Literature DB >> 22721601

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

Yoshihiko Kunisato1, Yasumasa Okamoto, Kazutaka Ueda, Keiichi Onoda, Go Okada, Shinpei Yoshimura, Shin-ichi Suzuki, Kazuyuki Samejima, Shigeto Yamawaki.   

Abstract

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.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22721601     DOI: 10.1016/j.jbtep.2012.05.007

Source DB:  PubMed          Journal:  J Behav Ther Exp Psychiatry        ISSN: 0005-7916


  33 in total

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