Valentin Wyart

7 mai 2021

Laboratoire de Neurosciences Cognitives Département d’Etudes Cognitives, Ecole Normale Supérieure

Computation noise in human learning and decision-making : origin, impact, function

invité par Andrea Brovelli

Résumé :

Making sense of uncertain and volatile environments, a cognitive process modeled across domains as statistical inference, constitutes a difficult yet ubiquitous challenge for human intelligence. Beside sensory errors and exploratory choices, recent research has identified the limited computational precision of cognitive inference as a surprisingly large contributor to the variability and suboptimality of perceptual and reward-guided decisions made under uncertainty. In this talk, I will present and discuss the theoretical and experimental evidence obtained by my group which, taken together, provides key insights into the origin, impact and function of this computation noise for learning and decision-making. Moving beyond the classical description of internal noise as a performance-limiting constraint on neural function and cognition, I will provide preliminary data that delineates the possible emergent benefits of computation noise for adaptive behavior in a range of adverse conditions.

Bios : Valentin Wyart’s research focuses on the neurobiological basis of human decision-making, and relies on a synergistic cross-talk between computational modeling, cognitive psychology and neuroscience to understand how we make decisions (and especially why we make errors) in the face of uncertainty. Vaentin’s research typically combines computational modeling of human choice behavior with multimodal functional neuroimaging.

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