Intermittent cluster synchronization in a unidirectional ring of bursting neurons

TL;DR

This paper uncovers a new intermittent cluster synchronization mechanism in a ring of bursting neurons that leads to extreme events, with potential implications for understanding complex neural dynamics and emergent phenomena.

Contribution

It introduces the concept of intermittent cluster synchronization as a precursor to extreme events in neural networks, supported by analysis of phase transitions and statistical distributions.

Findings

Extreme events originate during intermittent phase synchronization.

Distribution of maxima shows a long-tailed non-Gaussian pattern.

Intermittent synchronization becomes less frequent with more initial clusters.

Abstract

We report a new mechanism through which extreme events with a dragon king-like distribution emerge in a network of unidirectional ring of Hindmarsh-Rose bursting neurons interacting through chemical synapses. We establish and substantiate the fact that depending on the choice of initial conditions, the neurons are divided into different clusters. These clusters transit from a phase-locked state (anti-phase) to phase synchronized regime with increasing value of the coupling strength. Before attaining phase synchronization, there exists some regions of the coupling strength where these clusters are phase synchronized intermittently. During such intermittent phase synchronization, extreme events originate in the mean-field of the membrane potential. This mechanism, which we name as intermittent cluster synchronization, is proposed as the new precursor for the generation of emergent extreme events in this system. These results are also true for diffusive coupling (gap junctions). The distribution of the local maxima of the collective observable shows a long tailed non-Gaussian while the interevent interval follows the Weibull distribution. The goodness of fit are corroborated using probability-probability plot and quantile-quantile plot. This intermittent phase synchronization becomes rarer and rarer with the increase in the number of clusters of initial conditions.