc: Experimental intervals, whether that be logically distinct sub-experiments
    having a particular scientific goal, trials (see trials subgroup) during an experiment,
    or epochs (see epochs subgroup) deriving from analysis of data.
  groups:
  - doc: Divisions in time marking experimental stages or sub-divisions of a single
      recording session.
    name: epochs
    neurodata_type_inc: TimeIntervals
    quantity: '?'
  - doc: Repeated experimental events that have a logical grouping.
    name: trials
    neurodata_type_inc: TimeIntervals
    quantity: '?'
  - doc: Time intervals that should be removed from analysis.
    name: invalid_times
    neurodata_type_inc: TimeIntervals
    quantity: '?'
  - doc: Optional additional table(s) for describing other experimental time intervals.
    neurodata_type_inc: TimeIntervals
    quantity: '*'
  name: intervals
  quantity: '?'
- doc: Data about sorted spike units.
  name: units
  neurodata_type_inc: Units
  quantity: '?'
name: root
neurodata_type_def: NWBFile
neurodata_type_inc: NWBContainer

3.6.3. LabMetaData

Extends: NWBContainer

Description: see Section 2.5.3

YAML Specification:

doc: Lab-specific meta-data.
neurodata_type_def: LabMetaData
neurodata_type_inc: NWBContainer

3.6.4. Subject

Extends: NWBContainer

Description: see Section 2.5.4

YAML Specification:

datasets:
- attributes:
  - default_value: birth
    doc: Age is with reference to this event. Can be 'birth' or 'gestational'. If
      reference is omitted, 'birth' is implied.
    dtype: text
    name: reference
    required: false
  doc: Age of subject. Can be supplied instead of 'date_of_birth'.
  dtype: text
  name: age
  quantity: '?'
- doc: Date of birth of subject. Can be supplied instead of 'age'.
  dtype: isodatetime
  name: date_of_birth
  quantity: '?'
- doc: Description of subject and where subject came from (e.g., breeder, if animal).
  dtype: text
  name: description
  quantity: '?'
- doc: Genetic strain. If absent, assume Wild Type (WT).
  dtype: text
  name: genotype
  quantity: '?'
- doc: Gender of subject.
  dtype: text
  name: sex
  quantity: '?'
- doc: Species of subject.
  dtype: text
  name: species
  quantity: '?'
- doc: Strain of subject.
  dtype: text
  name: strain
  quantity: '?'
- doc: ID of animal/person used/participating in experiment (lab convention).
  dtype: text
  name: subject_id
  quantity: '?'
- doc: Weight at time of experiment, at time of surgery and at other important times.
  dtype: text
  name: weight
  quantity: '?'
doc: Information about the animal or person from which the data was measured.
neurodata_type_def: Subject
neurodata_type_inc: NWBContainer

3.7. Miscellaneous neurodata_types.

Miscellaneous types.

3.7.1. AbstractFeatureSeries

Extends: TimeSeries

Description: see Section 2.6.1

YAML Specification:

attributes:
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - default_value: see 'feature_units'
    doc: Since there can be different units for different features, store the units
      in 'feature_units'. The default value for this attribute is "see 'feature_units'".
    dtype: text
    name: unit
    required: false
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - - num_times
  - - num_times
    - num_features
  doc: Values of each feature at each time.
  dtype: numeric
  name: data
  shape:
  - -
  - -
    -
- dims:
  - num_features
  doc: Units of each feature.
  dtype: text
  name: feature_units
  quantity: '?'
  shape:
  -
- dims:
  - num_features
  doc: Description of the features represented in TimeSeries::data.
  dtype: text
  name: features
  shape:
  -
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Abstract features, such as quantitative descriptions of sensory stimuli. The
  TimeSeries::data field is a 2D array, storing those features (e.g., for visual grating
  stimulus this might be orientation, spatial frequency and contrast). Null stimuli
  (eg, uniform gray) can be marked as being an independent feature (eg, 1.0 for gray,
  0.0 for actual stimulus) or by storing NaNs for feature values, or through use of
  the TimeSeries::control fields. A set of features is considered to persist until
  the next set of features is defined. The final set of features stored should be
  the null set. This is useful when storing the raw stimulus is impractical.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
neurodata_type_def: AbstractFeatureSeries
neurodata_type_inc: TimeSeries

3.7.2. AnnotationSeries

Extends: TimeSeries

Description: see Section 2.6.2

YAML Specification:

attributes:
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - doc: Smallest meaningful difference between values in data. Annotations have no
      units, so the value is fixed to -1.0.
    dtype: float32
    name: resolution
    value: -1.0
  - doc: Base unit of measurement for working with the data. Annotations have no units,
      so the value is fixed to 'n/a'.
    dtype: text
    name: unit
    value: n/a
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - num_times
  doc: Annotations made during an experiment.
  dtype: text
  name: data
  shape:
  -
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Stores user annotations made during an experiment. The data[] field stores a
  text array, and timestamps are stored for each annotation (ie, interval=1). This
  is largely an alias to a standard TimeSeries storing a text array but that is identifiable
  as storing annotations in a machine-readable way.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
neurodata_type_def: AnnotationSeries
neurodata_type_inc: TimeSeries

3.7.3. IntervalSeries

Extends: TimeSeries

Description: see Section 2.6.3

YAML Specification:

attributes:
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - doc: Smallest meaningful difference between values in data. Annotations have no
      units, so the value is fixed to -1.0.
    dtype: float32
    name: resolution
    value: -1.0
  - doc: Base unit of measurement for working with the data. Annotations have no units,
      so the value is fixed to 'n/a'.
    dtype: text
    name: unit
    value: n/a
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - num_times
  doc: Use values >0 if interval started, <0 if interval ended.
  dtype: int8
  name: data
  shape:
  -
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Stores intervals of data. The timestamps field stores the beginning and end of
  intervals. The data field stores whether the interval just started (>0 value) or
  ended (<0 value). Different interval types can be represented in the same series
  by using multiple key values (eg, 1 for feature A, 2 for feature B, 3 for feature
  C, etc). The field data stores an 8-bit integer. This is largely an alias of a standard
  TimeSeries but that is identifiable as representing time intervals in a machine-readable
  way.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
neurodata_type_def: IntervalSeries
neurodata_type_inc: TimeSeries

3.7.4. DecompositionSeries

Extends: TimeSeries

Description: see Section 2.6.4

YAML Specification:

attributes:
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - default_value: no unit
    doc: Base unit of measurement for working with the data. Actual stored values
      are not necessarily stored in these units. To access the data in these units,
      multiply 'data' by 'conversion'.
    dtype: text
    name: unit
    required: false
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - num_times
  - num_channels
  - num_bands
  doc: Data decomposed into frequency bands.
  dtype: numeric
  name: data
  shape:
  -
  -
  -
- doc: The metric used, e.g. phase, amplitude, power.
  dtype: text
  name: metric
- doc: DynamicTableRegion pointer to the channels that this decomposition series was
    generated from.
  name: source_channels
  neurodata_type_inc: DynamicTableRegion
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Spectral analysis of a time series, e.g. of an LFP or a speech signal.
groups:
- datasets:
  - doc: Name of the band, e.g. theta.
    dtype: text
    name: band_name
    neurodata_type_inc: VectorData
  - dims:
    - num_bands
    - low, high
    doc: Low and high limit of each band in Hz. If it is a Gaussian filter, use 2
      SD on either side of the center.
    dtype: float32
    name: band_limits
    neurodata_type_inc: VectorData
    shape:
    -
    - 2
  - dims:
    - num_bands
    doc: The mean Gaussian filters, in Hz.
    dtype: float32
    name: band_mean
    neurodata_type_inc: VectorData
    shape:
    -
  - dims:
    - num_bands
    doc: The standard deviation of Gaussian filters, in Hz.
    dtype: float32
    name: band_stdev
    neurodata_type_inc: VectorData
    shape:
    -
  doc: Table for describing the bands that this series was generated from. There should
    be one row in this table for each band.
  name: bands
  neurodata_type_inc: DynamicTable
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to TimeSeries object that this data was calculated from. Metadata about
    electrodes and their position can be read from that ElectricalSeries so it is
    not necessary to store that information here.
  name: source_timeseries
  quantity: '?'
  target_type: TimeSeries
neurodata_type_def: DecompositionSeries
neurodata_type_inc: TimeSeries

3.7.5. Units

Extends: DynamicTable

Description: see Section 2.6.5

YAML Specification:

