Understanding the timing of cognitive processes with a variable rate neural code

Abstract

Cognitive processes all require time, as they universally depend on information transmission between brain regions limited by physical and biological constraints. The time required for behavior also exhibits surprisingly lawful variation with task demands, success and failure, stimulus and response complexity, familiarity, practice and learning. Here we consider these regularities as consequences of constraints on information transmission, which we show provide rational predictions for timing effects across a surprising range of cognitive domains. We use a simple model for neural information transmission based on a variable-length rate coding model built with Poisson processes, Bayesian inference, and an entropybased decision threshold that simultaneously replicates a broad array of well-known reaction-time effects. By providing a principled connection between a high-level normative decision framework with time-dependent neural rate codes, we integrate several disjoint ideas in cognitive science through translating plausible constraints into information theoretic terms.