Nonstationary stochastic resonance viewed through the lens of information theory

TL;DR

This paper develops an analytical information-theoretic framework to quantify nonstationary stochastic resonance in biological spike processes, addressing how signal duration, strength, and noise influence information transfer.

Contribution

It introduces a novel approach using Kullback-Leibler information to analyze nonstationary stochastic resonance in biological systems.

Findings

Quantifies information transfer in nonstationary spike processes.

Analyzes the impact of signal duration and noise on detection.

Provides theoretical insights into stochastic resonance phenomena.

Abstract

In biological systems, information is frequently transferred with Poisson like spike processes (shot noise) modulated in time by information-carrying signals. How then to quantify information transfer for the output for such nonstationary input signals of finite duration? Is there some minimal length of the input signal duration versus its strength? Can such signals be better detected when immersed in noise stemming from the surroundings by increasing the stochastic intensity? These are some basic questions which we attempt to address within an analytical theory based on the Kullback-Leibler information concept applied to random processes.