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A neurocomputational hypothesis for nicotine addiction.

Abstract : We present a hypothetical neurocomputational model that combines a set of neural circuits at the molecular, cellular, and system levels and accounts for several neurobiological and behavioral processes leading to nicotine addiction. We propose that combining changes in the nicotinic receptor response, expressed by mesolimbic dopaminergic neurons, with dopamine-gated learning in action-selection circuits, suffices to capture the acquisition of nicotine addiction. We show that an opponent process enhanced by persistent nicotine-taking renders self-administration rigid and habitual by inhibiting the learning process, resulting in long-term impairments in the absence of the drug. The model implies distinct thresholds on the dosage and duration for the acquisition and persistence of nicotine addiction. Our hypothesis unites a number of prevalent ideas on nicotine action into a coherent formal network for further understanding of compulsive drug addiction.
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Contributor : Yolande Meunier Connect in order to contact the contributor
Submitted on : Tuesday, July 10, 2007 - 5:24:44 PM
Last modification on : Tuesday, October 18, 2022 - 3:42:53 AM

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Boris S. Guktin, Stanislas Dehaene, Jean-Pierre Changeux. A neurocomputational hypothesis for nicotine addiction.. Proceedings of the National Academy of Sciences of the United States of America, 2006, 103 (4), pp.1106-11. ⟨10.1073/pnas.0510220103⟩. ⟨pasteur-00161490⟩



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