Phase synchronization and coexisting attractors in a model of three different neurons coupled via hybrid synapses

Abstract

Resistor(R), Inductor(L) and Capacitor(C) are electronic components used to evaluate the effects of joule heat, magnetic field and electric field respectively. In neuroscience, these components are used to design biological synapses, which allows several biological neurons to be interconnected with each other. In this manuscript, we design a neural network from three distinct neural circuits and different electronic components (RLC). This neural model consists of a photosensitive neuron, an auditory neuron and a heat-sensitive neuron interconnected respectively by a resistor, an inductor and a capacitor. This setup allows to estimate the magnetic field, electric field and the joule heat effect in this neural network. Analyzes on its dynamic model have made it possible to understand that the momentary variation of the various intrinsic parameters of the coupling channels leads the neural circuit to regular (periodic) or irregular (chaotic) behaviors. In addition, we found that it can be sensitive to initial conditions, which explains the phenomenon of coexisting attractors that can arise in this coupled neuron model. In addition, phase synchronization stability can be achieved as the coupling channel parameters increase. This important tool can find its application in the biomedical field for the manufacture of artificial neurons.