nwb.misc.yaml

groups:
- neurodata_type_def: AbstractFeatureSeries
  neurodata_type_inc: TimeSeries
  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.
  datasets:
  - name: data
    dtype: numeric
    dims:
    - - num_times
    - - num_times
      - num_features
    shape:
    - - null
    - - null
      - null
    doc: Values of each feature at each time.
    attributes:
    - name: unit
      dtype: text
      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'".
      required: false
  - name: feature_units
    dtype: text
    dims:
    - num_features
    shape:
    - null
    doc: Units of each feature.
    quantity: '?'
  - name: features
    dtype: text
    dims:
    - num_features
    shape:
    - null
    doc: Description of the features represented in TimeSeries::data.

- neurodata_type_def: AnnotationSeries
  neurodata_type_inc: TimeSeries
  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.
  datasets:
  - name: data
    dtype: text
    dims:
    - num_times
    shape:
    - null
    doc: Annotations made during an experiment.
    attributes:
    - name: resolution
      dtype: float32
      value: -1.0
      doc: Smallest meaningful difference between values in data. Annotations have
        no units, so the value is fixed to -1.0.
    - name: unit
      dtype: text
      value: n/a
      doc: Base unit of measurement for working with the data. Annotations have
        no units, so the value is fixed to 'n/a'.

- neurodata_type_def: IntervalSeries
  neurodata_type_inc: TimeSeries
  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.
  datasets:
  - name: data
    dtype: int8
    dims:
    - num_times
    shape:
    - null
    doc: Use values >0 if interval started, <0 if interval ended.
    attributes:
    - name: resolution
      dtype: float32
      value: -1.0
      doc: Smallest meaningful difference between values in data. Annotations have
        no units, so the value is fixed to -1.0.
    - name: unit
      dtype: text
      value: n/a
      doc: Base unit of measurement for working with the data. Annotations have
        no units, so the value is fixed to 'n/a'.

- neurodata_type_def: DecompositionSeries
  neurodata_type_inc: TimeSeries
  doc: Spectral analysis of a time series, e.g. of an LFP or a speech signal.
  datasets:
  - name: data
    dtype: numeric
    dims:
    - num_times
    - num_channels
    - num_bands
    shape:
    - null
    - null
    - null
    doc: Data decomposed into frequency bands.
    attributes:
    - name: unit
      dtype: text
      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'.
  - name: metric
    dtype: text
    doc: The metric used, e.g. phase, amplitude, power.
  - name: source_channels
    neurodata_type_inc: DynamicTableRegion
    doc: DynamicTableRegion pointer to the channels that this decomposition series was generated from.
    quantity: '?'
  groups:
  - name: bands
    neurodata_type_inc: DynamicTable
    doc: Table for describing the bands that this series was generated from. There
      should be one row in this table for each band.
    datasets:
    - name: band_name
      neurodata_type_inc: VectorData
      dtype: text
      doc: Name of the band, e.g. theta.
    - name: band_limits
      neurodata_type_inc: VectorData
      dtype: float32
      dims:
      - num_bands
      - low, high
      shape:
      - null
      - 2
      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.
    - name: band_mean
      neurodata_type_inc: VectorData
      dtype: float32
      dims:
      - num_bands
      shape:
      - null
      doc: The mean Gaussian filters, in Hz.
      quantity: '?'
    - name: band_stdev
      neurodata_type_inc: VectorData
      dtype: float32
      dims:
      - num_bands
      shape:
      - null
      doc: The standard deviation of Gaussian filters, in Hz.
      quantity: '?'
  links:
  - name: source_timeseries
    target_type: TimeSeries
    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.
    quantity: '?'

- neurodata_type_def: Units
  neurodata_type_inc: DynamicTable
  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.
  datasets:
  - name: spike_times_index
    neurodata_type_inc: VectorIndex
    doc: Index into the spike_times dataset.
    quantity: '?'
  - name: spike_times
    neurodata_type_inc: VectorData
    dtype: float64
    doc: Spike times for each unit in seconds.
    quantity: '?'
    attributes:
    - name: resolution
      dtype: float64
      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.
      required: false
  - name: obs_intervals_index
    neurodata_type_inc: VectorIndex
    doc: Index into the obs_intervals dataset.
    quantity: '?'
  - name: obs_intervals
    neurodata_type_inc: VectorData
    dtype: float64
    dims:
    - num_intervals
    - start|end
    shape:
    - null
    - 2
    doc: Observation intervals for each unit.
    quantity: '?'
  - name: electrodes_index
    neurodata_type_inc: VectorIndex
    doc: Index into electrodes.
    quantity: '?'
  - name: electrodes
    neurodata_type_inc: DynamicTableRegion
    doc: Electrode that each spike unit came from, specified using a DynamicTableRegion.
    quantity: '?'
  - name: electrode_group
    neurodata_type_inc: VectorData
    dtype:
      target_type: ElectrodeGroup
      reftype: object
    doc: Electrode group that each spike unit came from.
    quantity: '?'
  - name: waveform_mean
    neurodata_type_inc: VectorData
    dtype: float32
    dims:
    - - num_units
      - num_samples
    - - num_units
      - num_samples
      - num_electrodes
    shape:
    - - null
      - null
    - - null
      - null
      - null
    doc: Spike waveform mean for each spike unit.
    quantity: '?'
    attributes:
    - name: sampling_rate
      dtype: float32
      doc: Sampling rate, in hertz.
      required: false
    - name: unit
      dtype: text
      value: volts
      doc: Unit of measurement. This value is fixed to 'volts'.
      required: false
  - name: waveform_sd
    neurodata_type_inc: VectorData
    dtype: float32
    dims:
    - - num_units
      - num_samples
    - - num_units
      - num_samples
      - num_electrodes
    shape:
    - - null
      - null
    - - null
      - null
      - null
    doc: Spike waveform standard deviation for each spike unit.
    quantity: '?'
    attributes:
    - name: sampling_rate
      dtype: float32
      doc: Sampling rate, in hertz.
      required: false
    - name: unit
      dtype: text
      value: volts
      doc: Unit of measurement. This value is fixed to 'volts'.
      required: false
  - name: waveforms
    neurodata_type_inc: VectorData
    dtype: numeric
    dims:
      - num_waveforms
      - num_samples
    shape:
      - null
      - null
    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 the same as the order of the electrodes referenced in
      the 'electrodes' column of this table. The number of samples for each waveform must be the same."
    quantity: '?'
    attributes:
      - name: sampling_rate
        dtype: float32
        doc: Sampling rate, in hertz.
        required: false
      - name: unit
        dtype: text
        value: volts
        doc: Unit of measurement. This value is fixed to 'volts'.
        required: false
  - name: waveforms_index
    neurodata_type_inc: VectorIndex
    doc: Index into the 'waveforms' dataset. One value for every spike event. See 'waveforms' for more detail.
    quantity: '?'
  - name: waveforms_index_index
    neurodata_type_inc: VectorIndex
    doc: Index into the 'waveforms_index' dataset. One value for every unit (row in the table). See 'waveforms' for more
      detail.
    quantity: '?'