Historique
Article de Périodique
Addiction as a computational process gone awry (2004)
Auteur(s) :
REDISH A. D.
Année
2004
Page(s) :
1944-1947
Langue(s) :
Anglais
Refs biblio. :
41
Domaine :
Drogues illicites / Illicit drugs
Discipline :
PRO (Produits, mode d'action, méthode de dépistage / Substances, action mode, screening methods)
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.
Affiliation :
Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA