Technical Report #251

Using Computational Models to Help Explain Decision Making Processes of Substance Abusers

Jerome R. Busemeyer, Julie C. Stout, and Peter Finn, Indiana University

Abstract

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The purpose of this chapter is to formulate a computational model that synthesizes two separate explanations for decision making deficits in substance abusers. One is based on poor planning caused by discounting of future consequences, and the other is based on poor learning caused by insensitivity to punishments or hypersensitivity to rewards. First we review empirical research on differences between substance abusers and non abusers with respect to discounting of future consequences. Second, we review empirical research that has revealed hypersensitivity to rewards or insensitivity to punishments by drug abusers as compared to non abusers on the Bechara-Damasio simulated gambling task. Third we present a computational model of multistage decision making that includes planning for future consequences, and we apply this model to both the delay discounting paradigm and the simulated gambling paradigm. Finally, we make linkages between this computational model and the neurophysiological underpinnings of the model, and we discuss the implications of these linkages for understanding the development of substance abuse habits.

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