Influence of autapses on synchronisation in neural networks with chemical synapses

TL;DR

This study investigates how autapses influence synchronization in neural networks with chemical synapses, revealing that autapses affect synchronous and desynchronous activities depending on synapse type and network composition.

Contribution

It introduces a model of neural networks with autapses and analyzes their impact on synchronization, highlighting the role of autapses in neural dynamics.

Findings

Autapses influence synchronization patterns in neural networks.

Synchronization depends on synapse type (excitatory or inhibitory).

Networks exhibit both synchronous and desynchronous activities with autapses.

Abstract

A great deal of research has been devoted on the investigation of neural dynamics in various network topologies. However, only a few studies have focused on the influence of autapses, synapses from a neuron onto itself via closed loops, on neural synchronisation. Here, we build a random network with adaptive exponential integrate-and-fire neurons coupled with chemical synapses, equipped with autapses, to study the effect of the latter on synchronous behaviour. We consider time delay in the conductance of the pre-synaptic neuron for excitatory and inhibitory connections. Interestingly, in neural networks consisting of both excitatory and inhibitory neurons, we uncover that synchronous behaviour depends on their synapse type. Our results provide evidence on the synchronous and desynchronous activities that emerge in random neural networks with chemical, inhibitory and excitatory synapses where neurons are equipped with autapses.