attributes:
- dims:
  - num_columns
  doc: The names of the columns in this table. This should be used to specify an order
    to the columns.
  dtype: text
  name: colnames
  shape:
  -
- doc: Description of what is in this dynamic table.
  dtype: text
  name: description
datasets:
- doc: Index into the spike_times dataset.
  name: spike_times_index
  neurodata_type_inc: VectorIndex
  quantity: '?'
- attributes:
  - doc: The smallest possible difference between two spike times. Usually 1 divided
      by the acquisition sampling rate from which spike times were extracted, but
      could be larger if the acquisition time series was downsampled or smaller if
      the acquisition time series was smoothed/interpolated and it is possible for
      the spike time to be between samples.
    dtype: float64
    name: resolution
    required: false
  doc: Spike times for each unit in seconds.
  dtype: float64
  name: spike_times
  neurodata_type_inc: VectorData
  quantity: '?'
- doc: Index into the obs_intervals dataset.
  name: obs_intervals_index
  neurodata_type_inc: VectorIndex
  quantity: '?'
- dims:
  - num_intervals
  - start|end
  doc: Observation intervals for each unit.
  dtype: float64
  name: obs_intervals
  neurodata_type_inc: VectorData
  quantity: '?'
  shape:
  -
  - 2
- doc: Index into electrodes.
  name: electrodes_index
  neurodata_type_inc: VectorIndex
  quantity: '?'
- doc: Electrode that each spike unit came from, specified using a DynamicTableRegion.
  name: electrodes
  neurodata_type_inc: DynamicTableRegion
  quantity: '?'
- doc: Electrode group that each spike unit came from.
  dtype:
    reftype: object
    target_type: ElectrodeGroup
  name: electrode_group
  neurodata_type_inc: VectorData
  quantity: '?'
- attributes:
  - doc: Sampling rate, in hertz.
    dtype: float32
    name: sampling_rate
    required: false
  - doc: Unit of measurement. This value is fixed to 'volts'.
    dtype: text
    name: unit
    value: volts
  dims:
  - - num_units
    - num_samples
  - - num_units
    - num_samples
    - num_electrodes
  doc: Spike waveform mean for each spike unit.
  dtype: float32
  name: waveform_mean
  neurodata_type_inc: VectorData
  quantity: '?'
  shape:
  - -
    -
  - -
    -
    -
- attributes:
  - doc: Sampling rate, in hertz.
    dtype: float32
    name: sampling_rate
    required: false
  - doc: Unit of measurement. This value is fixed to 'volts'.
    dtype: text
    name: unit
    value: volts
  dims:
  - - num_units
    - num_samples
  - - num_units
    - num_samples
    - num_electrodes
  doc: Spike waveform standard deviation for each spike unit.
  dtype: float32
  name: waveform_sd
  neurodata_type_inc: VectorData
  quantity: '?'
  shape:
  - -
    -
  - -
    -
    -
- attributes:
  - doc: Sampling rate, in hertz.
    dtype: float32
    name: sampling_rate
    required: false
  - doc: Unit of measurement. This value is fixed to 'volts'.
    dtype: text
    name: unit
    value: volts
  dims:
  - num_waveforms
  - num_samples
  doc: Individual waveforms for each spike on each electrode. This is a doubly indexed
    column. The 'waveforms_index' column indexes which waveforms in this column belong
    to the same spike event for a given unit, where each waveform was recorded from
    a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index'
    column to indicate which spike events belong to a given unit. For example, if
    the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements
    of the 'waveforms_index' column correspond to the 2 spike events of the first
    unit, the next 3 elements of the 'waveforms_index' column correspond to the 3
    spike events of the second unit, and the next 1 element of the 'waveforms_index'
    column corresponds to the 1 spike event of the third unit. If the 'waveforms_index'
    column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms'
    column contain the 3 spike waveforms that were recorded from 3 different electrodes
    for the first spike time of the first unit. See
    https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays
    for a graphical representation of this example. When there is only one electrode
    for each unit (i.e., each spike time is associated with a single waveform), then
    the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number
    of spike events. The number of electrodes for each spike event should be the same
    within a given unit. The 'electrodes' column should be used to indicate which
    electrodes are associated with each unit, and the order of the waveforms within
    a given unit x spike event should be in the same order as the electrodes referenced
    in the 'electrodes' column of this table. The number of samples for each waveform
    must be the same.
  dtype: numeric
  name: waveforms
  neurodata_type_inc: VectorData
  quantity: '?'
  shape:
  -
  -
- doc: Index into the waveforms dataset. One value for every spike event. See 'waveforms'
    for more detail.
  name: waveforms_index
  neurodata_type_inc: VectorIndex
  quantity: '?'
- doc: Index into the waveforms_index dataset. One value for every unit (row in the
    table). See 'waveforms' for more detail.
  name: waveforms_index_index
  neurodata_type_inc: VectorIndex
  quantity: '?'
- dims:
  - num_rows
  doc: Array of unique identifiers for the rows of this dynamic table.
  dtype: int
  name: id
  neurodata_type_inc: ElementIdentifiers
  shape:
  -
- doc: Vector columns, including index columns, of this dynamic table.
  neurodata_type_inc: VectorData
  quantity: '*'
default_name: Units
doc: Data about spiking units. Event times of observed units (e.g. cell, synapse,
  etc.) should be concatenated and stored in spike_times.
neurodata_type_def: Units
neurodata_type_inc: DynamicTable

3.8. Behavior

This source module contains neurodata_types for behavior data.

3.8.1. SpatialSeries

Extends: TimeSeries

Description: see Section 2.7.1

YAML Specification:

attributes:
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - default_value: meters
    doc: Base unit of measurement for working with the data. The default value is
      'meters'. Actual stored values are not necessarily stored in these units. To
      access the data in these units, multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
    required: false
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - - num_times
  - - num_times
    - x
  - - num_times
    - x,y
  - - num_times
    - x,y,z
  doc: 1-D or 2-D array storing position or direction relative to some reference frame.
  dtype: numeric
  name: data
  shape:
  - -
  - -
    - 1
  - -
    - 2
  - -
    - 3
- doc: Description defining what exactly 'straight-ahead' means.
  dtype: text
  name: reference_frame
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: "Direction, e.g., of gaze or travel, or position. The TimeSeries::data field
  is a 2D array storing position or direction relative to some reference frame. Array
  structure: [num measurements] [num dimensions]. Each SpatialSeries has a text dataset
  reference_frame that indicates the zero-position, or the zero-axes for direction.
  For example, if representing gaze direction, 'straight-ahead' might be a specific
  pixel on the monitor, or some other point in space. For position data, the 0,0 point
  might be the top-left corner of an enclosure, as viewed from the tracking camera.
  The unit of data will indicate how to interpret SpatialSeries values."
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
neurodata_type_def: SpatialSeries
neurodata_type_inc: TimeSeries

3.8.2. BehavioralEpochs

Extends: NWBDataInterface

Description: see Section 2.7.2

YAML Specification:

default_name: BehavioralEpochs
doc: TimeSeries for storing behavioral epochs.  The objective of this and the other
  two Behavioral interfaces (e.g. BehavioralEvents and BehavioralTimeSeries) is to
  provide generic hooks for software tools/scripts. This allows a tool/script to take
  the output one specific interface (e.g., UnitTimes) and plot that data relative
  to another data modality (e.g., behavioral events) without having to define all
  possible modalities in advance. Declaring one of these interfaces means that one
  or more TimeSeries of the specified type is published. These TimeSeries should reside
  in a group having the same name as the interface. For example, if a BehavioralTimeSeries
  interface is declared, the module will have one or more TimeSeries defined in the
  module sub-group 'BehavioralTimeSeries'. BehavioralEpochs should use IntervalSeries.
  BehavioralEvents is used for irregular events. BehavioralTimeSeries is for continuous
  data.
groups:
- doc: IntervalSeries object containing start and stop times of epochs.
  neurodata_type_inc: IntervalSeries
  quantity: '*'
neurodata_type_def: BehavioralEpochs
neurodata_type_inc: NWBDataInterface

3.8.3. BehavioralEvents

Extends: NWBDataInterface

Description: see Section 2.7.3

YAML Specification:

default_name: BehavioralEvents
doc: TimeSeries for storing behavioral events. See description of <a href="#BehavioralEpochs">BehavioralEpochs</a>
  for more details.
groups:
- doc: TimeSeries object containing behavioral events.
  neurodata_type_inc: TimeSeries
  quantity: '*'
neurodata_type_def: BehavioralEvents
neurodata_type_inc: NWBDataInterface

3.8.4. BehavioralTimeSeries

Extends: NWBDataInterface

Description: see Section 2.7.4

YAML Specification:

default_name: BehavioralTimeSeries
doc: TimeSeries for storing Behavoioral time series data. See description of <a href="#BehavioralEpochs">BehavioralEpochs</a>
  for more details.
groups:
- doc: TimeSeries object containing continuous behavioral data.
  neurodata_type_inc: TimeSeries
  quantity: '*'
neurodata_type_def: BehavioralTimeSeries
neurodata_type_inc: NWBDataInterface

3.8.5. PupilTracking

Extends: NWBDataInterface

Description: see Section 2.7.5

YAML Specification:

default_name: PupilTracking
doc: Eye-tracking data, representing pupil size.
groups:
- doc: TimeSeries object containing time series data on pupil size.
  neurodata_type_inc: TimeSeries
  quantity: +
neurodata_type_def: PupilTracking
neurodata_type_inc: NWBDataInterface

3.8.6. EyeTracking

Extends: NWBDataInterface

Description: see Section 2.7.6

YAML Specification:

default_name: EyeTracking
doc: Eye-tracking data, representing direction of gaze.
groups:
- doc: SpatialSeries object containing data measuring direction of gaze.
  neurodata_type_inc: SpatialSeries
  quantity: '*'
neurodata_type_def: EyeTracking
neurodata_type_inc: NWBDataInterface

3.8.7. CompassDirection

Extends: NWBDataInterface

Description: see Section 2.7.7

YAML Specification:

default_name: CompassDirection
doc: With a CompassDirection interface, a module publishes a SpatialSeries object
  representing a floating point value for theta. The SpatialSeries::reference_frame
  field should indicate what direction corresponds to 0 and which is the direction
  of rotation (this should be clockwise). The si_unit for the SpatialSeries should
  be radians or degrees.
groups:
- doc: SpatialSeries object containing direction of gaze travel.
  neurodata_type_inc: SpatialSeries
  quantity: '*'
neurodata_type_def: CompassDirection
neurodata_type_inc: NWBDataInterface

3.8.8. Position

Extends: NWBDataInterface

Description: see Section 2.7.8

YAML Specification:

default_name: Position
doc: Position data, whether along the x, x/y or x/y/z axis.
groups:
- doc: SpatialSeries object containing position data.
  neurodata_type_inc: SpatialSeries
  quantity: +
neurodata_type_def: Position
neurodata_type_inc: NWBDataInterface

3.9. Extracellular electrophysiology

This source module contains neurodata_types for extracellular electrophysiology data.

3.9.1. ElectricalSeries

Extends: TimeSeries

Description: see Section 2.8.1

YAML Specification:

attributes:
- doc: Filtering applied to all channels of the data. For example, if this ElectricalSeries
    represents high-pass-filtered data (also known as AP Band), then this value could
    be "High-pass 4-pole Bessel filter at 500 Hz". If this ElectricalSeries represents
    low-pass-filtered LFP data and the type of filter is unknown, then this value
    could be "Low-pass filter at 300 Hz". If a non-standard filter type is used, provide
    as much detail about the filter properties as possible.
  dtype: text
  name: filtering
  required: false
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - doc: Base unit of measurement for working with the data. This value is fixed to
      'volts'. Actual stored values are not necessarily stored in these units. To
      access the data in these units, multiply 'data' by 'conversion', followed by
      'channel_conversion' (if present), and then add 'offset'.
    dtype: text
    name: unit
    value: volts
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - - num_times
  - - num_times
    - num_channels
  - - num_times
    - num_channels
    - num_samples
  doc: Recorded voltage data.
  dtype: numeric
  name: data
  shape:
  - -
  - -
    -
  - -
    -
    -
- doc: DynamicTableRegion pointer to the electrodes that this time series was generated
    from.
  name: electrodes
  neurodata_type_inc: DynamicTableRegion
- attributes:
  - doc: The zero-indexed axis of the 'data' dataset that the channel-specific conversion
      factor corresponds to. This value is fixed to 1.
    dtype: int32
    name: axis
    value: 1
  dims:
  - num_channels
  doc: Channel-specific conversion factor. Multiply the data in the 'data' dataset
    by these values along the channel axis (as indicated by axis attribute) AND by
    the global conversion factor in the 'conversion' attribute of 'data' to get the
    data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion.
    This approach allows for both global and per-channel data conversion factors needed
    to support the storage of electrical recordings as native values generated by
    data acquisition systems. If this dataset is not present, then there is no channel-specific
    conversion factor, i.e. it is 1 for all channels.
  dtype: float32
  name: channel_conversion
  quantity: '?'
  shape:
  -
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: A time series of acquired voltage data from extracellular recordings. The data
  field is an int or float array storing data in volts. The first dimension should
  always represent time. The second dimension, if present, should represent channels.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
neurodata_type_def: ElectricalSeries
neurodata_type_inc: TimeSeries

