Effects of depression on reward-based decision making and variability of action in probabilistic learning

Yoshihiko Kunisato, Yasumasa Okamoto, Kazutaka Ueda, Keiichi Onoda, Go Okada, Shinpei Yoshimura, Shinichi Suzuki, Kazuyuki Samejima, Shigeto Yamawaki

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    32 Citations (Scopus)


    Background and objectives: Depression is characterized by low reward sensitivity in behavioral studies applying signal detection theory. We examined deficits in reward-based decision making in depressed participants during a probabilistic learning task, and used a reinforcement learning model to examine learning parameters during the task. Methods: Thirty-six nonclinical undergraduates completed a probabilistic selection task. Participants were divided into depressed and non-depressed groups based on Center for Epidemiologic Studies-Depression (CES-D) cut scores. We then applied a reinforcement learning model to every participant's behavioral data. Results: Depressed participants showed a reward-based decision making deficit and higher levels of the learning parameter τ, which modulates variability of action selection, as compared to non-depressed participants. Highly variable action selection is more random and characterized by difficulties with selecting a specific course of action. Conclusion: These results suggest that depression is characterized by deficits in reward-based decision making as well as high variability in terms of action selection.

    Original languageEnglish
    Pages (from-to)1088-1094
    Number of pages7
    JournalJournal of Behavior Therapy and Experimental Psychiatry
    Issue number4
    Publication statusPublished - 2012 Dec



    • Decision making
    • Depression
    • Probabilistic learning
    • Reinforcement learning
    • Reward sensitivity
    • Variability of action selection

    ASJC Scopus subject areas

    • Psychiatry and Mental health
    • Experimental and Cognitive Psychology
    • Clinical Psychology
    • Arts and Humanities (miscellaneous)

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