elephant.sta.spike_triggered_average(signal, spiketrains, window)[source]

Calculates the spike-triggered averages of analog signals in a time window relative to the spike times of a corresponding spiketrain for multiple signals each. The function receives n analog signals and either one or n spiketrains. In case it is one spiketrain this one is muliplied n-fold and used for each of the n analog signals.

signalneo AnalogSignal object

‘signal’ contains n analog signals.

spiketrainsone SpikeTrain or one numpy ndarray or a list of n of either of these.

‘spiketrains’ contains the times of the spikes in the spiketrains.

windowtuple of 2 Quantity objects with dimensions of time.

‘window’ is the start time and the stop time, relative to a spike, of the time interval for signal averaging. If the window size is not a multiple of the sampling interval of the signal the window will be extended to the next multiple.

result_staneo AnalogSignal object

‘result_sta’ contains the spike-triggered averages of each of the analog signals with respect to the spikes in the corresponding spiketrains. The length of ‘result_sta’ is calculated as the number of bins from the given start and stop time of the averaging interval and the sampling rate of the analog signal. If for an analog signal no spike was either given or all given spikes had to be ignored because of a too large averaging interval, the corresponding returned analog signal has all entries as nan. The number of used spikes and unused spikes for each analog signal are returned as annotations to the returned AnalogSignal object.


>>> signal = neo.AnalogSignal(np.array([signal1, signal2]).T, units='mV',
...                                sampling_rate=10/ms)
>>> stavg = spike_triggered_average(signal, [spiketrain1, spiketrain2],
...                                 (-5 * ms, 10 * ms))