3.9.2. SpikeEventSeries

Extends: ElectricalSeries

Description: see Section 2.8.2

YAML Specification:

attributes:
- doc: Filtering applied to all channels of the data. For example, if this ElectricalSeries
    represents high-pass-filtered data (also known as AP Band), then this value could
    be "High-pass 4-pole Bessel filter at 500 Hz". If this ElectricalSeries represents
    low-pass-filtered LFP data and the type of filter is unknown, then this value
    could be "Low-pass filter at 300 Hz". If a non-standard filter type is used, provide
    as much detail about the filter properties as possible.
  dtype: text
  name: filtering
  required: false
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - doc: Unit of measurement for waveforms, which is fixed to 'volts'.
    dtype: text
    name: unit
    value: volts
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - - num_events
    - num_samples
  - - num_events
    - num_channels
    - num_samples
  doc: Spike waveforms.
  dtype: numeric
  name: data
  shape:
  - -
    -
  - -
    -
    -
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time. Timestamps are required
    for the events. Unlike for TimeSeries, timestamps are required for SpikeEventSeries
    and are thus re-specified here.
  dtype: float64
  name: timestamps
  shape:
  -
- doc: DynamicTableRegion pointer to the electrodes that this time series was generated
    from.
  name: electrodes
  neurodata_type_inc: DynamicTableRegion
- attributes:
  - doc: The zero-indexed axis of the 'data' dataset that the channel-specific conversion
      factor corresponds to. This value is fixed to 1.
    dtype: int32
    name: axis
    value: 1
  dims:
  - num_channels
  doc: Channel-specific conversion factor. Multiply the data in the 'data' dataset
    by these values along the channel axis (as indicated by axis attribute) AND by
    the global conversion factor in the 'conversion' attribute of 'data' to get the
    data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion.
    This approach allows for both global and per-channel data conversion factors needed
    to support the storage of electrical recordings as native values generated by
    data acquisition systems. If this dataset is not present, then there is no channel-specific
    conversion factor, i.e. it is 1 for all channels.
  dtype: float32
  name: channel_conversion
  quantity: '?'
  shape:
  -
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: 'Stores snapshots/snippets of recorded spike events (i.e., threshold crossings).
  This may also be raw data, as reported by ephys hardware. If so, the TimeSeries::description
  field should describe how events were detected. All SpikeEventSeries should reside
  in a module (under EventWaveform interface) even if the spikes were reported and
  stored by hardware. All events span the same recording channels and store snapshots
  of equal duration. TimeSeries::data array structure: [num events] [num channels]
  [num samples] (or [num events] [num samples] for single electrode).'
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
neurodata_type_def: SpikeEventSeries
neurodata_type_inc: ElectricalSeries

3.9.3. FeatureExtraction

Extends: NWBDataInterface

Description: see Section 2.8.3

YAML Specification:

datasets:
- dims:
  - num_features
  doc: Description of features (eg, ''PC1'') for each of the extracted features.
  dtype: text
  name: description
  shape:
  -
- dims:
  - num_events
  - num_channels
  - num_features
  doc: Multi-dimensional array of features extracted from each event.
  dtype: float32
  name: features
  shape:
  -
  -
  -
- dims:
  - num_events
  doc: Times of events that features correspond to (can be a link).
  dtype: float64
  name: times
  shape:
  -
- doc: DynamicTableRegion pointer to the electrodes that this time series was generated
    from.
  name: electrodes
  neurodata_type_inc: DynamicTableRegion
default_name: FeatureExtraction
doc: Features, such as PC1 and PC2, that are extracted from signals stored in a SpikeEventSeries
  or other source.
neurodata_type_def: FeatureExtraction
neurodata_type_inc: NWBDataInterface

3.9.4. EventDetection

Extends: NWBDataInterface

Description: see Section 2.8.4

YAML Specification:

datasets:
- doc: Description of how events were detected, such as voltage threshold, or dV/dT
    threshold, as well as relevant values.
  dtype: text
  name: detection_method
- dims:
  - num_events
  doc: Indices (zero-based) into source ElectricalSeries::data array corresponding
    to time of event. ''description'' should define what is meant by time of event
    (e.g., .25 ms before action potential peak, zero-crossing time, etc). The index
    points to each event from the raw data.
  dtype: int32
  name: source_idx
  shape:
  -
- attributes:
  - doc: Unit of measurement for event times, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_events
  doc: Timestamps of events, in seconds.
  dtype: float64
  name: times
  shape:
  -
default_name: EventDetection
doc: Detected spike events from voltage trace(s).
links:
- doc: Link to the ElectricalSeries that this data was calculated from. Metadata about
    electrodes and their position can be read from that ElectricalSeries so it's not
    necessary to include that information here.
  name: source_electricalseries
  target_type: ElectricalSeries
neurodata_type_def: EventDetection
neurodata_type_inc: NWBDataInterface

3.9.5. EventWaveform

Extends: NWBDataInterface

Description: see Section 2.8.5

YAML Specification:

default_name: EventWaveform
doc: Represents either the waveforms of detected events, as extracted from a raw data
  trace in /acquisition, or the event waveforms that were stored during experiment
  acquisition.
groups:
- doc: SpikeEventSeries object(s) containing detected spike event waveforms.
  neurodata_type_inc: SpikeEventSeries
  quantity: '*'
neurodata_type_def: EventWaveform
neurodata_type_inc: NWBDataInterface

3.9.6. FilteredEphys

Extends: NWBDataInterface

Description: see Section 2.8.6

YAML Specification:

default_name: FilteredEphys
doc: Electrophysiology data from one or more channels that has been subjected to filtering.
  Examples of filtered data include Theta and Gamma (LFP has its own interface). FilteredEphys
  modules publish an ElectricalSeries for each filtered channel or set of channels.
  The name of each ElectricalSeries is arbitrary but should be informative. The source
  of the filtered data, whether this is from analysis of another time series or as
  acquired by hardware, should be noted in each's TimeSeries::description field. There
  is no assumed 1::1 correspondence between filtered ephys signals and electrodes,
  as a single signal can apply to many nearby electrodes, and one electrode may have
  different filtered (e.g., theta and/or gamma) signals represented. Filter properties
  should be noted in the ElectricalSeries 'filtering' attribute.
groups:
- doc: ElectricalSeries object(s) containing filtered electrophysiology data.
  neurodata_type_inc: ElectricalSeries
  quantity: +
neurodata_type_def: FilteredEphys
neurodata_type_inc: NWBDataInterface

3.9.7. LFP

Extends: NWBDataInterface

Description: see Section 2.8.7

YAML Specification:

default_name: LFP
doc: LFP data from one or more channels. The electrode map in each published ElectricalSeries
  will identify which channels are providing LFP data. Filter properties should be
  noted in the ElectricalSeries 'filtering' attribute.
groups:
- doc: ElectricalSeries object(s) containing LFP data for one or more channels.
  neurodata_type_inc: ElectricalSeries
  quantity: +
neurodata_type_def: LFP
neurodata_type_inc: NWBDataInterface

3.9.8. ElectrodeGroup

Extends: NWBContainer

Description: see Section 2.8.8

YAML Specification:

attributes:
- doc: Description of this electrode group.
  dtype: text
  name: description
- doc: Location of electrode group. Specify the area, layer, comments on estimation
    of area/layer, etc. Use standard atlas names for anatomical regions when possible.
  dtype: text
  name: location
datasets:
- doc: stereotaxic or common framework coordinates
  dtype:
  - doc: x coordinate
    dtype: float32
    name: x
  - doc: y coordinate
    dtype: float32
    name: y
  - doc: z coordinate
    dtype: float32
    name: z
  name: position
  quantity: '?'
doc: A physical grouping of electrodes, e.g. a shank of an array.
links:
- doc: Link to the device that was used to record from this electrode group.
  name: device
  target_type: Device
neurodata_type_def: ElectrodeGroup
neurodata_type_inc: NWBContainer

3.9.9. ClusterWaveforms

Extends: NWBDataInterface

Description: see Section 2.8.9

YAML Specification:

datasets:
- doc: Filtering applied to data before generating mean/sd
  dtype: text
  name: waveform_filtering
- dims:
  - num_clusters
  - num_samples
  doc: The mean waveform for each cluster, using the same indices for each wave as
    cluster numbers in the associated Clustering module (i.e, cluster 3 is in array
    slot [3]). Waveforms corresponding to gaps in cluster sequence should be empty
    (e.g., zero- filled)
  dtype: float32
  name: waveform_mean
  shape:
  -
  -
- dims:
  - num_clusters
  - num_samples
  doc: Stdev of waveforms for each cluster, using the same indices as in mean
  dtype: float32
  name: waveform_sd
  shape:
  -
  -
default_name: ClusterWaveforms
doc: DEPRECATED The mean waveform shape, including standard deviation, of the different
  clusters. Ideally, the waveform analysis should be performed on data that is only
  high-pass filtered. This is a separate module because it is expected to require
  updating. For example, IMEC probes may require different storage requirements to
  store/display mean waveforms, requiring a new interface or an extension of this
  one.
links:
- doc: Link to Clustering interface that was the source of the clustered data
  name: clustering_interface
  target_type: Clustering
neurodata_type_def: ClusterWaveforms
neurodata_type_inc: NWBDataInterface

3.9.10. Clustering

Extends: NWBDataInterface

Description: see Section 2.8.10

YAML Specification:

datasets:
- doc: Description of clusters or clustering, (e.g. cluster 0 is noise, clusters curated
    using Klusters, etc)
  dtype: text
  name: description
- dims:
  - num_events
  doc: Cluster number of each event
  dtype: int32
  name: num
  shape:
  -
- dims:
  - num_clusters
  doc: Maximum ratio of waveform peak to RMS on any channel in the cluster (provides
    a basic clustering metric).
  dtype: float32
  name: peak_over_rms
  shape:
  -
- dims:
  - num_events
  doc: Times of clustered events, in seconds. This may be a link to times field in
    associated FeatureExtraction module.
  dtype: float64
  name: times
  shape:
  -
default_name: Clustering
doc: DEPRECATED Clustered spike data, whether from automatic clustering tools (e.g.,
  klustakwik) or as a result of manual sorting.
neurodata_type_def: Clustering
neurodata_type_inc: NWBDataInterface

3.10. Intracellular electrophysiology

This source module contains neurodata_types for intracellular electrophysiology data.

