pyeeg.simulate.JRNetwork.step

JRNetwork.step(P=220, sigma_p=22, history_outs=None)

Advance the network by one integration step.

The coupling matrix is updated from the history of the outputs, then every node receives the external input P plus a fluctuating external input plus the inter-area contributions from the other nodes.

Parameters:

• P (float) – The constant external input to each node.

• sigma_p (float) – The standard deviation of the external input fluctuations.

• history_outs (array_like, optional) – The firing-rate outputs of all nodes up to the current time, used to update the coupling matrix. Shape (N, ntimes).

Returns:

outs – The readout of every node after the step. Shape (N,).

Return type:

ndarray