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


CONCLUSIONS
These results suggest that depression is characterized by deficits in reward-based decision making as well as high variability in terms of action selection.
Faculty of Human Sciences, Waseda University, 2-579-15, Mikajima, Tokorozawa, Saitama 359-1192, Japan.
Yoshihiko
Y
Kunisato
Yasumasa
Y
Okamoto
Kazutaka
K
Ueda
Keiichi
K
Onoda
Go
G
Okada
Shinpei
S
Yoshimura
Shin-ichi
S
Suzuki
Kazuyuki
K
Samejima
Shigeto
S
Yamawaki
D003657:Decision Making; D003863:Depression / Q000523:psychology*; D003866:Depressive Disorder / Q000523:psychology*; D005260:Female; D006801:Humans; D008297:Male; D011337:Probability Learning; D012054:Reinforcement, Psychology; D012201:Reward; D055815:Young Adult