Collective irregular dynamics in balanced networks of leaky integrate-and-fire neurons

TL;DR

This paper investigates collective irregular dynamics in balanced networks of leaky integrate-and-fire neurons, revealing CID as a distinct thermodynamic phase characterized by stochastic-like single-neuron behavior and collective irregularity.

Contribution

It demonstrates that CID is a genuine thermodynamic phase in LIF networks, expanding understanding of neural network dynamics beyond traditional asynchronous regimes.

Findings

CID is a true thermodynamic phase.

Neural networks exhibit both microscopic stochasticity and collective irregular dynamics.

CID differs fundamentally from asynchronous regimes.

Abstract

We extensively explore networks of weakly unbalanced, leaky integrate-and-fire (LIF) neurons for different coupling strength, connectivity, and by varying the degree of refractoriness, as well as the delay in the spike transmission. We find that the neural network does not only exhibit a microscopic (single-neuron) stochastic-like evolution, but also a collective irregular dynamics (CID). Our analysis is based on the computation of a suitable order parameter, typically used to characterize synchronization phenomena and on a detailed scaling analysis (i.e. simulations of different network sizes). As a result, we can conclude that CID is a true thermodynamic phase, intrinsically different from the standard asynchronous regime.