Impaired arbitration between reward-related decision-making strategies in Alcohol Users compared to Alcohol Non-Users: a computational modeling study

Abstract Reinforcement learning studies propose that decision-making is guided by a tradeoff between computationally cheaper model-free (habitual) control and costly model-based (goal-directed) control. Greater model-based control is typically used under highly rewarding conditions to minimize risk...

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主要な著者:	Srinivasan A. Ramakrishnan, Riaz B. Shaik, Tamizharasan Kanagamani, Gopi Neppala, Jeffrey Chen, Vincenzo G. Fiore, Christopher J. Hammond, Shankar Srinivasan, Iliyan Ivanov, V. Srinivasa Chakravarthy, Wouter Kool, Muhammad A. Parvaz
フォーマット:	Artigo
言語:	Inglês
出版事項:	Springer 2025-01-01
シリーズ:	NPP-Digital Psychiatry and Neuroscience
オンライン･アクセス:	https://doi.org/10.1038/s44277-024-00023-8
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