Eur. Phys. J. Spec. Top. (2022) 231: 4037-4048
https://doi.org/10.1140/epjs/s11734-022-00630-6

Regular Article

Complete synchronization analysis of neocortical network model

¹ Center for Big Data Research in Health, Xijing University, 710123, Xi’an, China
² Xi’an Key Laboratory of Advanced Photo-Electronics Materials and Energy Conversion Device, School of Science, Xijing University, 710123, Xi’an, China
³ Centre for Artificial Intelligence, Chennai Institute of Technology, Chennai, India
⁴ Department of Electronics Techniques, Babylon Technical Institute, Al-Furat Al-Awsat Technical University, 51001, Babylon, Iraq

^c williamchristian@163.com

Received: 27 February 2022
Accepted: 21 June 2022
Published online: 20 July 2022

Abstract

The brain is a complex network consisting of excitatory and inhibitory neurons. The connections between excitatory and inhibitory neurons lead to different dynamical behaviors. The synchronization is a significant behavior among these neurons. In this paper, the synchronization is analyzed by considering a simple neural network model for up-to-down-state oscillation of the cortical network. This neural network model includes a group of excitatory and inhibitory neurons coupled with each other. Synchronization of two neural models is analyzed, and it is revealed that it depends on the coupling of the excitatory neurons rather than the inhibitory ones. The network of neural models is also investigated by considering a one-dimensional and also two-layer structure. The results represent the formation of different dynamical behaviors such as imperfect synchronization, chimera state, and complete synchronization in the networks.