3.10.1. PatchClampSeries

Extends: TimeSeries

Description: see Section 2.9.1

YAML Specification:

attributes:
- doc: Protocol/stimulus name for this patch-clamp dataset.
  dtype: text
  name: stimulus_description
- doc: Sweep number, allows to group different PatchClampSeries together.
  dtype: uint32
  name: sweep_number
  required: false
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - doc: Base unit of measurement for working with the data. Actual stored values
      are not necessarily stored in these units. To access the data in these units,
      multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - num_times
  doc: Recorded voltage or current.
  dtype: numeric
  name: data
  shape:
  -
- doc: Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp).
  dtype: float32
  name: gain
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: An abstract base class for patch-clamp data - stimulus or response, current or
  voltage.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to IntracellularElectrode object that describes the electrode that was
    used to apply or record this data.
  name: electrode
  target_type: IntracellularElectrode
neurodata_type_def: PatchClampSeries
neurodata_type_inc: TimeSeries

3.10.2. CurrentClampSeries

Extends: PatchClampSeries

Description: see Section 2.9.2

YAML Specification:

attributes:
- doc: Protocol/stimulus name for this patch-clamp dataset.
  dtype: text
  name: stimulus_description
- doc: Sweep number, allows to group different PatchClampSeries together.
  dtype: uint32
  name: sweep_number
  required: false
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - doc: Base unit of measurement for working with the data. which is fixed to 'volts'.
      Actual stored values are not necessarily stored in these units. To access the
      data in these units, multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
    value: volts
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  doc: Recorded voltage.
  name: data
- doc: Bias current, in amps.
  dtype: float32
  name: bias_current
  quantity: '?'
- doc: Bridge balance, in ohms.
  dtype: float32
  name: bridge_balance
  quantity: '?'
- doc: Capacitance compensation, in farads.
  dtype: float32
  name: capacitance_compensation
  quantity: '?'
- doc: Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp).
  dtype: float32
  name: gain
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Voltage data from an intracellular current-clamp recording. A corresponding CurrentClampStimulusSeries
  (stored separately as a stimulus) is used to store the current injected.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to IntracellularElectrode object that describes the electrode that was
    used to apply or record this data.
  name: electrode
  target_type: IntracellularElectrode
neurodata_type_def: CurrentClampSeries
neurodata_type_inc: PatchClampSeries

3.10.3. IZeroClampSeries

Extends: CurrentClampSeries

Description: see Section 2.9.3

YAML Specification:

attributes:
- doc: An IZeroClampSeries has no stimulus, so this attribute is automatically set
    to "N/A"
  dtype: text
  name: stimulus_description
  value: N/A
- doc: Sweep number, allows to group different PatchClampSeries together.
  dtype: uint32
  name: sweep_number
  required: false
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- doc: Bias current, in amps, fixed to 0.0.
  dtype: float32
  name: bias_current
- doc: Bridge balance, in ohms, fixed to 0.0.
  dtype: float32
  name: bridge_balance
- doc: Capacitance compensation, in farads, fixed to 0.0.
  dtype: float32
  name: capacitance_compensation
- attributes:
  - doc: Base unit of measurement for working with the data. which is fixed to 'volts'.
      Actual stored values are not necessarily stored in these units. To access the
      data in these units, multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
    value: volts
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  doc: Recorded voltage.
  name: data
- doc: Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp).
  dtype: float32
  name: gain
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Voltage data from an intracellular recording when all current and amplifier settings
  are off (i.e., CurrentClampSeries fields will be zero). There is no CurrentClampStimulusSeries
  associated with an IZero series because the amplifier is disconnected and no stimulus
  can reach the cell.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to IntracellularElectrode object that describes the electrode that was
    used to apply or record this data.
  name: electrode
  target_type: IntracellularElectrode
neurodata_type_def: IZeroClampSeries
neurodata_type_inc: CurrentClampSeries

3.10.4. CurrentClampStimulusSeries

Extends: PatchClampSeries

Description: see Section 2.9.4

YAML Specification:

attributes:
- doc: Protocol/stimulus name for this patch-clamp dataset.
  dtype: text
  name: stimulus_description
- doc: Sweep number, allows to group different PatchClampSeries together.
  dtype: uint32
  name: sweep_number
  required: false
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - doc: Base unit of measurement for working with the data. which is fixed to 'amperes'.
      Actual stored values are not necessarily stored in these units. To access the
      data in these units, multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
    value: amperes
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  doc: Stimulus current applied.
  name: data
- doc: Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp).
  dtype: float32
  name: gain
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Stimulus current applied during current clamp recording.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to IntracellularElectrode object that describes the electrode that was
    used to apply or record this data.
  name: electrode
  target_type: IntracellularElectrode
neurodata_type_def: CurrentClampStimulusSeries
neurodata_type_inc: PatchClampSeries

3.10.5. VoltageClampSeries

Extends: PatchClampSeries

Description: see Section 2.9.5

YAML Specification:

attributes:
- doc: Protocol/stimulus name for this patch-clamp dataset.
  dtype: text
  name: stimulus_description
- doc: Sweep number, allows to group different PatchClampSeries together.
  dtype: uint32
  name: sweep_number
  required: false
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - doc: Base unit of measurement for working with the data. which is fixed to 'amperes'.
      Actual stored values are not necessarily stored in these units. To access the
      data in these units, multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
    value: amperes
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  doc: Recorded current.
  name: data
- attributes:
  - doc: Unit of measurement for capacitance_fast, which is fixed to 'farads'.
    dtype: text
    name: unit
    value: farads
  doc: Fast capacitance, in farads.
  dtype: float32
  name: capacitance_fast
  quantity: '?'
- attributes:
  - doc: Unit of measurement for capacitance_fast, which is fixed to 'farads'.
    dtype: text
    name: unit
    value: farads
  doc: Slow capacitance, in farads.
  dtype: float32
  name: capacitance_slow
  quantity: '?'
- attributes:
  - doc: Unit of measurement for resistance_comp_bandwidth, which is fixed to 'hertz'.
    dtype: text
    name: unit
    value: hertz
  doc: Resistance compensation bandwidth, in hertz.
  dtype: float32
  name: resistance_comp_bandwidth
  quantity: '?'
- attributes:
  - doc: Unit of measurement for resistance_comp_correction, which is fixed to 'percent'.
    dtype: text
    name: unit
    value: percent
  doc: Resistance compensation correction, in percent.
  dtype: float32
  name: resistance_comp_correction
  quantity: '?'
- attributes:
  - doc: Unit of measurement for resistance_comp_prediction, which is fixed to 'percent'.
    dtype: text
    name: unit
    value: percent
  doc: Resistance compensation prediction, in percent.
  dtype: float32
  name: resistance_comp_prediction
  quantity: '?'
- attributes:
  - doc: Unit of measurement for whole_cell_capacitance_comp, which is fixed to 'farads'.
    dtype: text
    name: unit
    value: farads
  doc: Whole cell capacitance compensation, in farads.
  dtype: float32
  name: whole_cell_capacitance_comp
  quantity: '?'
- attributes:
  - doc: Unit of measurement for whole_cell_series_resistance_comp, which is fixed
      to 'ohms'.
    dtype: text
    name: unit
    value: ohms
  doc: Whole cell series resistance compensation, in ohms.
  dtype: float32
  name: whole_cell_series_resistance_comp
  quantity: '?'
- doc: Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp).
  dtype: float32
  name: gain
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Current data from an intracellular voltage-clamp recording. A corresponding VoltageClampStimulusSeries
  (stored separately as a stimulus) is used to store the voltage injected.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to IntracellularElectrode object that describes the electrode that was
    used to apply or record this data.
  name: electrode
  target_type: IntracellularElectrode
neurodata_type_def: VoltageClampSeries
neurodata_type_inc: PatchClampSeries

3.10.6. VoltageClampStimulusSeries

Extends: PatchClampSeries

Description: see Section 2.9.6

YAML Specification:

attributes:
- doc: Protocol/stimulus name for this patch-clamp dataset.
  dtype: text
  name: stimulus_description
- doc: Sweep number, allows to group different PatchClampSeries together.
  dtype: uint32
  name: sweep_number
  required: false
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - doc: Base unit of measurement for working with the data. which is fixed to 'volts'.
      Actual stored values are not necessarily stored in these units. To access the
      data in these units, multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
    value: volts
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  doc: Stimulus voltage applied.
  name: data
- doc: Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp).
  dtype: float32
  name: gain
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Stimulus voltage applied during a voltage clamp recording.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to IntracellularElectrode object that describes the electrode that was
    used to apply or record this data.
  name: electrode
  target_type: IntracellularElectrode
neurodata_type_def: VoltageClampStimulusSeries
neurodata_type_inc: PatchClampSeries

3.10.7. IntracellularElectrode

Extends: NWBContainer

Description: see Section 2.9.7

YAML Specification:

datasets:
- doc: unique ID of the cell
  dtype: text
  name: cell_id
  quantity: '?'
- doc: Description of electrode (e.g.,  whole-cell, sharp, etc.).
  dtype: text
  name: description
- doc: Electrode specific filtering.
  dtype: text
  name: filtering
  quantity: '?'
- doc: Initial access resistance.
  dtype: text
  name: initial_access_resistance
  quantity: '?'
- doc: Location of the electrode. Specify the area, layer, comments on estimation
    of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names
    for anatomical regions when possible.
  dtype: text
  name: location
  quantity: '?'
- doc: Electrode resistance, in ohms.
  dtype: text
  name: resistance
  quantity: '?'
- doc: Information about seal used for recording.
  dtype: text
  name: seal
  quantity: '?'
- doc: Information about slice used for recording.
  dtype: text
  name: slice
  quantity: '?'
doc: An intracellular electrode and its metadata.
links:
- doc: Device that was used to record from this electrode.
  name: device
  target_type: Device
neurodata_type_def: IntracellularElectrode
neurodata_type_inc: NWBContainer

