Computational models of drug use and addiction: A review.

ABSTRACT: In this brief review, we describe current computational models of drug-use and addiction that fall into 2 broad categories: mathematically based models that rely on computational theories, and brain-based models that link computations to brain areas or circuits. Across categories, many are models of learning and decision-making, which may be compromised in addiction. Several mathematical models take predictive coding approaches, focusing on Bayesian prediction error. Other models focus on learning processes and (traditional) prediction error. Brain-based models have incorporated prefrontal cortex, basal ganglia, and the dopamine system, based on the effects of drugs on dopamine, motivation, and executive control circuits. Several models specifically describe how behavioral control may tran

SUBMITTER: Mollick JA 

PROVIDER: S-EPMC7416739 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature