背景:抑郁症的特征通常是奖励功能受损,并在强化学习中显示出改变的奖励动机。本研究进一步探讨了任务难度是否会影响有或没有抑郁症状的大学生的强化学习。
方法:抑郁症状组(20)和无抑郁症状组(26)完成概率奖励学习任务,中等,和高难度,在该任务中,分析了对奖励的反应偏差和奖励的可识别性。此外,在执行简单的赌博任务时,记录并分析了对奖励和损失反馈的电生理反应。
结果:当任务很容易时,抑郁症症状组比无抑郁症症状组表现出更多的对奖励的反应偏差,然后随着任务难度的增加,对奖励的反应偏差更快地降低。无抑郁症状组仅在高难度条件下才显示出反应偏差的减少。进一步的回归分析表明,反馈相关的负(FRN)和θ振荡可以预测低难度条件下的响应偏差变化,FRN和theta和delta的振荡可以预测中等和高难度条件下的响应偏差变化。
结论:对损失和奖励的电生理反应没有记录在与强化学习行为相同的任务中。
结论:有抑郁症状的大学生在强化学习过程中对任务难度更为敏感。FRN,θ和δ的振荡可以预测奖励倾斜行为。
BACKGROUND: Depression is usually characterized by impairments in reward function, and shows altered motivation to reward in reinforcement learning. This study further explored whether task difficulty affects reinforcement learning in college students with and without depression symptom.
METHODS: The depression symptom group (20) and the no depression symptom group (26) completed a probabilistic reward learning task with low, medium, and high difficulty levels, in which task the response bias to reward and the discriminability of reward were analyzed. Additionally, electrophysiological responses to reward and loss feedback were recorded and analyzed while they performed a simple gambling task.
RESULTS: The depression symptom group showed more response bias to reward than the no depression symptom group when the task was easy and then exhibited more quickly decrease in response bias to reward as task difficulty increased. The no depression symptom group showed a decrease in response bias only in the high-difficulty condition. Further regression analyses showed that, the Feedback-related negativity (FRN) and theta oscillation could predict response bias change in the low-difficulty condition, the FRN and oscillations of theta and delta could predict response bias change in the medium and high-difficulty conditions.
CONCLUSIONS: The electrophysiological responses to loss and reward were not recorded in the same task as the reinforcement learning behaviors.
CONCLUSIONS: College students with depression symptom are more sensitive to task difficulty during reinforcement learning. The FRN, and oscillations of theta and delta could predict reward leaning behavior.