Neural and computational underpinnings of biased confidence in human reinforcement learning

Chih-Chung Ting, Nahuel Salem-Garcia, Stefano Palminteri, Jan Engelmann and Mael Lebreton
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Chih-Chung Ting: UHH - Universität Hamburg = University of Hamburg
Nahuel Salem-Garcia: CISA - Swiss Center for Affective Sciences - UNIGE - Université de Genève = University of Geneva
Stefano Palminteri: ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres

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Abstract: While navigating a fundamentally uncertain world, humans and animals constantly evaluate the probability of their decisions, actions or statements being correct. When explicitly elicited, these confidence estimates typically correlates positively with neural activity in a ventromedial-prefrontal (VMPFC) network and negatively in a dorsolateral and dorsomedial prefrontal network. Here, combining fMRI with a reinforcement-learning paradigm, we leverage the fact that humans are more confident in their choices when seeking gains than avoiding losses to reveal a functional dissociation: whereas the dorsal prefrontal network correlates negatively with a condition-specific confidence signal, the VMPFC network positively encodes task-wide confidence signal incorporating the valence-induced bias. Challenging dominant neuro-computational models, we found that decision-related VMPFC activity better correlates with confidence than with option-values inferred from reinforcement-learning models. Altogether, these results identify the VMPFC as a key node in the neuro-computational architecture that builds global feeling-of-confidence signals from latent decision variables and contextual biases during reinforcement-learning.

Keywords: Decision; Decision making; Human behaviour; Learning algorithms (search for similar items in EconPapers)
Date: 2023
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Published in Nature Communications, 2023, 14, ⟨10.1038/s41467-023-42589-5⟩

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Journal Article: Neural and computational underpinnings of biased confidence in human reinforcement learning (2023)
Working Paper: Neural and computational underpinnings of biased confidence in human reinforcement learning (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:pseptp:halshs-04409145

DOI: 10.1038/s41467-023-42589-5

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