Behavioral, computational and self-reported measures of reward and punishment sensitivity as predictors of mental health characteristics

Stefano Vrizzi (), Anis Najar, Cédric Lemogne, Stefano Palminteri and Mael Lebreton ()
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Stefano Vrizzi: ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres, LNC2 - Laboratoire de Neurosciences Cognitives & Computationnelles - DEC - Département d'Etudes Cognitives - ENS-PSL - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INSERM - Institut National de la Santé et de la Recherche Médicale
Anis Najar: ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres, LNC2 - Laboratoire de Neurosciences Cognitives & Computationnelles - DEC - Département d'Etudes Cognitives - ENS-PSL - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INSERM - Institut National de la Santé et de la Recherche Médicale
Cédric Lemogne: Hôpital Hôtel-Dieu [Paris] - AP-HP - Assistance publique - Hôpitaux de Paris (AP-HP), CRESS (U1153 / UMR_A 1125) - Centre for Research in Epidemiology and Statistics | Centre de Recherche Épidémiologie et Statistiques - INSERM - Institut National de la Santé et de la Recherche Médicale - UPCité - Université Paris Cité - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Stefano Palminteri: ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres, LNC2 - Laboratoire de Neurosciences Cognitives & Computationnelles - DEC - Département d'Etudes Cognitives - ENS-PSL - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INSERM - Institut National de la Santé et de la Recherche Médicale
Mael Lebreton: PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - ENPC - École nationale des ponts et chaussées - IP Paris - Institut Polytechnique de Paris, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - ENPC - École nationale des ponts et chaussées - IP Paris - Institut Polytechnique de Paris, CISA - Swiss Center for Affective Sciences - UNIGE - Université de Genève = University of Geneva

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Abstract: Computational psychiatry proposes that behavioral task-derived computational measures can improve our understanding, diagnosis and treatment of neuropsychiatric disorders. However, recent meta-analyses in cognitive psychology suggest that behavioral and computational measures are less stable than self-reported surveys as assessed by test–retest correlations. If extended to mental health measures, this poses a challenge to the computational psychiatry agenda. To evaluate this challenge, we collected cross-sectional data from participants who performed a popular reinforcement-learning task twice (~5 months apart). Leveraging a well-validated neuro-computational framework, we compared the reliability of behavioral measures, computational parameters and psychological and mental health questionnaires. Despite the remarkable replicability of behavioral and computational measures averaged at the population level, their test–retest reliability at the individual level was surprisingly low. Furthermore, behavioral measures were essentially correlated only among themselves and generally unrelated to mental health symptoms. Overall, these findings challenge the translational potential of computational approaches for precision psychiatry.

Date: 2025-05
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Published in Nature Mental Health, 2025, 3 (6), pp.654-666. ⟨10.1038/s44220-025-00427-1⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-05163046

DOI: 10.1038/s44220-025-00427-1

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