Review| Volume 72, ISSUE 2, P107-112, July 15, 2012

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Neuroeconomics and the Study of Addiction

  • John Monterosso
    Address correspondence to John Monterosso, Ph.D., University of Southern California, Department of Psychology, 3641 Watt Way, Los Angeles, CA 90089-2520
    Department of Psychology, University of Southern California, Los Angeles, California

    Neuroscience Graduate Program, University of Southern California, Los Angeles, California

    Brain and Creativity Institute, University of Southern California, Los Angeles, California
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  • Payam Piray
    Neuroscience Graduate Program, University of Southern California, Los Angeles, California
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  • Shan Luo
    Department of Psychology, University of Southern California, Los Angeles, California
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      We review the key findings in the application of neuroeconomics to the study of addiction. Although there are not “bright line” boundaries between neuroeconomics and other areas of behavioral science, neuroeconomics coheres around the topic of the neural representations of “Value” (synonymous with the “decision utility” of behavioral economics). Neuroeconomics parameterizes distinct features of Valuation, going beyond the general construct of “reward sensitivity” widely used in addiction research. We argue that its modeling refinements might facilitate the identification of neural substrates that contribute to addiction. We highlight two areas of neuroeconomics that have been particularly productive. The first is research on neural correlates of delay discounting (reduced Valuation of rewards as a function of their delay). The second is work that models how Value is learned as a function of “prediction-error” signaling. Although both areas are part of the neuroeconomic program, delay discounting research grows directly out of behavioral economics, whereas prediction-error work is grounded in models of learning. We also consider efforts to apply neuroeconomics to the study of self-control and discuss challenges for this area. We argue that neuroeconomic work has the potential to generate breakthrough research in addiction science.

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