I am a PhD student at the Laboratoire de Neurosciences Cognitives et Computationnelles in the Human Reinforcement Learning team (Ecole normale supérieure, Paris, France).
I received a bachelor’s degree in fundamental mathematics and a master’s degree in cellular neuroscience from the Université Pierre et Marie Curie (Paris 6). My current work in cognitive neuroscience involves computational applications in value-based decision-making.
I am interested in the different strategies we use to make decisions, their inter-individual variability, and the neuropathologies emerging from their dysfunction.
Paris Computational Psychiatry Symposium
Dates to be announced
2021 Bavard S, Rustichini A, Palminteri S. Two sides of the same coin: beneficial and detrimental consequences of range adaptation in human reinforcement learning. Science Advances, 7, eabe0340
2019 Lebreton M, Bavard S, Daunizeau J, Palminteri S. Assessing inter-individual differences with task-related functional neuroimaging. Nature Human Behaviour, 3(9), 897-905
2018 *Bavard S, *Lebreton M, Khamassi M, Coricelli G, Palminteri S. Reference-point centering and range-adaptation enhance human reinforcement learning at the cost of irrational preferences. Nature Communications, 9(1), 4503