Chimera states in a ring of map-based neurons

Abstract

Chimera state is a simultaneous combination of synchronous and asynchronous environments in a network of identical oscillators, attracts the attention of researchers in the different fields of science. Neuroscientists believe that existing both the synchronous and asynchronous behavior in the brain plays a vital role in brain neuronal activity. As a result, in this paper, we investigate the ability of a neural network to produce chimera. Our focus has been on using a discrete neuronal model which resolve the curse of dimensionality by retraining the complex behavior at the same time. Each neuron is coupled to its neighboring with limited scope. The interdependency of the spatiotemporal dynamic on the coupling strength in a fixed range made the switching process visible, which rises with the appearance of thin bands of incoherence, occupying the whole space ultimately.