Sequential Desynchronization in Networks of Spiking Neurons with Partial Reset

TL;DR

This paper introduces a neuron model with partial reset after spiking, revealing a novel sequential desynchronization mechanism in neural networks that transitions from synchronized clusters to complete asynchrony.

Contribution

It analytically demonstrates a new desynchronization process driven by partial reset strength in coupled spiking neurons, expanding understanding of neural network dynamics.

Findings

Partial reset induces sequential desynchronization in neuron networks.

Increasing reset strength causes bifurcations from synchronized to asynchronous states.

Mechanism has implications for understanding neural synchronization phenomena.

Abstract

The response of a neuron to synaptic input strongly depends on whether or not it has just emitted a spike. We propose a neuron model that after spike emission exhibits a partial response to residual input charges and study its collective network dynamics analytically. We uncover a novel desynchronization mechanism that causes a sequential desynchronization transition: In globally coupled neurons an increase in the strength of the partial response induces a sequence of bifurcations from states with large clusters of synchronously firing neurons, through states with smaller clusters to completely asynchronous spiking. We briefly discuss key consequences of this mechanism for more general networks of biophysical neurons.