Abstract:
:Based on the dopamine hypotheses of cocaine addiction and the assumption of decrement of brain reward system sensitivity after long-term drug exposure, we propose a computational model for cocaine addiction. Utilizing average reward temporal difference reinforcement learning, we incorporate the elevation of basal reward threshold after long-term drug exposure into the model of drug addiction proposed by Redish. Our model is consistent with the animal models of drug seeking under punishment. In the case of nondrug reward, the model explains increased impulsivity after long-term drug exposure. Furthermore, the existence of a blocking effect for cocaine is predicted by our model.
journal_name
Neural Computjournal_title
Neural computationauthors
Dezfouli A,Piray P,Keramati MM,Ekhtiari H,Lucas C,Mokri Adoi
10.1162/neco.2009.10-08-882subject
Has Abstractpub_date
2009-10-01 00:00:00pages
2869-93issue
10eissn
0899-7667issn
1530-888Xjournal_volume
21pub_type
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