3.10.8. SweepTable

Extends: DynamicTable

Description: see Section 2.9.8

YAML Specification:

attributes:
- dims:
  - num_columns
  doc: The names of the columns in this table. This should be used to specify an order
    to the columns.
  dtype: text
  name: colnames
  shape:
  -
- doc: Description of what is in this dynamic table.
  dtype: text
  name: description
datasets:
- doc: Sweep number of the PatchClampSeries in that row.
  dtype: uint32
  name: sweep_number
  neurodata_type_inc: VectorData
- doc: The PatchClampSeries with the sweep number in that row.
  dtype:
    reftype: object
    target_type: PatchClampSeries
  name: series
  neurodata_type_inc: VectorData
- doc: Index for series.
  name: series_index
  neurodata_type_inc: VectorIndex
- dims:
  - num_rows
  doc: Array of unique identifiers for the rows of this dynamic table.
  dtype: int
  name: id
  neurodata_type_inc: ElementIdentifiers
  shape:
  -
- doc: Vector columns, including index columns, of this dynamic table.
  neurodata_type_inc: VectorData
  quantity: '*'
doc: '[DEPRECATED] Table used to group different PatchClampSeries. SweepTable is being
  replaced by IntracellularRecordingsTable and SimultaneousRecordingsTable tables.
  Additional SequentialRecordingsTable, RepetitionsTable, and ExperimentalConditions
  tables provide enhanced support for experiment metadata.'
neurodata_type_def: SweepTable
neurodata_type_inc: DynamicTable

3.10.9. IntracellularElectrodesTable

Extends: DynamicTable

Description: see Section 2.9.9

YAML Specification:

attributes:
- doc: Description of what is in this dynamic table.
  dtype: text
  name: description
  value: Table for storing intracellular electrode related metadata.
- dims:
  - num_columns
  doc: The names of the columns in this table. This should be used to specify an order
    to the columns.
  dtype: text
  name: colnames
  shape:
  -
datasets:
- doc: Column for storing the reference to the intracellular electrode.
  dtype:
    reftype: object
    target_type: IntracellularElectrode
  name: electrode
  neurodata_type_inc: VectorData
- dims:
  - num_rows
  doc: Array of unique identifiers for the rows of this dynamic table.
  dtype: int
  name: id
  neurodata_type_inc: ElementIdentifiers
  shape:
  -
- doc: Vector columns, including index columns, of this dynamic table.
  neurodata_type_inc: VectorData
  quantity: '*'
doc: Table for storing intracellular electrode related metadata.
neurodata_type_def: IntracellularElectrodesTable
neurodata_type_inc: DynamicTable

3.10.10. IntracellularStimuliTable

Extends: DynamicTable

Description: see Section 2.9.10

YAML Specification:

attributes:
- doc: Description of what is in this dynamic table.
  dtype: text
  name: description
  value: Table for storing intracellular stimulus related metadata.
- dims:
  - num_columns
  doc: The names of the columns in this table. This should be used to specify an order
    to the columns.
  dtype: text
  name: colnames
  shape:
  -
datasets:
- doc: Column storing the reference to the recorded stimulus for the recording (rows).
  name: stimulus
  neurodata_type_inc: TimeSeriesReferenceVectorData
- dims:
  - num_rows
  doc: Array of unique identifiers for the rows of this dynamic table.
  dtype: int
  name: id
  neurodata_type_inc: ElementIdentifiers
  shape:
  -
- doc: Vector columns, including index columns, of this dynamic table.
  neurodata_type_inc: VectorData
  quantity: '*'
doc: Table for storing intracellular stimulus related metadata.
neurodata_type_def: IntracellularStimuliTable
neurodata_type_inc: DynamicTable

3.10.11. IntracellularResponsesTable

Extends: DynamicTable

Description: see Section 2.9.11

YAML Specification:

attributes:
- doc: Description of what is in this dynamic table.
  dtype: text
  name: description
  value: Table for storing intracellular response related metadata.
- dims:
  - num_columns
  doc: The names of the columns in this table. This should be used to specify an order
    to the columns.
  dtype: text
  name: colnames
  shape:
  -
datasets:
- doc: Column storing the reference to the recorded response for the recording (rows)
  name: response
  neurodata_type_inc: TimeSeriesReferenceVectorData
- dims:
  - num_rows
  doc: Array of unique identifiers for the rows of this dynamic table.
  dtype: int
  name: id
  neurodata_type_inc: ElementIdentifiers
  shape:
  -
- doc: Vector columns, including index columns, of this dynamic table.
  neurodata_type_inc: VectorData
  quantity: '*'
doc: Table for storing intracellular response related metadata.
neurodata_type_def: IntracellularResponsesTable
neurodata_type_inc: DynamicTable

3.10.12. IntracellularRecordingsTable

Extends: AlignedDynamicTable

Description: see Section 2.9.12

YAML Specification:

attributes:
- doc: Description of the contents of this table. Inherited from AlignedDynamicTable
    and overwritten here to fix the value of the attribute.
  dtype: text
  name: description
  value: A table to group together a stimulus and response from a single electrode
    and a single simultaneous recording and for storing metadata about the intracellular
    recording.
- dims:
  - num_categories
  doc: The names of the categories in this AlignedDynamicTable. Each category is represented
    by one DynamicTable stored in the parent group. This attribute should be used
    to specify an order of categories and the category names must match the names
    of the corresponding DynamicTable in the group.
  dtype: text
  name: categories
  shape:
  -
- dims:
  - num_columns
  doc: The names of the columns in this table. This should be used to specify an order
    to the columns.
  dtype: text
  name: colnames
  shape:
  -
datasets:
- dims:
  - num_rows
  doc: Array of unique identifiers for the rows of this dynamic table.
  dtype: int
  name: id
  neurodata_type_inc: ElementIdentifiers
  shape:
  -
- doc: Vector columns, including index columns, of this dynamic table.
  neurodata_type_inc: VectorData
  quantity: '*'
doc: A table to group together a stimulus and response from a single electrode and
  a single simultaneous recording. Each row in the table represents a single recording
  consisting typically of a stimulus and a corresponding response. In some cases,
  however, only a stimulus or a response is recorded as part of an experiment. In
  this case, both the stimulus and response will point to the same TimeSeries while
  the idx_start and count of the invalid column will be set to -1, thus, indicating
  that no values have been recorded for the stimulus or response, respectively. Note,
  a recording MUST contain at least a stimulus or a response. Typically the stimulus
  and response are PatchClampSeries. However, the use of AD/DA channels that are not
  associated to an electrode is also common in intracellular electrophysiology, in
  which case other TimeSeries may be used.
groups:
- doc: Table for storing intracellular electrode related metadata.
  name: electrodes
  neurodata_type_inc: IntracellularElectrodesTable
- doc: Table for storing intracellular stimulus related metadata.
  name: stimuli
  neurodata_type_inc: IntracellularStimuliTable
- doc: Table for storing intracellular response related metadata.
  name: responses
  neurodata_type_inc: IntracellularResponsesTable
- doc: A DynamicTable representing a particular category for columns in the AlignedDynamicTable
    parent container. The table MUST be aligned with (i.e., have the same number of
    rows) as all other DynamicTables stored in the AlignedDynamicTable parent container.
    The name of the category is given by the name of the DynamicTable and its description
    by the description attribute of the DynamicTable.
  neurodata_type_inc: DynamicTable
  quantity: '*'
name: intracellular_recordings
neurodata_type_def: IntracellularRecordingsTable
neurodata_type_inc: AlignedDynamicTable

3.10.13. SimultaneousRecordingsTable

Extends: DynamicTable

Description: see Section 2.9.13

YAML Specification:

attributes:
- dims:
  - num_columns
  doc: The names of the columns in this table. This should be used to specify an order
    to the columns.
  dtype: text
  name: colnames
  shape:
  -
- doc: Description of what is in this dynamic table.
  dtype: text
  name: description
datasets:
- attributes:
  - doc: Reference to the IntracellularRecordingsTable table that this table region
      applies to. This specializes the attribute inherited from DynamicTableRegion
      to fix the type of table that can be referenced here.
    dtype:
      reftype: object
      target_type: IntracellularRecordingsTable
    name: table
  doc: A reference to one or more rows in the IntracellularRecordingsTable table.
  name: recordings
  neurodata_type_inc: DynamicTableRegion
- doc: Index dataset for the recordings column.
  name: recordings_index
  neurodata_type_inc: VectorIndex
- dims:
  - num_rows
  doc: Array of unique identifiers for the rows of this dynamic table.
  dtype: int
  name: id
  neurodata_type_inc: ElementIdentifiers
  shape:
  -
- doc: Vector columns, including index columns, of this dynamic table.
  neurodata_type_inc: VectorData
  quantity: '*'
doc: A table for grouping different intracellular recordings from the IntracellularRecordingsTable
  table together that were recorded simultaneously from different electrodes.
name: simultaneous_recordings
neurodata_type_def: SimultaneousRecordingsTable
neurodata_type_inc: DynamicTable

3.10.14. SequentialRecordingsTable

Extends: DynamicTable

Description: see Section 2.9.14

YAML Specification:

attributes:
- dims:
  - num_columns
  doc: The names of the columns in this table. This should be used to specify an order
    to the columns.
  dtype: text
  name: colnames
  shape:
  -
- doc: Description of what is in this dynamic table.
  dtype: text
  name: description
datasets:
- attributes:
  - doc: Reference to the SimultaneousRecordingsTable table that this table region
      applies to. This specializes the attribute inherited from DynamicTableRegion
      to fix the type of table that can be referenced here.
    dtype:
      reftype: object
      target_type: SimultaneousRecordingsTable
    name: table
  doc: A reference to one or more rows in the SimultaneousRecordingsTable table.
  name: simultaneous_recordings
  neurodata_type_inc: DynamicTableRegion
- doc: Index dataset for the simultaneous_recordings column.
  name: simultaneous_recordings_index
  neurodata_type_inc: VectorIndex
- doc: The type of stimulus used for the sequential recording.
  dtype: text
  name: stimulus_type
  neurodata_type_inc: VectorData
- dims:
  - num_rows
  doc: Array of unique identifiers for the rows of this dynamic table.
  dtype: int
  name: id
  neurodata_type_inc: ElementIdentifiers
  shape:
  -
- doc: Vector columns, including index columns, of this dynamic table.
  neurodata_type_inc: VectorData
  quantity: '*'
doc: A table for grouping different sequential recordings from the SimultaneousRecordingsTable
  table together. This is typically used to group together sequential recordings where
  a sequence of stimuli of the same type with varying parameters have been presented
  in a sequence.
name: sequential_recordings
neurodata_type_def: SequentialRecordingsTable
neurodata_type_inc: DynamicTable

