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.
| Original language | English |
|---|---|
| Pages (from-to) | 1088-1094 |
| Number of pages | 7 |
| Journal | Journal of Behavior Therapy and Experimental Psychiatry |
| Volume | 43 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2012 Dec |
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Keywords
- 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)
Cite this
Effects of depression on reward-based decision making and variability of action in probabilistic learning. / Kunisato, Yoshihiko; Okamoto, Yasumasa; Ueda, Kazutaka; Onoda, Keiichi; Okada, Go; Yoshimura, Shinpei; Suzuki, Shinichi; Samejima, Kazuyuki; Yamawaki, Shigeto.
In: Journal of Behavior Therapy and Experimental Psychiatry, Vol. 43, No. 4, 12.2012, p. 1088-1094.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Effects of depression on reward-based decision making and variability of action in probabilistic learning
AU - Kunisato, Yoshihiko
AU - Okamoto, Yasumasa
AU - Ueda, Kazutaka
AU - Onoda, Keiichi
AU - Okada, Go
AU - Yoshimura, Shinpei
AU - Suzuki, Shinichi
AU - Samejima, Kazuyuki
AU - Yamawaki, Shigeto
PY - 2012/12
Y1 - 2012/12
N2 - 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.
AB - 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.
KW - Decision making
KW - Depression
KW - Probabilistic learning
KW - Reinforcement learning
KW - Reward sensitivity
KW - Variability of action selection
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U2 - 10.1016/j.jbtep.2012.05.007
DO - 10.1016/j.jbtep.2012.05.007
M3 - Article
C2 - 22721601
AN - SCOPUS:84862287089
VL - 43
SP - 1088
EP - 1094
JO - Journal of Behavior Therapy and Experimental Psychiatry
JF - Journal of Behavior Therapy and Experimental Psychiatry
SN - 0005-7916
IS - 4
ER -