Synchronization in a small-world network of non-identical Chialvo neurons

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. In this work, we study synchronization in a small-world network of non-identical Chialvo neurons that are electrically coupled. We introduce a mismatch in one of the model parameters to construct non-identical neurons. 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.