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.

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 differe

Une affection neurodégénérative héréditaire du système nerveux central

La rééducation du langage avec l'eCALAP : l'utilisation de la psycholinguistique dans la thérapie numérique

Graphic and verbal communication are typically thought to work in very different ways. While speech uses a conventionalized vocabulary that is acquired from children’s environments, drawing is assumed to reflect the articulation of how people see and think, with learning based on “artistic talent.” Yet, research from linguistics and cognitive science upends these assumptions, suggesting that these domains are actually not so distinctive.

Learning and decision making have hitherto been investigated almost exclusively in multicellular neural organisms. Yet, evidence for learning and decision making have been described in single celled organisms : ciliates and slime molds for instance. In this conference, in the first part of my talk, I will focus on decision making in slime molds and explore various frameworks: nutritional geometry, speed versus accuracy trade-off, Weber's law and social influence.

Neural responses and perception of visual inputs strongly depend on the spatial context, i.e., what surrounds a given object or feature. I will discuss our work on developing a visual cortical model based on the hypothesis that neurons represent inputs in a coordinate system that is matched to the statistical structure of images in the natural environment. The model generalizes a nonlinear computation known as normalization, that is ubiquitous in neural processing, and can capture some spatial context effects in cortical neurons.

This is an exciting time for scientists who are interested in cognitive development: there is now a wealth of easily-accessible data that can be used to ask interesting questions about how psychological, neural, and genetic factors affect changes in cognitive functions across the lifespan - and how they differ between individuals. In this talk, I'll describe several studies that apply individual-differences methods to large-scale, sometimes longitudinal datasets that include cognitive and biological information.

L’ingénieur travaillera au sein de l’équipe NeuroPsychologie Interventionnelle (NPI), unité de recherche mixte (INSERM, UPEC, ENS), dirigée par le Prof. Anne-Catherine Bachoud-Lévi, présente sur deux sites :