Impact of Network Heterogeneity on Neuronal Synchronization

TL;DR

This study investigates how network heterogeneity, noise, and connection types influence neuronal synchronization in small-world networks of non-identical neurons, revealing critical factors for effective synchronization relevant to brain function and disorders.

Contribution

It introduces a parameter mismatch to model heterogeneity and analyzes its impact on synchronization, providing new insights into the mechanisms of neuronal network dynamics.

Findings

Critical noise levels facilitate synchronization

Parameter mismatch affects synchronization thresholds

Balance of excitatory and inhibitory connections is crucial

Abstract

Synchronization dynamics is a phenomenon of great interest in many fields of science. One of the most important fields is neuron dynamics, as synchronization in certain regions of the brain is related to some of the most common mental illnesses. To study the impact of the network heterogeneity in the neuronal synchronization, we analyze a small-world network of non-identical Chialvo neurons that are electrically coupled. We introduce a mismatch in one of the model parameters to introduce the heterogeneity of the network. Our study examines the effects of this parameter mismatch, the noise intensity in the stochastic model, and the coupling strength between neurons on synchronization and firing frequency. We have identified critical values of noise intensity, parameter mismatch, and rewiring probability that facilitate effective synchronization within the network. Furthermore, we observe that the balance between excitatory and inhibitory connections plays a crucial role in achieving global synchronization. Our findings offer insights into the mechanisms driving synchronization dynamics in complex neuron networks.