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Optimistic reinforcement learning: computational and neural bases

G. Lefebvre, M. Lebreton, F. Meyniel, S. Bourgeois-Gironde, S. Palminteri
doi: https://doi.org/10.1101/038778
G. Lefebvre
aLaboratoire de Neurosciences Cognitives (LNC), INSERM U960, Ecole Normale Supérieure, 75005, Paris, France
bLaboratoire d'Économie Mathématique et de Microéconomie Appliquée (LEMMA), Université Panthéon-Assas, 75006, Paris, France
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M. Lebreton
cAmsterdam Brain and Cognition (ABC), Nieuwe Achtergracht 129, 1018 WS Amsterdam, the Netherlands
dAmsterdam School of Economics (ASE), Faculty of Economics and Business (FEB), Roetersstraat 11, 1018 WB Amsterdam, the Netherlands
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F. Meyniel
eCognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Sud, Université, Paris-Saclay, NeuroSpin center, 91191 Gif/Yvette, France
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S. Bourgeois-Gironde
bLaboratoire d'Économie Mathématique et de Microéconomie Appliquée (LEMMA), Université Panthéon-Assas, 75006, Paris, France
fInstitut Jean-Nicod (IJN), CNRS UMR 8129; Ecole Normale Supérieure, 75005, Paris, France
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S. Palminteri
aLaboratoire de Neurosciences Cognitives (LNC), INSERM U960, Ecole Normale Supérieure, 75005, Paris, France
gInstitute of Cognitive Neurosciences (ICN), University College London, WC1N 3AR London, UK
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Abstract

While forming and updating beliefs about future life outcomes, people tend to consider good news and to disregard bad news. This tendency is supposed to support the optimism bias. Whether this learning bias is specific to “high-level” abstract belief update or a particular expression of a more general “low-level” reinforcement learning process is unknown. Here we report evidence in favor of the second hypothesis. In a simple instrumental learning task, participants incorporated better-than-expected outcomes at a higher rate compared to worse-than-expected ones. In addition, functional imaging indicated that inter-individual difference in the expression of optimistic update corresponds to enhanced prediction error signaling in the reward circuitry. Our results constitute a new step in the understanding of the genesis of optimism bias at the neurocomputational level.

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Posted October 03, 2016.
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Optimistic reinforcement learning: computational and neural bases
G. Lefebvre, M. Lebreton, F. Meyniel, S. Bourgeois-Gironde, S. Palminteri
bioRxiv 038778; doi: https://doi.org/10.1101/038778
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Optimistic reinforcement learning: computational and neural bases
G. Lefebvre, M. Lebreton, F. Meyniel, S. Bourgeois-Gironde, S. Palminteri
bioRxiv 038778; doi: https://doi.org/10.1101/038778

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