# Functional importance of noise in neuronal information processing

## TL;DR

This paper reviews how noise influences neuronal information processing, highlighting stochastic resonance as a beneficial mechanism and discussing recent biophysical model research and future directions.

## Contribution

It provides a comprehensive review of neuronal stochastic resonance, emphasizing its functional role and recent advances in biophysical modeling and regulation mechanisms.

## Key findings

- Noise can enhance weak signal detection via stochastic resonance
- Recent models elucidate mechanisms of neuronal stochastic resonance
- Open questions highlight future research directions

## Abstract

Noise is an inherent part of neuronal dynamics, and thus of the brain. It can be observed in neuronal activity at different spatiotemporal scales, including in neuronal membrane potentials, local field potentials, electroencephalography, and magnetoencephalography. A central research topic in contemporary neuroscience is to elucidate the functional role of noise in neuronal information processing. Experimental studies have shown that a suitable level of noise may enhance the detection of weak neuronal signals by means of stochastic resonance. In response, theoretical research, based on the theory of stochastic processes, nonlinear dynamics, and statistical physics, has made great strides in elucidating the mechanism and the many benefits of stochastic resonance in neuronal systems. In this perspective, we review recent research dedicated to neuronal stochastic resonance in biophysical mathematical models. We also explore the regulation of neuronal stochastic resonance, and we outline important open questions and directions for future research. A deeper understanding of neuronal stochastic resonance may afford us new insights into the highly impressive information processing in the brain.