Neurocomputational mechanisms involved in adaptation to fluctuating intentions of others.

Autor: Philippe R; CNRS-Institut des Sciences Cognitives Marc Jeannerod, UMR5229, Neuroeconomics, reward, and decision making laboratory, Lyon, France.; Université Claude Bernard Lyon 1, Lyon, France., Janet R; CNRS-Institut des Sciences Cognitives Marc Jeannerod, UMR5229, Neuroeconomics, reward, and decision making laboratory, Lyon, France.; Université Claude Bernard Lyon 1, Lyon, France., Khalvati K; Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA., Rao RPN; Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA.; Center for Neurotechnology, University of Washington, Seattle, WA, USA., Lee D; Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD, USA.; Kavli Discovery Neuroscience Institute, Johns Hopkins University, Baltimore, MD, USA.; Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA.; Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA., Dreher JC; CNRS-Institut des Sciences Cognitives Marc Jeannerod, UMR5229, Neuroeconomics, reward, and decision making laboratory, Lyon, France. dreher@isc.cnrs.fr.; Université Claude Bernard Lyon 1, Lyon, France. dreher@isc.cnrs.fr.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2024 Apr 12; Vol. 15 (1), pp. 3189. Date of Electronic Publication: 2024 Apr 12.
DOI: 10.1038/s41467-024-47491-2
Abstrakt: Humans frequently interact with agents whose intentions can fluctuate between competition and cooperation over time. It is unclear how the brain adapts to fluctuating intentions of others when the nature of the interactions (to cooperate or compete) is not explicitly and truthfully signaled. Here, we use model-based fMRI and a task in which participants thought they were playing with another player. In fact, they played with an algorithm that alternated without signaling between cooperative and competitive strategies. We show that a neurocomputational mechanism with arbitration between competitive and cooperative experts outperforms other learning models in predicting choice behavior. At the brain level, the fMRI results show that the ventral striatum and ventromedial prefrontal cortex track the difference of reliability between these experts. When attributing competitive intentions, we find increased coupling between these regions and a network that distinguishes prediction errors related to competition and cooperation. These findings provide a neurocomputational account of how the brain arbitrates dynamically between cooperative and competitive intentions when making adaptive social decisions.
(© 2024. The Author(s).)
Databáze: MEDLINE
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