3.10.15. RepetitionsTable

Extends: DynamicTable

Description: see Section 2.9.15

YAML Specification:

attributes:
- dims:
  - num_columns
  doc: The names of the columns in this table. This should be used to specify an order
    to the columns.
  dtype: text
  name: colnames
  shape:
  -
- doc: Description of what is in this dynamic table.
  dtype: text
  name: description
datasets:
- attributes:
  - doc: Reference to the SequentialRecordingsTable table that this table region applies
      to. This specializes the attribute inherited from DynamicTableRegion to fix
      the type of table that can be referenced here.
    dtype:
      reftype: object
      target_type: SequentialRecordingsTable
    name: table
  doc: A reference to one or more rows in the SequentialRecordingsTable table.
  name: sequential_recordings
  neurodata_type_inc: DynamicTableRegion
- doc: Index dataset for the sequential_recordings column.
  name: sequential_recordings_index
  neurodata_type_inc: VectorIndex
- dims:
  - num_rows
  doc: Array of unique identifiers for the rows of this dynamic table.
  dtype: int
  name: id
  neurodata_type_inc: ElementIdentifiers
  shape:
  -
- doc: Vector columns, including index columns, of this dynamic table.
  neurodata_type_inc: VectorData
  quantity: '*'
doc: A table for grouping different sequential intracellular recordings together.
  With each SequentialRecording typically representing a particular type of stimulus,
  the RepetitionsTable table is typically used to group sets of stimuli applied in
  sequence.
name: repetitions
neurodata_type_def: RepetitionsTable
neurodata_type_inc: DynamicTable

3.10.16. ExperimentalConditionsTable

Extends: DynamicTable

Description: see Section 2.9.16

YAML Specification:

attributes:
- dims:
  - num_columns
  doc: The names of the columns in this table. This should be used to specify an order
    to the columns.
  dtype: text
  name: colnames
  shape:
  -
- doc: Description of what is in this dynamic table.
  dtype: text
  name: description
datasets:
- attributes:
  - doc: Reference to the RepetitionsTable table that this table region applies to.
      This specializes the attribute inherited from DynamicTableRegion to fix the
      type of table that can be referenced here.
    dtype:
      reftype: object
      target_type: RepetitionsTable
    name: table
  doc: A reference to one or more rows in the RepetitionsTable table.
  name: repetitions
  neurodata_type_inc: DynamicTableRegion
- doc: Index dataset for the repetitions column.
  name: repetitions_index
  neurodata_type_inc: VectorIndex
- dims:
  - num_rows
  doc: Array of unique identifiers for the rows of this dynamic table.
  dtype: int
  name: id
  neurodata_type_inc: ElementIdentifiers
  shape:
  -
- doc: Vector columns, including index columns, of this dynamic table.
  neurodata_type_inc: VectorData
  quantity: '*'
doc: A table for grouping different intracellular recording repetitions together that
  belong to the same experimental condition.
name: experimental_conditions
neurodata_type_def: ExperimentalConditionsTable
neurodata_type_inc: DynamicTable

3.11. Optogenetics

This source module contains neurodata_types for opto-genetics data.

3.11.1. OptogeneticSeries

Extends: TimeSeries

Description: see Section 2.10.1

YAML Specification:

attributes:
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - doc: Unit of measurement for data, which is fixed to 'watts'.
    dtype: text
    name: unit
    value: watts
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - num_times
  doc: Applied power for optogenetic stimulus, in watts.
  dtype: numeric
  name: data
  shape:
  -
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: An optogenetic stimulus.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to OptogeneticStimulusSite object that describes the site to which this
    stimulus was applied.
  name: site
  target_type: OptogeneticStimulusSite
neurodata_type_def: OptogeneticSeries
neurodata_type_inc: TimeSeries

3.11.2. OptogeneticStimulusSite

Extends: NWBContainer

Description: see Section 2.10.2

YAML Specification:

datasets:
- doc: Description of stimulation site.
  dtype: text
  name: description
- doc: Excitation wavelength, in nm.
  dtype: float32
  name: excitation_lambda
- doc: Location of the stimulation site. Specify the area, layer, comments on estimation
    of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names
    for anatomical regions when possible.
  dtype: text
  name: location
doc: A site of optogenetic stimulation.
links:
- doc: Device that generated the stimulus.
  name: device
  target_type: Device
neurodata_type_def: OptogeneticStimulusSite
neurodata_type_inc: NWBContainer

3.12. Optical physiology

This source module contains neurodata_types for optical physiology data.

3.12.1. OnePhotonSeries

Extends: ImageSeries

Description: see Section 2.11.1

YAML Specification:

attributes:
- doc: Photomultiplier gain.
  dtype: float32
  name: pmt_gain
  required: false
- doc: Lines imaged per second. This is also stored in /general/optophysiology but
    is kept here as it is useful information for analysis, and so good to be stored
    w/ the actual data.
  dtype: float32
  name: scan_line_rate
  required: false
- doc: Exposure time of the sample; often the inverse of the frequency.
  dtype: float32
  name: exposure_time
  required: false
- doc: Amount of pixels combined into 'bins'; could be 1, 2, 4, 8, etc.
  dtype: uint8
  name: binning
  required: false
- doc: Power of the excitation in mW, if known.
  dtype: float32
  name: power
  required: false
- doc: Intensity of the excitation in mW/mm^2, if known.
  dtype: float32
  name: intensity
  required: false
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Base unit of measurement for working with the data. Actual stored values
      are not necessarily stored in these units. To access the data in these units,
      multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - - frame
    - x
    - y
  - - frame
    - x
    - y
    - z
  doc: Binary data representing images across frames. If data are stored in an external
    file, this should be an empty 3D array.
  dtype: numeric
  name: data
  shape:
  - -
    -
    -
  - -
    -
    -
    -
- dims:
  - rank
  doc: Number of pixels on x, y, (and z) axes.
  dtype: int32
  name: dimension
  quantity: '?'
  shape:
  -
- attributes:
  - dims:
    - num_files
    doc: Each external image may contain one or more consecutive frames of the full
      ImageSeries. This attribute serves as an index to indicate which frames each
      file contains, to faciliate random access. The 'starting_frame' attribute, hence,
      contains a list of frame numbers within the full ImageSeries of the first frame
      of each file listed in the parent 'external_file' dataset. Zero-based indexing
      is used (hence, the first element will always be zero). For example, if the
      'external_file' dataset has three paths to files and the first file has 5 frames,
      the second file has 10 frames, and the third file has 20 frames, then this attribute
      will have values [0, 5, 15]. If there is a single external file that holds all
      of the frames of the ImageSeries (and so there is a single element in the 'external_file'
      dataset), then this attribute should have value [0].
    dtype: int32
    name: starting_frame
    shape:
    -
  dims:
  - num_files
  doc: Paths to one or more external file(s). The field is only present if format='external'.
    This is only relevant if the image series is stored in the file system as one
    or more image file(s). This field should NOT be used if the image is stored in
    another NWB file and that file is linked to this file.
  dtype: text
  name: external_file
  quantity: '?'
  shape:
  -
- default_value: raw
  doc: Format of image. If this is 'external', then the attribute 'external_file'
    contains the path information to the image files. If this is 'raw', then the raw
    (single-channel) binary data is stored in the 'data' dataset. If this attribute
    is not present, then the default format='raw' case is assumed.
  dtype: text
  name: format
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Image stack recorded over time from 1-photon microscope.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to ImagingPlane object from which this TimeSeries data was generated.
  name: imaging_plane
  target_type: ImagingPlane
- doc: Link to the Device object that was used to capture these images.
  name: device
  quantity: '?'
  target_type: Device
neurodata_type_def: OnePhotonSeries
neurodata_type_inc: ImageSeries

3.12.2. TwoPhotonSeries

Extends: ImageSeries

Description: see Section 2.11.2

YAML Specification:

attributes:
- doc: Photomultiplier gain.
  dtype: float32
  name: pmt_gain
  required: false
- doc: Lines imaged per second. This is also stored in /general/optophysiology but
    is kept here as it is useful information for analysis, and so good to be stored
    w/ the actual data.
  dtype: float32
  name: scan_line_rate
  required: false
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- dims:
  - - width|height
  - - width|height|depth
  doc: Width, height and depth of image, or imaged area, in meters.
  dtype: float32
  name: field_of_view
  quantity: '?'
  shape:
  - - 2
  - - 3
- attributes:
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Base unit of measurement for working with the data. Actual stored values
      are not necessarily stored in these units. To access the data in these units,
      multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - - frame
    - x
    - y
  - - frame
    - x
    - y
    - z
  doc: Binary data representing images across frames. If data are stored in an external
    file, this should be an empty 3D array.
  dtype: numeric
  name: data
  shape:
  - -
    -
    -
  - -
    -
    -
    -
- dims:
  - rank
  doc: Number of pixels on x, y, (and z) axes.
  dtype: int32
  name: dimension
  quantity: '?'
  shape:
  -
- attributes:
  - dims:
    - num_files
    doc: Each external image may contain one or more consecutive frames of the full
      ImageSeries. This attribute serves as an index to indicate which frames each
      file contains, to faciliate random access. The 'starting_frame' attribute, hence,
      contains a list of frame numbers within the full ImageSeries of the first frame
      of each file listed in the parent 'external_file' dataset. Zero-based indexing
      is used (hence, the first element will always be zero). For example, if the
      'external_file' dataset has three paths to files and the first file has 5 frames,
      the second file has 10 frames, and the third file has 20 frames, then this attribute
      will have values [0, 5, 15]. If there is a single external file that holds all
      of the frames of the ImageSeries (and so there is a single element in the 'external_file'
      dataset), then this attribute should have value [0].
    dtype: int32
    name: starting_frame
    shape:
    -
  dims:
  - num_files
  doc: Paths to one or more external file(s). The field is only present if format='external'.
    This is only relevant if the image series is stored in the file system as one
    or more image file(s). This field should NOT be used if the image is stored in
    another NWB file and that file is linked to this file.
  dtype: text
  name: external_file
  quantity: '?'
  shape:
  -
- default_value: raw
  doc: Format of image. If this is 'external', then the attribute 'external_file'
    contains the path information to the image files. If this is 'raw', then the raw
    (single-channel) binary data is stored in the 'data' dataset. If this attribute
    is not present, then the default format='raw' case is assumed.
  dtype: text
  name: format
  quantity: '?'
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: Image stack recorded over time from 2-photon microscope.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
links:
- doc: Link to ImagingPlane object from which this TimeSeries data was generated.
  name: imaging_plane
  target_type: ImagingPlane
- doc: Link to the Device object that was used to capture these images.
  name: device
  quantity: '?'
  target_type: Device
neurodata_type_def: TwoPhotonSeries
neurodata_type_inc: ImageSeries

