  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.
