Titre : | Addiction as a computational process gone awry (2004) |
Auteurs : | REDISH A. D. |
Type de document : | Article : Périodique |
Dans : | Science (Vol.306, n°5703, 10 December 2004) |
Article en page(s) : | 1944-1947 |
Langues: | Anglais |
Discipline : | PRO (Produits, mode d'action, méthode de dépistage / Substances, action mode, screening methods) |
Mots-clés : |
Thésaurus mots-clés ADDICTION ; MECANISME D'ACTION ; MODELE ; THEORIE ; PHYSIOLOGIE |
Résumé : | Addictive drugs have been hypothesized to access the same neurophysiological mechanisms as natural learning systems. These natural learning systems can be modeled through temporal-difference reinforcement learning (TDRL), which requires a reward-error signal that has been hypothesized to be carried by dopamine. TDRL learns to predict reward by driving that reward-error signal to zero. By adding a noncompensable drug-induced dopamine increase to a TDRL model, a computational model of addiction is constructed that over-selects actions leading to drug receipt. The model provides an explanation for important aspects of the addiction literature and provides a theoretic viewpoint with which to address other aspects. |
Domaine : | Drogues illicites / Illicit drugs |
Refs biblio. : | 41 |
Affiliation : | Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA |
Numéro Toxibase : | 207961 |
Centre Emetteur : | 02 Coordonnateur |
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