Behavioural and neural characterization of optimistic reinforcement learning

Germain Lefebvre, Mael Lebreton, Florent Meyniel, Sacha Bourgeois-Gironde and Stefano Palminteri ()
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Germain Lefebvre: Laboratoire de Neurosciences Cognitives, Institut National de la Santé et de la Recherche Médicale
Florent Meyniel: INSERM-CEA Cognitive Neuroimaging Unit (UNICOG)
Stefano Palminteri: Laboratoire de Neurosciences Cognitives, Institut National de la Santé et de la Recherche Médicale

Nature Human Behaviour, 2017, vol. 1, issue 4, 1-9

Abstract: Abstract When forming and updating beliefs about future life outcomes, people tend to consider good news and to disregard bad news. This tendency is assumed 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 favour of the second hypothesis. In a simple instrumental learning task, participants incorporated better-than-expected outcomes at a higher rate than worse-than-expected ones. In addition, functional imaging indicated that inter-individual difference in the expression of optimistic update corresponds to enhanced prediction error signalling in the reward circuitry. Our results constitute a step towards the understanding of the genesis of optimism bias at the neurocomputational level.

Date: 2017
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DOI: 10.1038/s41562-017-0067

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