Oscillatory profiles of positive, negative and neutral feedback stimuli during adaptive decision making
Oscillatory profiles of positive, negative and neutral feedback stimuli during adaptive decision making
复制标题
适应性决策过程中正反馈刺激、负反馈刺激和中性反馈刺激的振荡曲线。
DOI：
10.1016/j.ijpsycho.2016.06.018
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发表时间：
2016-09-01
影响因子：
3
通讯作者：
Li, Hong
中科院分区：
文献类型：
--
作者：
Li, Peng;Baker, Travis E.;Li, Hong
在过去的二十年里，强化学习过程中对正反馈和负反馈的电生理反应已经有了很好的记录，然而，人们对经常跟随我们行动的无信息事件的神经反应知之甚少。为了解决这个问题，我们记录了脑电图（EEG）在时间估计任务使用信息（积极和消极）和非信息（中性）反馈。在时间-频率域中，非信息反馈引起的β-γ活性显着低于信息反馈。这一结果表明，β-γ活动对可以指导行为调整的反馈特别敏感，与其他工作一致。相比之下，θ和δ活动对负反馈和中性反馈之间的差异都不敏感，尽管这两种频率都能区分正反馈和非正反馈（中性或负）。有趣的是，在时间域中，我们观察到反馈相关负性的幅度存在线性关系（中性>负性>正性），这是事件相关脑电位的一个组成部分，被认为是一种特定类型的强化学习信号的指标，称为奖励预测误差。综上所述，这些结果表明，强化学习系统将中性反馈视为特例，提供了有关用于索引额叶中线皮层认知功能的电生理测量的有价值信息。(C)2016由Elsevier B. V.出版
The electrophysiological response to positive and negative feedback during reinforcement learning has been well documented over the past two decades, yet, little is known about the neural response to uninformative events that often follow our actions. To address this issue, we recorded the electroencephalograph (EEG) during a time-estimation task using both informative (positive and negative) and uninformative (neutral) feedback. In the time-frequency domain, uninformative feedback elicited significantly less induced beta-gamma activity than informative feedback. This result suggests that beta-gamma activity is particularly sensitive to feedback that can guide behavioral adjustments, consistent with other work. In contrast, neither theta nor delta activity were sensitive to the difference between negative and neutral feedback, though both frequencies discriminated between positive, and non-positive (neutral or negative) feedback. Interestingly, in the time domain, we observed a linear relationship in the amplitude of the feedback-related negativity (neutral > negative > positive), a component of the event-related brain potential thought to index a specific kind of reinforcement learning signal called a reward prediction error. Taken together, these results suggest that the reinforcement learning system treats neutral feedback as a special case, providing valuable information about the electrophysiological measures used to index the cognitive function of frontal midline cortex. (C) 2016 Published by Elsevier B.V.