Suppression of neuronal phase synchronisation in cat cerebral cortex

TL;DR

This study investigates methods to suppress pathological neuronal synchronization in the cat cerebral cortex using simulations of delayed feedback, periodic driving, and neuron activation, finding delayed feedback most effective.

Contribution

It introduces a clustered small-world network model of the cat cortex and compares the effectiveness of three control methods for suppressing neuronal synchronization.

Findings

Delayed feedback control is most effective in suppression.

External periodic driving is less effective.

Neuron activation has limited suppression capability.

Abstract

We have studied effects of perturbations on the cat cerebral cortex. According to the literature, this cortex structure can be described by a clustered network. This way, we construct a clustered network with the same number of areas as in the cat matrix, where each area is described as a sub-network with small-world property. We focus on the suppression of neuronal phase synchronisation considering different kinds of perturbations. Among the various controlling interventions, we choose three methods: delayed feedback control, external time-periodic driving, and activation of selected neurons. We simulate these interventions to provide a procedure to suppress undesired and pathological abnormal rhythms that can be associated with many forms of synchronisation. In our simulations, we have verified that the efficiency of synchronisation suppression by delayed feedback control is higher than external time-periodic driving and activation of selected neurons for the cat cerebral cortex with the same coupling strengths.