Cocaine addiction as a homeostatic reinforcement learning disorder.

Mehdi Keramati, Audrey Durand, Paul Girardeau, Boris Gutkin, Serge H. Ahmed
Psychological Review. 2017-01-01; 124(2): 130-153
DOI: 10.1037/rev0000046

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1. Psychol Rev. 2017 Mar;124(2):130-153. doi: 10.1037/rev0000046. Epub 2017 Jan 16.

Cocaine addiction as a homeostatic reinforcement learning disorder.

Keramati M(1), Durand A(2), Girardeau P(2), Gutkin B(3), Ahmed SH(2).

Author information:
(1)Gatsby Computational Neuroscience Unit.
(2)Institut des Maladies Neurodégénératives, Université de Bordeaux.
(3)Group for Neural Theory, INSERM U960, Departément des Etudes Cognitives, Ecole
Normale Supérieure, PSL Research University.

Drug addiction implicates both reward learning and homeostatic regulation
mechanisms of the brain. This has stimulated 2 partially successful theoretical
perspectives on addiction. Many important aspects of addiction, however, remain
to be explained within a single, unified framework that integrates the 2
mechanisms. Building upon a recently developed homeostatic reinforcement learning
theory, the authors focus on a key transition stage of addiction that is well
modeled in animals, escalation of drug use, and propose a computational theory of
cocaine addiction where cocaine reinforces behavior due to its rapid homeostatic
corrective effect, whereas its chronic use induces slow and long-lasting changes
in homeostatic setpoint. Simulations show that our new theory accounts for key
behavioral and neurobiological features of addiction, most notably, escalation of
cocaine use, drug-primed craving and relapse, individual differences underlying
dose-response curves, and dopamine D2-receptor downregulation in addicts. The
theory also generates unique predictions about cocaine self-administration
behavior in rats that are confirmed by new experimental results. Viewing
addiction as a homeostatic reinforcement learning disorder coherently explains
many behavioral and neurobiological aspects of the transition to cocaine
addiction, and suggests a new perspective toward understanding addiction.
(PsycINFO Database Record

(c) 2017 APA, all rights reserved).

DOI: 10.1037/rev0000046
PMID: 28095003 [Indexed for MEDLINE]

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