Noise-induced phase transitions in neuronal networks

TL;DR

This paper demonstrates that increasing shot noise in a cortical neuronal network model induces various phase transitions, including oscillations and avalanches, revealing complex non-equilibrium behaviors similar to biological neurons.

Contribution

It provides an exactly solvable model showing how shot noise causes phase transitions and oscillations in neuronal networks, linking noise intensity to network dynamics.

Findings

Shot noise induces first- and second-order phase transitions.

Network exhibits bursts and avalanches of activity.

Sustained oscillations arise via bifurcations.

Abstract

Using an exactly solvable cortical model of a neuronal network, we show that, by increasing the intensity of shot noise (flow of random spikes bombarding neurons), the network undergoes first- and second-order non-equilibrium phase transitions. We study the nature of the transitions, bursts and avalanches of neuronal activity. Saddle-node and supercritical Hopf bifurcations are the mechanisms of emergence of sustained network oscillations. We show that the network stimulated by shot noise behaves similar to the Morris-Lecar model of a biological neuron stimulated by an applied current.