Soft threshold stochastic resonance

Abstract

Soft thresholds are ubiquitous in living organisms, in particular in mechanisms of neurons and of neural networks such as sensory systems. Which soft threshold functions produce (threshold) stochastic resonance remains a question. The answer may depend on the information measure used. We argue that Fisher information about signal parameters is an attractive measure of information transmission across soft thresholds. We illustrate how the pattern of information changes as a signal moves across a soft threshold. For some signals this pattern is much the same whether Fisher information or signal-to-noise ratio is used as a measure of information transmission. Noninvertibility of the threshold function, rather than its steepness, is important for stochastic resonance measured by Fisher information.