Chaos and correlated avalanches in excitatory neural networks with synaptic plasticity

TL;DR

This paper investigates how excitatory neural networks with synaptic plasticity can exhibit chaotic activity and avalanches, revealing a new mechanism for irregular neural dynamics driven by disorder and chaos.

Contribution

It introduces a model showing a collective chaotic phase with avalanches in excitatory neurons, highlighting the role of disorder and synaptic plasticity in neural dynamics.

Findings

Discovery of a chaotic phase with power law avalanches

Identification of phase transitions to bursty regimes

Enhanced complexity and time correlations in activity

Abstract

A collective chaotic phase with power law scaling of activity events is observed in a disordered mean field network of purely excitatory leaky integrate-and-fire neurons with short-term synaptic plasticity. The dynamical phase diagram exhibits two transitions from quasi-synchronous and asynchronous regimes to the nontrivial, collective, bursty regime with avalanches. In the homogeneous case without disorder, the system synchronizes and the bursty behavior is reflected into a doubling-period transition to chaos for a two dimensional discrete map. Numerical simulations show that the bursty chaotic phase with avalanches exhibits a spontaneous emergence of time correlations and enhanced Kolmogorov complexity. Our analysis reveals a mechanism for the generation of irregular avalanches that emerges from the combination of disorder and deterministic underlying chaotic dynamics.