3.12.3. RoiResponseSeries

Extends: TimeSeries

Description: see Section 2.11.3

YAML Specification:

attributes:
- default_value: no description
  doc: Description of the time series.
  dtype: text
  name: description
  required: false
- default_value: no comments
  doc: Human-readable comments about the TimeSeries. This second descriptive field
    can be used to store additional information, or descriptive information if the
    primary description field is populated with a computer-readable string.
  dtype: text
  name: comments
  required: false
datasets:
- attributes:
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as signed 16-bit integers (int16 range -32,768 to 32,767)
      that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system
      gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition
      values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
    dtype: float32
    name: conversion
    required: false
  - default_value: 0.0
    doc: Scalar to add to the data after scaling by 'conversion' to finalize its coercion
      to the specified 'unit'. Two common examples of this include (a) data stored
      in an unsigned type that requires a shift after scaling to re-center the data,
      and (b) specialized recording devices that naturally cause a scalar offset with
      respect to the true units.
    dtype: float32
    name: offset
    required: false
  - default_value: -1.0
    doc: Smallest meaningful difference between values in data, stored in the specified
      by unit, e.g., the change in value of the least significant bit, or a larger
      number if signal noise is known to be present. If unknown, use -1.0.
    dtype: float32
    name: resolution
    required: false
  - doc: Base unit of measurement for working with the data. Actual stored values
      are not necessarily stored in these units. To access the data in these units,
      multiply 'data' by 'conversion' and add 'offset'.
    dtype: text
    name: unit
  - doc: Optionally describe the continuity of the data. Can be "continuous", "instantaneous",
      or "step". For example, a voltage trace would be "continuous", because samples
      are recorded from a continuous process. An array of lick times would be "instantaneous",
      because the data represents distinct moments in time. Times of image presentations
      would be "step" because the picture remains the same until the next timepoint.
      This field is optional, but is useful in providing information about the underlying
      data. It may inform the way this data is interpreted, the way it is visualized,
      and what analysis methods are applicable.
    dtype: text
    name: continuity
    required: false
  dims:
  - - num_times
  - - num_times
    - num_ROIs
  doc: Signals from ROIs.
  dtype: numeric
  name: data
  shape:
  - -
  - -
    -
- doc: DynamicTableRegion referencing into an ROITable containing information on the
    ROIs stored in this timeseries.
  name: rois
  neurodata_type_inc: DynamicTableRegion
- attributes:
  - doc: Sampling rate, in Hz.
    dtype: float32
    name: rate
  - doc: Unit of measurement for time, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  doc: Timestamp of the first sample in seconds. When timestamps are uniformly spaced,
    the timestamp of the first sample can be specified and all subsequent ones calculated
    from the sampling rate attribute.
  dtype: float64
  name: starting_time
  quantity: '?'
- attributes:
  - doc: Value is '1'
    dtype: int32
    name: interval
    value: 1
  - doc: Unit of measurement for timestamps, which is fixed to 'seconds'.
    dtype: text
    name: unit
    value: seconds
  dims:
  - num_times
  doc: Timestamps for samples stored in data, in seconds, relative to the common experiment
    master-clock stored in NWBFile.timestamps_reference_time.
  dtype: float64
  name: timestamps
  quantity: '?'
  shape:
  -
- dims:
  - num_times
  doc: Numerical labels that apply to each time point in data for the purpose of querying
    and slicing data by these values. If present, the length of this array should
    be the same size as the first dimension of data.
  dtype: uint8
  name: control
  quantity: '?'
  shape:
  -
- dims:
  - num_control_values
  doc: Description of each control value. Must be present if control is present. If
    present, control_description[0] should describe time points where control == 0.
  dtype: text
  name: control_description
  quantity: '?'
  shape:
  -
doc: ROI responses over an imaging plane. The first dimension represents time. The
  second dimension, if present, represents ROIs.
groups:
- doc: Lab-specific time and sync information as provided directly from hardware devices
    and that is necessary for aligning all acquired time information to a common timebase.
    The timestamp array stores time in the common timebase. This group will usually
    only be populated in TimeSeries that are stored external to the NWB file, in files
    storing raw data. Once timestamp data is calculated, the contents of 'sync' are
    mostly for archival purposes.
  name: sync
  quantity: '?'
neurodata_type_def: RoiResponseSeries
neurodata_type_inc: TimeSeries

3.12.4. DfOverF

Extends: NWBDataInterface

Description: see Section 2.11.4

YAML Specification:

default_name: DfOverF
doc: dF/F information about a region of interest (ROI). Storage hierarchy of dF/F
  should be the same as for segmentation (i.e., same names for ROIs and for image
  planes).
groups:
- doc: RoiResponseSeries object(s) containing dF/F for a ROI.
  neurodata_type_inc: RoiResponseSeries
  quantity: +
neurodata_type_def: DfOverF
neurodata_type_inc: NWBDataInterface

3.12.5. Fluorescence

Extends: NWBDataInterface

Description: see Section 2.11.5

YAML Specification:

default_name: Fluorescence
doc: Fluorescence information about a region of interest (ROI). Storage hierarchy
  of fluorescence should be the same as for segmentation (ie, same names for ROIs
  and for image planes).
groups:
- doc: RoiResponseSeries object(s) containing fluorescence data for a ROI.
  neurodata_type_inc: RoiResponseSeries
  quantity: +
neurodata_type_def: Fluorescence
neurodata_type_inc: NWBDataInterface

3.12.6. ImageSegmentation

Extends: NWBDataInterface

Description: see Section 2.11.6

YAML Specification:

default_name: ImageSegmentation
doc: Stores pixels in an image that represent different regions of interest (ROIs)
  or masks. All segmentation for a given imaging plane is stored together, with storage
  for multiple imaging planes (masks) supported. Each ROI is stored in its own subgroup,
  with the ROI group containing both a 2D mask and a list of pixels that make up this
  mask. Segments can also be used for masking neuropil. If segmentation is allowed
  to change with time, a new imaging plane (or module) is required and ROI names should
  remain consistent between them.
groups:
- doc: Results from image segmentation of a specific imaging plane.
  neurodata_type_inc: PlaneSegmentation
  quantity: +
neurodata_type_def: ImageSegmentation
neurodata_type_inc: NWBDataInterface

3.12.7. PlaneSegmentation

Extends: DynamicTable

Description: see Section 2.11.7

YAML Specification:

attributes:
- dims:
  - num_columns
  doc: The names of the columns in this table. This should be used to specify an order
    to the columns.
  dtype: text
  name: colnames
  shape:
  -
- doc: Description of what is in this dynamic table.
  dtype: text
  name: description
datasets:
- dims:
  - - num_roi
    - num_x
    - num_y
  - - num_roi
    - num_x
    - num_y
    - num_z
  doc: ROI masks for each ROI. Each image mask is the size of the original imaging
    plane (or volume) and members of the ROI are finite non-zero.
  name: image_mask
  neurodata_type_inc: VectorData
  quantity: '?'
  shape:
  - -
    -
    -
  - -
    -
    -
    -
- doc: Index into pixel_mask.
  name: pixel_mask_index
  neurodata_type_inc: VectorIndex
  quantity: '?'
- doc: 'Pixel masks for each ROI: a list of indices and weights for the ROI. Pixel
    masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation'
  dtype:
  - doc: Pixel x-coordinate.
    dtype: uint32
    name: x
  - doc: Pixel y-coordinate.
    dtype: uint32
    name: y
  - doc: Weight of the pixel.
    dtype: float32
    name: weight
  name: pixel_mask
  neurodata_type_inc: VectorData
  quantity: '?'
- doc: Index into voxel_mask.
  name: voxel_mask_index
  neurodata_type_inc: VectorIndex
  quantity: '?'
- doc: 'Voxel masks for each ROI: a list of indices and weights for the ROI. Voxel
    masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation'
  dtype:
  - doc: Voxel x-coordinate.
    dtype: uint32
    name: x
  - doc: Voxel y-coordinate.
    dtype: uint32
    name: y
  - doc: Voxel z-coordinate.
    dtype: uint32
    name: z
  - doc: Weight of the voxel.
    dtype: float32
    name: weight
  name: voxel_mask
  neurodata_type_inc: VectorData
  quantity: '?'
- dims:
  - num_rows
  doc: Array of unique identifiers for the rows of this dynamic table.
  dtype: int
  name: id
  neurodata_type_inc: ElementIdentifiers
  shape:
  -
- doc: Vector columns, including index columns, of this dynamic table.
  neurodata_type_inc: VectorData
  quantity: '*'
doc: Results from image segmentation of a specific imaging plane.
groups:
- doc: Image stacks that the segmentation masks apply to.
  groups:
  - doc: One or more image stacks that the masks apply to (can be one-element stack).
    neurodata_type_inc: ImageSeries
    quantity: '*'
  name: reference_images
links:
- doc: Link to ImagingPlane object from which this data was generated.
  name: imaging_plane
  target_type: ImagingPlane
neurodata_type_def: PlaneSegmentation
neurodata_type_inc: DynamicTable

3.12.8. ImagingPlane

Extends: NWBContainer

Description: see Section 2.11.8

YAML Specification:

