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.


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


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


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.


The list of the first three cumulants of the data.


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