nwb-linkml/nwb_linkml/schema/core.nwb.ecephys.include.yaml

name: core.nwb.ecephys.include
id: core.nwb.ecephys.include
imports:
- core.nwb.base
- hdmf-common.table
- core.nwb.device
- nwb.language
- core.nwb.ecephys.include
- core.nwb.ecephys
default_prefix: core.nwb.ecephys.include/
classes:
  ElectricalSeries__data:
    name: ElectricalSeries__data
    description: Recorded voltage data.
    attributes:
      unit:
        name: unit
        description: 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'.
        range: text
      array:
        name: array
        range: ElectricalSeries__data__Array
  ElectricalSeries__data__Array:
    name: ElectricalSeries__data__Array
    is_a: Arraylike
    attributes:
      num_times:
        name: num_times
        range: numeric
        required: true
      num_channels:
        name: num_channels
        range: numeric
        required: false
      num_samples:
        name: num_samples
        range: numeric
        required: false
  ElectricalSeries__electrodes:
    name: ElectricalSeries__electrodes
    description: DynamicTableRegion pointer to the electrodes that this time series
      was generated from.
    is_a: DynamicTableRegion
  ElectricalSeries__channel_conversion:
    name: ElectricalSeries__channel_conversion
    description: 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.
    attributes:
      axis:
        name: axis
        description: The zero-indexed axis of the 'data' dataset that the channel-specific
          conversion factor corresponds to. This value is fixed to 1.
        range: int32
      channel_conversion:
        name: channel_conversion
        description: 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.
        multivalued: true
        range: float32
        required: false
  SpikeEventSeries__data:
    name: SpikeEventSeries__data
    description: Spike waveforms.
    attributes:
      unit:
        name: unit
        description: Unit of measurement for waveforms, which is fixed to 'volts'.
        range: text
      array:
        name: array
        range: SpikeEventSeries__data__Array
  SpikeEventSeries__data__Array:
    name: SpikeEventSeries__data__Array
    is_a: Arraylike
    attributes:
      num_events:
        name: num_events
        range: numeric
        required: true
      num_samples:
        name: num_samples
        range: numeric
        required: true
      num_channels:
        name: num_channels
        range: numeric
        required: false
  SpikeEventSeries__timestamps:
    name: SpikeEventSeries__timestamps
    description: 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.
    attributes:
      interval:
        name: interval
        description: Value is '1'
        range: int32
      unit:
        name: unit
        description: Unit of measurement for timestamps, which is fixed to 'seconds'.
        range: text
      timestamps:
        name: timestamps
        description: 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.
        multivalued: true
        range: float64
        required: true
  FeatureExtraction__description:
    name: FeatureExtraction__description
    description: Description of features (eg, ''PC1'') for each of the extracted features.
    attributes:
      description:
        name: description
        description: Description of features (eg, ''PC1'') for each of the extracted
          features.
        multivalued: true
        range: text
        required: true
  FeatureExtraction__features:
    name: FeatureExtraction__features
    description: Multi-dimensional array of features extracted from each event.
    attributes:
      array:
        name: array
        range: FeatureExtraction__features__Array
  FeatureExtraction__features__Array:
    name: FeatureExtraction__features__Array
    is_a: Arraylike
    attributes:
      num_events:
        name: num_events
        range: float32
        required: false
      num_channels:
        name: num_channels
        range: float32
        required: false
      num_features:
        name: num_features
        range: float32
        required: false
  FeatureExtraction__times:
    name: FeatureExtraction__times
    description: Times of events that features correspond to (can be a link).
    attributes:
      times:
        name: times
        description: Times of events that features correspond to (can be a link).
        multivalued: true
        range: float64
        required: true
  FeatureExtraction__electrodes:
    name: FeatureExtraction__electrodes
    description: DynamicTableRegion pointer to the electrodes that this time series
      was generated from.
    is_a: DynamicTableRegion
  EventDetection__source_idx:
    name: EventDetection__source_idx
    description: 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.
    attributes:
      source_idx:
        name: source_idx
        description: 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.
        multivalued: true
        range: int32
        required: true
  EventDetection__times:
    name: EventDetection__times
    description: Timestamps of events, in seconds.
    attributes:
      unit:
        name: unit
        description: Unit of measurement for event times, which is fixed to 'seconds'.
        range: text
      times:
        name: times
        description: Timestamps of events, in seconds.
        multivalued: true
        range: float64
        required: true
  ClusterWaveforms__waveform_mean:
    name: ClusterWaveforms__waveform_mean
    description: 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)
    attributes:
      array:
        name: array
        range: ClusterWaveforms__waveform_mean__Array
  ClusterWaveforms__waveform_mean__Array:
    name: ClusterWaveforms__waveform_mean__Array
    is_a: Arraylike
    attributes:
      num_clusters:
        name: num_clusters
        range: float32
        required: false
      num_samples:
        name: num_samples
        range: float32
        required: false
  ClusterWaveforms__waveform_sd:
    name: ClusterWaveforms__waveform_sd
    description: Stdev of waveforms for each cluster, using the same indices as in
      mean
    attributes:
      array:
        name: array
        range: ClusterWaveforms__waveform_sd__Array
  ClusterWaveforms__waveform_sd__Array:
    name: ClusterWaveforms__waveform_sd__Array
    is_a: Arraylike
    attributes:
      num_clusters:
        name: num_clusters
        range: float32
        required: false
      num_samples:
        name: num_samples
        range: float32
        required: false
  Clustering__num:
    name: Clustering__num
    description: Cluster number of each event
    attributes:
      num:
        name: num
        description: Cluster number of each event
        multivalued: true
        range: int32
        required: true
  Clustering__peak_over_rms:
    name: Clustering__peak_over_rms
    description: Maximum ratio of waveform peak to RMS on any channel in the cluster
      (provides a basic clustering metric).
    attributes:
      peak_over_rms:
        name: peak_over_rms
        description: Maximum ratio of waveform peak to RMS on any channel in the cluster
          (provides a basic clustering metric).
        multivalued: true
        range: float32
        required: true
  Clustering__times:
    name: Clustering__times
    description: Times of clustered events, in seconds. This may be a link to times
      field in associated FeatureExtraction module.
    attributes:
      times:
        name: times
        description: Times of clustered events, in seconds. This may be a link to
          times field in associated FeatureExtraction module.
        multivalued: true
        range: float64
        required: true