Faculty of Human Sciences, Waseda University, 2-579-15, Mikajima, Tokorozawa, Saitama 359-1192, Japan.
J Behav Ther Exp Psychiatry. 2012 Dec;43(4):1088-94. doi: 10.1016/j.jbtep.2012.05.007. Epub 2012 May 31.
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.
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.
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.
These results suggest that depression is characterized by deficits in reward-based decision making as well as high variability in terms of action selection.
在应用信号检测理论的行为研究中，抑郁症的特征是奖励敏感性降低。我们在一项概率学习任务中检查了抑郁参与者在基于奖励的决策中的缺陷，并使用强化学习模型来检查任务期间的学习参数。
36 名非临床本科生完成了一项概率选择任务。根据流行病学研究中心抑郁量表 (CES-D) 的评分，参与者被分为抑郁组和非抑郁组。然后，我们将强化学习模型应用于每个参与者的行为数据。
与非抑郁组相比，抑郁组的参与者表现出基于奖励的决策制定缺陷和更高的学习参数 τ，τ 调节了动作选择的可变性。高变动作选择更随机，其特征是难以选择特定的行动方案。
这些结果表明，抑郁症的特征是基于奖励的决策制定缺陷以及动作选择的高度可变性。
