Mutual synchronization in ensembles of globally coupled neural networks

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Abstract
The collective dynamics in globally coupled ensembles of identical neural networks with random asymmetric synaptic connections is investigated. We find that this system shows a spontaneous synchronization transition, i.e., networks with synchronous activity patterns appear in the ensemble when the coupling intensity exceeds a threshold. Under further increase of the coupling: intensity, the entire ensemble breaks down into a number of coherent clusters, until complete mutual synchronization is eventually established.