The silencing of neuronal activity by noise and the phenomenon of inverse stochastic resonance

TL;DR

This paper introduces the concept of inverse stochastic resonance, where noise suppresses neuronal activity instead of enhancing it, revealing a novel nonlinear response in neurons and other dynamical systems.

Contribution

It demonstrates that noise can inhibit neuronal firing and rhythmic activity, a counterintuitive phenomenon supported by modeling and experimental data.

Findings

Noise can suppress neuronal activity in models and experiments.

Inverse stochastic resonance occurs at specific noise levels.

Suppression phenomena may apply to various nonlinear systems.

Abstract

Neurons in the central nervous system are affected by complex and noisy signals due to fluctuations in their cellular environment and in the inputs they receive from many other cells 1,2. Such noise usually increases the probability that a neuron will send out a signal to its target cells 2-5. In stochastic resonance, which occurs in many physical and biological systems, an optimal response is found at a particular noise amplitude 6-9. We have found that in a classical neuronal model the opposite can occur - that noise can subdue or turn off repetitive neuronal activity in both single cells and networks of cells. Recent experiments on regularly firing neurons with noisy inputs confirm these predictions 10,11. Surprisingly, we find that in some cases there is a noise level at which the response is a minimum, a phenomenon which is called inverse stochastic resonance. Suppression of rhythmic behavior by noise and inverse stochastic resonance are predicted to occur not only in neuronal systems but more generally in diverse nonlinear dynamical systems where a stable limit cycle is attainable from a stable rest state.