Dynamics of stochastic integrate-and-fire networks

TL;DR

This paper develops a statistical field theory for stochastic integrate-and-fire neural networks, revealing how spike resets and inhibition influence network stability and activity fluctuations, aligning with experimental observations.

Contribution

It introduces a novel mean field theory with rate-dependent leak for integrate-and-fire networks and analyzes the impact of spike resets and inhibition on network dynamics.

Findings

Bistability between quiescent and active states in networks.

Fluctuations suppress activity due to spike resets.

Inhibition stabilizes network activity across parameter space.

Abstract

The neural dynamics generating sensory, motor, and cognitive functions are commonly understood through field theories for neural population activity. Classic neural field theories are derived from highly simplified models of individual neurons, while biological neurons are highly complex cells. Integrate-and-fire neuron models balance biophysical detail and analytical tractability. Here, we develop a statistical field theory for networks of integrate-and-fire neurons with stochastic spike emission. This reveals an exact mapping to a self-consistent renewal process and a new mean field theory for the activity in these networks. The mean field theory has a rate-dependent leak, approximating the spike-driven resets of the membrane voltage. This gives rise to bistability between quiescent and active states in homogenous and excitatory-inhibitory pulse-coupled networks. The field-theoretic framework also exposes fluctuation corrections to the mean field theory. We find that due to the spike reset, fluctuations suppress activity. We then examine the roles of spike resets and recurrent inhibition in stabilizing network activity. We calculate the phase diagram for inhibitory stabilization and find that an inhibition-stabilized regime occurs in wide regions of parameter space, consistent with experimental reports of inhibitory stabilization in diverse brain regions. Fluctuations narrow the region of inhibitory stabilization, consistent with their role in suppressing activity through spike resets.