Human thalamic low-frequency oscillations correlate with expected value and outcomes during reinforcement learning

Antoine Collomb-Clerc, Maëlle C. M. Gueguen, Lorella Minotti, Philippe Kahane, Vincent Navarro, Fabrice Bartolomei, Romain Carron, Jean Regis, Stephan Chabardès, Stefano Palminteri and Julien Bastin ()
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Antoine Collomb-Clerc: Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences
Maëlle C. M. Gueguen: Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences
Lorella Minotti: Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences
Philippe Kahane: Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences
Vincent Navarro: Sorbonne Université, Paris Brain Institute – Institut du Cerveau, ICM, INSERM, CNRS, AP-HP, Pitié-Salpêtrière Hospital
Fabrice Bartolomei: Timone University Hospital, Sleep Unit, Epileptology and Cerebral Rhythmology, University Hospital of Marseille
Romain Carron: Aix Marseille University, Inserm, Institut de Neurosciences des Systèmes
Jean Regis: University Hospital of Marseille
Stephan Chabardès: Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences
Stefano Palminteri: Laboratoire de Neurosciences Cognitives Computationnelles, Département d’Etudes Cognitives, ENS, PSL, INSERM
Julien Bastin: Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences

Nature Communications, 2023, vol. 14, issue 1, 1-10

Abstract: Abstract Reinforcement-based adaptive decision-making is believed to recruit fronto-striatal circuits. A critical node of the fronto-striatal circuit is the thalamus. However, direct evidence of its involvement in human reinforcement learning is lacking. We address this gap by analyzing intra-thalamic electrophysiological recordings from eight participants while they performed a reinforcement learning task. We found that in both the anterior thalamus (ATN) and dorsomedial thalamus (DMTN), low frequency oscillations (LFO, 4-12 Hz) correlated positively with expected value estimated from computational modeling during reward-based learning (after outcome delivery) or punishment-based learning (during the choice process). Furthermore, LFO recorded from ATN/DMTN were also negatively correlated with outcomes so that both components of reward prediction errors were signaled in the human thalamus. The observed differences in the prediction signals between rewarding and punishing conditions shed light on the neural mechanisms underlying action inhibition in punishment avoidance learning. Our results provide insight into the role of thalamus in reinforcement-based decision-making in humans.

Date: 2023
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DOI: 10.1038/s41467-023-42380-6

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