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