Synchronization of interacted spiking neuronal networks with inhibitory coupling

The development of mathematical models to describe neuronal interaction processes in the brain is a challenging task of nonlinear dynamics. Recent advances in biochemistry and neuroscience allow better understanding of biological mechanisms underlying the neuron functioning and synaptic connections be-tween neurons. Moreover, significant progress in brain imaging sheds light on the structure of the brain network and certain aspects of neuronal dynamics. However, dynamical mechanisms leading to synchro-nization between different brain areas still remain unknown and require further investigation. To shed light on this issue, we consider two small-world networks of Hodgkin-Huxley neurons interacting via in-hibitory coupling. We found that synchronization indices (SI) in both networks oscillate periodically in time, so that time intervals of high SI alternate with time intervals of low SI. Depending on the coupling strength, the two coupled networks can be in the regime of either in-phase or anti-phase synchroniza-tion. We suppose that the inherent mechanism behind such a behavior lies in the cognitive resource redistribution between neuronal ensembles of the brain. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

Developing mathematical models to describe neuronal interactions in the brain is a challenging task in nonlinear dynamics. Recent advances in biochemistry and neuroscience have improved our understanding of neuron functioning and synaptic connections, but the mechanisms behind synchronization of different brain areas remain unknown and require further investigation.