Dynamics and chimera state in a neural network with discrete memristor coupling

• Published in: The European physical journal. ST, Special topics Vol. 231; no. 22-23; pp. 4065 - 4076
• Main Authors: Shang, Chenxi, He, Shaobo, Rajagopal, Karthikeyan, Wang, Huihai, Sun, Kehui
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-12-2022; Springer Nature B.V
• Subjects: Atomic; Classical and Continuum Physics; Collective Behavior of Nonlinear Dynamical Oscillators; Condensed Matter Physics; Coupled modes; Coupling; Materials Science; Measurement Science and Instrumentation; Memristors; Molecular; Neural networks; Neurons; Optical and Plasma Physics; Physics; Physics and Astronomy; Regular Article; Synapses; Synchronism
• ISSN: 1951-6355; 1951-6401
• DOI: 10.1140/epjs/s11734-022-00699-z

Due to characteristics of memristor being highly similar to the principle and structure of synapses in biological brains, memristor neural networks are widely studied. Discrete memristor made it possible to study the discrete memristor neural network. In this paper, the properties of the individual Chialvo neuron are discussed. The synchronization of two neurons through different firing modes coupled with a discrete memristor is studied by changing the coupling gain. A ring neural network is constructed, and two adjacent neurons are connected by a discrete memristor. Synchronization and chimera state in the network are analyzed from the coupling gain and the number of neurons with different firing modes in the network. Simulation results show that discrete memristor plays the role of synapse well and realizes the synchronization of neurons and neural networks.