  The presence of synchronized clusters in neuron networks is a hallmark of
information transmission and processing. The methods commonly used to study
cluster synchronization in networks of coupled oscillators ground on
simplifying assumptions, which often neglect key biological features of neuron
networks. Here we propose a general framework to study presence and stability
of synchronous clusters in more realistic models of neuron networks,
characterized by the presence of delays, different kinds of neurons and
synapses. Application of this framework to the directed network of the macaque
cerebral cortex provides an interpretation key to explain known functional
mechanisms emerging from the combination of anatomy and neuron dynamics. The
cluster synchronization analysis is carried out also by changing parameters and
studying bifurcations. Despite some simplifications with respect to the real
network, the obtained results are in good agreement with previously reported
biological data.
