Rethinking behavior in the light of evolution

Abstract: In psychology and neuroscience, the human brain is usually described as an information processing system that encodes and manipulates representations of knowledge to produce plans of action. This view leads to a decomposition of brain functions into putative processes such as object recognition, memory, decision-making, action planning, etc., inspiring the search for the neural correlates of these processes. However, neurophysiological data does not support many of the predictions of these classic subdivisions.

Neural and behavioral signatures of resource limitations in visual speed perception

Bayesian inference is an elegant theoretical framework for understanding the characteristic biases and discrimination thresholds in visual speed perception. However, the framework is difficult to validate due to its flexibility and the fact that suitable constraints on the structure of thessensory uncertainty have been missing.

Integration of Personal vs. Social Information for Sustainable Decisions on Climate Action

Some of my past and current research looks at "decisions from  experience,” i.e., decisions based on the personally experienced outcomes of past choices, along the lines of reinforcement learning models and how such learning and updating is related to and differs from the way in which people and other intelligent agents use other sources of information, e.g., vicarious feedback (anecdotal/social and/or in the form of statistical distributions of outcomes) or science- or model-based outcome predictions to make “decisions from description.”  What happens when these different sources of foreca

CANCELLED - Statistical inference in auditory perception

The brain’s ability to extract statistical regularities from sound is an important tool in auditory scene analysis, necessary for object recognition, structural learning (in speech or music), texture perception, and novel event detection. In this talk, we explore perceptual, neural and computational principles underlying the brain’s ability to collect complex and non-deterministic patterns in echoic memory. These processes underlie statistical inference in auditory perception and guide our ability to delineate salient changes in our acoustic environment.

Neuronal encoding of vocal signals in a high-level auditory area

Sensitivity to the sequential structure and acoustic variations of communication sounds is fundamental not only for language comprehension in humans but also for song recognition in songbirds. Whether and how the auditory system processes fine variations in the temporal and acoustic features remains poorly understood. By quantifying single-unit responses, we investigate whether neurons in a high‑ level auditory area in zebra finches, a songbird species, are sensitive to the ordering of birdsong elements and to their acoustic variations.

Different neural circuits for perception and visual confidence

La métacognition, c'est-à-dire la capacité de réfléchir à nos propres pensées et processus mentaux, est essentielle pour l'apprentissage et la communication. Un des aspects de la métacognition est la confiance dans nos décisions, ce sentiment étant une bonne prédiction de leurs exactitudes. Cela s’applique également pour les décisions dites « perceptives », comme les décisions visuelles.

What happens when our brain imagines music?

Dans des travaux précédents, les scientifiques avaient constaté que les attentes et les prédictions de notre cerveau concernant la musique jouaient un rôle clé dans la façon dont nous l'apprécions et la ressentons. En effet, pour chaque note entendue notre cerveau produit une réponse reflétant l’attente de l'auditeur, il produira une réponse neuronale moins importante pour les sons attendus et évidents que pour les sons compliqués et surprenants.

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