Statistics of spike trains
Statistical measures of spike trains (e.g., Fano factor) and functions to
estimate firing rates.
Functions overview
Rate estimation
mean_firing_rate(spiketrain[, t_start, …]) |
Return the firing rate of the spike train. |
instantaneous_rate(spiketrain, sampling_period) |
Estimates instantaneous firing rate by kernel convolution. |
time_histogram(spiketrains, binsize[, …]) |
Time Histogram of a list of neo.SpikeTrain objects. |
sskernel(spiketimes[, tin, w, bootstrap]) |
Calculates optimal fixed kernel bandwidth, given as the standard deviation sigma. |
Spike interval statistics
isi(spiketrain[, axis]) |
Return an array containing the inter-spike intervals of the spike train. |
cv(a[, axis, nan_policy]) |
Compute the coefficient of variation. |
lv(v[, with_nan]) |
Calculate the measure of local variation LV for a sequence of time intervals between events. |
cv2(v[, with_nan]) |
Calculate the measure of CV2 for a sequence of time intervals between events. |
Statistics across spike trains
fanofactor(spiketrains) |
Evaluates the empirical Fano factor F of the spike counts of a list of neo.SpikeTrain objects. |
complexity_pdf(spiketrains, binsize) |
Complexity Distribution of a list of neo.SpikeTrain objects. |