datasets:
- doc: Description of the imaging plane.
  dtype: text
  name: description
  quantity: '?'
- doc: Excitation wavelength, in nm.
  dtype: float32
  name: excitation_lambda
- doc: Rate that images are acquired, in Hz. If the corresponding TimeSeries is present,
    the rate should be stored there instead.
  dtype: float32
  name: imaging_rate
  quantity: '?'
- doc: Calcium indicator.
  dtype: text
  name: indicator
- doc: Location of the imaging plane. Specify the area, layer, comments on estimation
    of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names
    for anatomical regions when possible.
  dtype: text
  name: location
- attributes:
  - default_value: 1.0
    doc: Scalar to multiply each element in data to convert it to the specified 'unit'.
      If the data are stored in acquisition system units or other units that require
      a conversion to be interpretable, multiply the data by 'conversion' to convert
      the data to the specified 'unit'. e.g. if the data acquisition system stores
      values in this object as pixels from x = -500 to 499, y = -500 to 499 that correspond
      to a 2 m x 2 m range, then the 'conversion' multiplier to get from raw data
      acquisition pixel units to meters is 2/1000.
    dtype: float32
    name: conversion
    required: false
  - default_value: meters
    doc: Base unit of measurement for working with the data. The default value is
      'meters'.
    dtype: text
    name: unit
    required: false
  dims:
  - - height
    - width
    - x, y, z
  - - height
    - width
    - depth
    - x, y, z
  doc: DEPRECATED Physical position of each pixel. 'xyz' represents the position of
    the pixel relative to the defined coordinate space. Deprecated in favor of origin_coords
    and grid_spacing.
  dtype: float32
  name: manifold
  quantity: '?'
  shape:
  - -
    -
    - 3
  - -
    -
    -
    - 3
- attributes:
  - default_value: meters
    doc: Measurement units for origin_coords. The default value is 'meters'.
    dtype: text
    name: unit
    required: false
  dims:
  - - x, y
  - - x, y, z
  doc: Physical location of the first element of the imaging plane (0, 0) for 2-D
    data or (0, 0, 0) for 3-D data. See also reference_frame for what the physical
    location is relative to (e.g., bregma).
  dtype: float32
  name: origin_coords
  quantity: '?'
  shape:
  - - 2
  - - 3
- attributes:
  - default_value: meters
    doc: Measurement units for grid_spacing. The default value is 'meters'.
    dtype: text
    name: unit
    required: false
  dims:
  - - x, y
  - - x, y, z
  doc: Space between pixels in (x, y) or voxels in (x, y, z) directions, in the specified
    unit. Assumes imaging plane is a regular grid. See also reference_frame to interpret
    the grid.
  dtype: float32
  name: grid_spacing
  quantity: '?'
  shape:
  - - 2
  - - 3
- doc: Describes reference frame of origin_coords and grid_spacing. For example, this
    can be a text description of the anatomical location and orientation of the grid
    defined by origin_coords and grid_spacing or the vectors needed to transform or
    rotate the grid to a common anatomical axis (e.g., AP/DV/ML). This field is necessary
    to interpret origin_coords and grid_spacing. If origin_coords and grid_spacing
    are not present, then this field is not required. For example, if the microscope
    takes 10 x 10 x 2 images, where the first value of the data matrix (index (0,
    0, 0)) corresponds to (-1.2, -0.6, -2) mm relative to bregma, the spacing between
    pixels is 0.2 mm in x, 0.2 mm in y and 0.5 mm in z, and larger numbers in x means
    more anterior, larger numbers in y means more rightward, and larger numbers in
    z means more ventral, then enter the following -- origin_coords = (-1.2, -0.6,
    -2) grid_spacing = (0.2, 0.2, 0.5) reference_frame = "Origin coordinates are relative
    to bregma. First dimension corresponds to anterior-posterior axis (larger index
    = more anterior). Second dimension corresponds to medial-lateral axis (larger
    index = more rightward). Third dimension corresponds to dorsal-ventral axis (larger
    index = more ventral)."
  dtype: text
  name: reference_frame
  quantity: '?'
doc: An imaging plane and its metadata.
groups:
- doc: An optical channel used to record from an imaging plane.
  neurodata_type_inc: OpticalChannel
  quantity: +
links:
- doc: Link to the Device object that was used to record from this electrode.
  name: device
  target_type: Device
neurodata_type_def: ImagingPlane
neurodata_type_inc: NWBContainer

3.12.9. OpticalChannel

Extends: NWBContainer

Description: see Section 2.11.9

YAML Specification:

datasets:
- doc: Description or other notes about the channel.
  dtype: text
  name: description
- doc: Emission wavelength for channel, in nm.
  dtype: float32
  name: emission_lambda
doc: An optical channel used to record from an imaging plane.
neurodata_type_def: OpticalChannel
neurodata_type_inc: NWBContainer

3.12.10. MotionCorrection

Extends: NWBDataInterface

Description: see Section 2.11.10

YAML Specification:

default_name: MotionCorrection
doc: 'An image stack where all frames are shifted (registered) to a common coordinate
  system, to account for movement and drift between frames. Note: each frame at each
  point in time is assumed to be 2-D (has only x & y dimensions).'
groups:
- doc: Reuslts from motion correction of an image stack.
  neurodata_type_inc: CorrectedImageStack
  quantity: +
neurodata_type_def: MotionCorrection
neurodata_type_inc: NWBDataInterface

3.12.11. CorrectedImageStack

Extends: NWBDataInterface

Description: see Section 2.11.11

YAML Specification:

doc: Reuslts from motion correction of an image stack.
groups:
- doc: Image stack with frames shifted to the common coordinates.
  name: corrected
  neurodata_type_inc: ImageSeries
- doc: Stores the x,y delta necessary to align each frame to the common coordinates,
    for example, to align each frame to a reference image.
  name: xy_translation
  neurodata_type_inc: TimeSeries
links:
- doc: Link to ImageSeries object that is being registered.
  name: original
  target_type: ImageSeries
neurodata_type_def: CorrectedImageStack
neurodata_type_inc: NWBDataInterface

3.13. Retinotopy

This source module contains neurodata_type for retinotopy data.

3.13.1. ImagingRetinotopy

Extends: NWBDataInterface

Description: see Section 2.12.1

YAML Specification:

datasets:
- attributes:
  - dims:
    - num_rows, num_cols
    doc: 'Number of rows and columns in the image. NOTE: row, column representation
      is equivalent to height, width.'
    dtype: int32
    name: dimension
    shape:
    - 2
  - dims:
    - height, width
    doc: Size of viewing area, in meters.
    dtype: float32
    name: field_of_view
    shape:
    - 2
  - doc: Unit that axis data is stored in (e.g., degrees).
    dtype: text
    name: unit
  dims:
  - num_rows
  - num_cols
  doc: Phase response to stimulus on the first measured axis.
  dtype: float32
  name: axis_1_phase_map
  shape:
  -
  -
- attributes:
  - dims:
    - num_rows, num_cols
    doc: 'Number of rows and columns in the image. NOTE: row, column representation
      is equivalent to height, width.'
    dtype: int32
    name: dimension
    shape:
    - 2
  - dims:
    - height, width
    doc: Size of viewing area, in meters.
    dtype: float32
    name: field_of_view
    shape:
    - 2
  - doc: Unit that axis data is stored in (e.g., degrees).
    dtype: text
    name: unit
  dims:
  - num_rows
  - num_cols
  doc: Power response on the first measured axis. Response is scaled so 0.0 is no
    power in the response and 1.0 is maximum relative power.
  dtype: float32
  name: axis_1_power_map
  quantity: '?'
  shape:
  -
  -
- attributes:
  - dims:
    - num_rows, num_cols
    doc: 'Number of rows and columns in the image. NOTE: row, column representation
      is equivalent to height, width.'
    dtype: int32
    name: dimension
    shape:
    - 2
  - dims:
    - height, width
    doc: Size of viewing area, in meters.
    dtype: float32
    name: field_of_view
    shape:
    - 2
  - doc: Unit that axis data is stored in (e.g., degrees).
    dtype: text
    name: unit
  dims:
  - num_rows
  - num_cols
  doc: Phase response to stimulus on the second measured axis.
  dtype: float32
  name: axis_2_phase_map
  shape:
  -
  -
- attributes:
  - dims:
    - num_rows, num_cols
    doc: 'Number of rows and columns in the image. NOTE: row, column representation
      is equivalent to height, width.'
    dtype: int32
    name: dimension
    shape:
    - 2
  - dims:
    - height, width
    doc: Size of viewing area, in meters.
    dtype: float32
    name: field_of_view
    shape:
    - 2
  - doc: Unit that axis data is stored in (e.g., degrees).
    dtype: text
    name: unit
  dims:
  - num_rows
  - num_cols
  doc: Power response on the second measured axis. Response is scaled so 0.0 is no
    power in the response and 1.0 is maximum relative power.
  dtype: float32
  name: axis_2_power_map
  quantity: '?'
  shape:
  -
  -
- dims:
  - axis_1, axis_2
  doc: Two-element array describing the contents of the two response axis fields.
    Description should be something like ['altitude', 'azimuth'] or '['radius', 'theta'].
  dtype: text
  name: axis_descriptions
  shape:
  - 2
- attributes:
  - doc: Number of bits used to represent each value. This is necessary to determine
      maximum (white) pixel value.
    dtype: int32
    name: bits_per_pixel
  - dims:
    - num_rows, num_cols
    doc: 'Number of rows and columns in the image. NOTE: row, column representation
      is equivalent to height, width.'
    dtype: int32
    name: dimension
    shape:
    - 2
  - dims:
    - height, width
    doc: Size of viewing area, in meters.
    dtype: float32
    name: field_of_view
    shape:
    - 2
  - doc: Focal depth offset, in meters.
    dtype: float32
    name: focal_depth
  - doc: Format of image. Right now only 'raw' is supported.
    dtype: text
    name: format
  dims:
  - num_rows
  - num_cols
  doc: 'Gray-scale image taken with same settings/parameters (e.g., focal depth, wavelength)
    as data collection. Array format: [rows][columns].'
  dtype: uint16
  name: focal_depth_image
  quantity: '?'
  shape:
  -
  -
- attributes:
  - dims:
    - num_rows, num_cols
    doc: 'Number of rows and columns in the image. NOTE: row, column representation
      is equivalent to height, width.'
    dtype: int32
    name: dimension
    shape:
    - 2
  - dims:
    - height, width
    doc: Size of viewing area, in meters.
    dtype: float32
    name: field_of_view
    shape:
    - 2
  dims:
  - num_rows
  - num_cols
  doc: Sine of the angle between the direction of the gradient in axis_1 and axis_2.
  dtype: float32
  name: sign_map
  quantity: '?'
  shape:
  -
  -
- attributes:
  - doc: Number of bits used to represent each value. This is necessary to determine
      maximum (white) pixel value
    dtype: int32
    name: bits_per_pixel
  - dims:
    - num_rows, num_cols
    doc: 'Number of rows and columns in the image. NOTE: row, column representation
      is equivalent to height, width.'
    dtype: int32
    name: dimension
    shape:
    - 2
  - dims:
    - height, width
    doc: Size of viewing area, in meters.
    dtype: float32
    name: field_of_view
    shape:
    - 2
  - doc: Format of image. Right now only 'raw' is supported.
    dtype: text
    name: format
  dims:
  - num_rows
  - num_cols
  doc: 'Gray-scale anatomical image of cortical surface. Array structure: [rows][columns]'
  dtype: uint16
  name: vasculature_image
  shape:
  -
  -
default_name: ImagingRetinotopy
doc: 'Intrinsic signal optical imaging or widefield imaging for measuring retinotopy.
  Stores orthogonal maps (e.g., altitude/azimuth; radius/theta) of responses to specific
  stimuli and a combined polarity map from which to identify visual areas. This group
  does not store the raw responses imaged during retinotopic mapping or the stimuli
  presented, but rather the resulting phase and power maps after applying a Fourier
  transform on the averaged responses. Note: for data consistency, all images and
  arrays are stored in the format [row][column] and [row, col], which equates to [y][x].
  Field of view and dimension arrays may appear backward (i.e., y before x).'
neurodata_type_def: ImagingRetinotopy
neurodata_type_inc: NWBDataInterface