Knowing how much you don't know: a neural organization of uncertainty estimates

Abstract

How we estimate uncertainty is important in decision neuroscience and has wide-ranging implications in basic and clinical neuroscience, from computational models of optimality to ideas on psychopathological disorders including anxiety, depression and schizophrenia. Empirical research in neuroscience, which has been based on divergent theoretical assumptions, has focused on the fundamental question of how uncertainty is encoded in the brain and how it influences behaviour. Here, we integrate several theoretical concepts about uncertainty into a decision-making framework. We conclude that the currently available evidence indicates that distinct neural encoding (including summary statistic-type representations) of uncertainty occurs in distinct neural systems.