SpikeTrain-class: A S4 class to represent the spike trains of one recording...
In kevin-allen/relectro: Analysis of electrophysiological data

Description Slots

This class is used to analyse the spike trains of neurons. You can calculate mean firing rates, instantaneous firing rates, spike-time autocorrelations, spike-time crosscorrelations, crosscorrelation between spike trains and events, etc. You can limit the analysis to some time interval by using the method setInterval. Similarly, you can limit the analysis to some cells with the method setCellList.

session: Name of the recording session
path: Directory where the recording session is located
samplingRate: Sampling rate of the electrophysiological data
res: Spike time in sample value
time: Spike time in seconds
clu: Cluster id for each spike
nCells: Number of cells in the recording session
nSpikes: Number of spikes in the recording session
nSpikesPerCell: Number of spikes for each cell
startInterval: Sample values of the beginning of intervals. To limit the analysis to some intervals. Only data within the intervals are considered
endInterval: Sample values of the end of intervals. Only data within the intervals are considered.
startResIndexc: Index in the spike arrays for the start of intervals. Index is for a C array with 0 indexing. The spike at the index is to be considered for analysis
endResIndexc: Index in the spike arrays for the start of intervals. Index is for a C array with 0 indexing. The spike at the intdex is to be considered for analysis
events: Time in sample number for some events
cellList: Cell list
auto: Matrix holding spike-time autocorrelation
autoMsPerBin: Ms per bin in spike-time autocorrelation
autoTimePoints: Time points for data points in the spike-time autocorrelation
autoProbability: Logical, whether the spike-time autocorrelation contains probability values or spike count
autoCOM: Center of mass of the positive half of each spike-time autocorrelation
cross: Matrix holding spike-time crosscorrelation between spikes and events
crossMsPerBin: Ms per bin in spike-time crosscorrelation with events
crossTimePoints: Time points for data points in the spike-time crosscorrelation
crossProbability: Logical, whether the spike-time crosscorrelation to events contains probability values or spike count
crossEvents: Matrix holding spike-time crosscorrelation between spikes and events
crossEventsMsPerBin: Ms per bin in spike-time crosscorrelation with events
crossEventsTimePoints: Time points for data points in the spike-time crosscorrelation to events
crossEventsProbability: Logical, whether the spike-time crosscorrelation to events contains probability values or spike count
cellPairList: Data frame containing pairs of cells
ifrKernelSdMs: Standard deviation of a gaussian kernel used to calculate the instantaneous firing rate
ifrWindowSizeMs: Window size of the instantaneous firing rate array
ifrSpikeBinMs: Size of the bins in which the number of spikes are counted
ifr: Matrix containing the instantaneous firing rate of the neurons
ifrTime: Time associated with each window of the instantaneous firing rate
meanFiringRate: Mean firing rate of the neurons
isolationDistance: Isolation distance of each cluster
refractoryRatio: Refractory ratio of each cluster
crossRefractoryRatio: Refractory ratio found in the spike-time crosscorrelation between a cluster and all other clusters. The smallest ratio is used.