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(spiketrains, sampling_period) |
Estimates instantaneous firing rate by kernel convolution. |
time_histogram(spiketrains, bin_size[, …]) |
Time Histogram of a list of neo.SpikeTrain objects. |
optimal_kernel_bandwidth(spiketimes[, …]) |
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. |
cv2(time_intervals[, with_nan]) |
Calculate the measure of Cv2 for a sequence of time intervals between events. |
lv(time_intervals[, with_nan]) |
Calculate the measure of local variation Lv for a sequence of time intervals between events. |
lvr(time_intervals[, R, with_nan]) |
Calculate the measure of revised local variation LvR for a sequence of time intervals between events. |
Statistics across spike trains
fanofactor(spiketrains[, warn_tolerance]) |
Evaluates the empirical Fano factor F of the spike counts of a list of neo.SpikeTrain objects. |
complexity_pdf(spiketrains, bin_size) |
Complexity Distribution of a list of neo.SpikeTrain objects. |
