elephant.cubic.cubic

elephant.cubic.cubic(histogram, max_iterations=100, alpha=0.05)[source]

Performs the CuBIC analysis [cubic1] on a population histogram, calculated from a population of spiking neurons.

The null hypothesis H_0: k_3(data)<=k^*_{3,\xi} is iteratively tested with increasing correlation order \xi until it is possible to accept, with a significance level alpha, that \hat{\xi} is the minimum order of correlation necessary to explain the third cumulant k_3(data).

k^*_{3,\xi} is the maximized third cumulant, supposing a Compound Poisson Process (CPP) model for correlated spike trains (see the paper) with maximum order of correlation equal to \xi.

Parameters:
histogramneo.AnalogSignal

The population histogram (count of spikes per time bin) of the entire population of neurons.

max_iterationsint, optional

The maximum number of iterations of the hypothesis test. Corresponds to the \hat{\xi_{\text{max}}} in [cubic1]. If it is not possible to compute the \hat{\xi} before max_iterations iteration, the CuBIC procedure is aborted. Default: 100

alphafloat, optional

The significance level of the hypothesis tests performed. Default: 0.05
Returns:
xi_hatint

The minimum correlation order estimated by CuBIC, necessary to explain the value of the third cumulant calculated from the population.

plist

The ordered list of all the p-values of the hypothesis tests that have been performed. If the maximum number of iteration max_iterations is reached, the last p-value is set to -4.

kappalist

The list of the first three cumulants of the data.

test_abortedbool

Whether the test was aborted because reached the maximum number of iteration, max_iterations.