Cogliati Dezza, I;
Xavier, N;
Cleeremans, A;
Yu, A;
(2018)
The Exploration-Exploitation Dilemma as a Tool for Studying Addiction.
In:
Proceedings of the 2018 Conference on Cognitive Computational Neuroscience (CCN 2018).
2018 Conference on Cognitive Computational Neuroscience (CCN 2018): Cognitive Computational Neuroscience (CCN).
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Abstract
Addiction is a complex psychiatry condition manifested by the loose of control over drugs or nondrug behaviors despite harmful consequences. In this study, we argue that the exploration-exploitation dilemma and its computational mechanisms can help us understand this disorder and its underlying mechanisms. We tested problem gamblers – for whom the confounding effects of substance abuse typically observed in drug addiction are nullified - and controls in a sequential decision-making task and adopted a reinforcement learning model so as to explore the mechanisms involved. The results show an unbalance in how problem gamblers solved decision problems, where reward learning and information control mechanisms both appear to play key roles. By studying addiction under the exploration-exploitation framework, this study opens up a new way of investigating this disorder and of reinterpreting its main symptoms as impairments of both learning and control mechanisms.
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