Rhythmogenesis in the mean field model of the neuron-glial network

TL;DR

This paper introduces a phenomenological mean field model demonstrating how neuron-glial interactions, short-term synaptic plasticity, and recurrent connections can induce bursting activity in neural networks, enhancing understanding of neural dynamics.

Contribution

It presents a novel model explaining bursting activity mechanisms through neuron-glial interactions and bifurcation analysis, advancing neural network dynamics research.

Findings

Neuron-glial interactions can induce bursting activity.

Bifurcation scenarios explain emergence of bursting.

Model enhances understanding of neural network dynamics.

Abstract

Despite the fact that the phenomenon of bursting activity is important for functioning of living neural networks, the mechanisms of its origin are still not clear. In this paper, we propose a new phenomenological model that can explain the mechanisms of the formation of bursting activity based on short-term synaptic plasticity, recurrent connections, and neuron-glial interactions. We show that neuron-glial interactions can induce bursting activity. The bifurcation scenarios of emergence of bursting activity are in the focus of the paper. Proposed study is important for understanding of the complex dynamics in neural networks.