brainpy.measure module#

This module aims to provide commonly used analysis methods for simulated neuronal data. You can access them through brainpy.measure.XXX.

cross_correlation(spikes, bin[, dt, numpy, ...])

Calculate cross correlation index between neurons.

voltage_fluctuation(potentials[, numpy, method])

Calculate neuronal synchronization via voltage variance.

matrix_correlation(x, y[, numpy])

Pearson correlation of the lower triagonal of two matrices.

weighted_correlation(x, y, w[, numpy])

Weighted Pearson correlation of two data series.

functional_connectivity(activities[, numpy])

Functional connectivity matrix of timeseries activities.

raster_plot(sp_matrix, times)

Get spike raster plot which displays the spiking activity of a group of neurons over time.

firing_rate(spikes, width[, dt, numpy])

Calculate the mean firing rate over in a neuron group.

unitary_LFP(times, spikes[, spike_type, ...])

A kernel-based method to calculate unitary local field potentials (uLFP) from a network of spiking neurons [1]_.