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The presence of synchronized clusters in neuron networks is a hallmark ofinformation transmission and processing. The methods commonly used to studycluster synchronization in networks of coupled oscillators ground onsimplifying assumptions, which often neglect key biological features of neuronnetworks. Here we propose a general framework to study presence and stabilityof synchronous clusters in more realistic models of neuron networks,characterized by the presence of delays, different kinds of neurons andsynapses. Application of this framework to the directed network of the macaquecerebral cortex provides an interpretation key to explain known functionalmechanisms emerging from the combination of anatomy and neuron dynamics. Thecluster synchronization analysis is carried out also by changing parameters andstudying bifurcations. Despite some simplifications with respect to the realnetwork, the obtained results are in good agreement with previously reportedbiological data.

Analyzing synchronized clusters in neuron networks