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选择预测反馈负波。

Choice predicts the feedback negativity.

机构信息

School of Psychology, University of Auckland, Auckland, New Zealand.

出版信息

Psychophysiology. 2017 Dec;54(12):1800-1811. doi: 10.1111/psyp.12961. Epub 2017 Jul 28.

Abstract

Choosing the appropriate response given the circumstance is integral to all aspects of human behavior. One way of elucidating the mechanisms of choice is to relate behavior to neural correlates. Electrophysiological evidence implicates the ERP feedback-negativity (FN) and the P300 as promising neural correlates of reward processing, an integral component of learning. However, prior research has not adequately addressed how the development of a preference to select one option over another (choice preference) relates to the FN and the P300. We assessed whether variation in choice preference predicted the FN and P300 amplitude within subjects. We used a discrete-trials two-alternative choice procedure, where the reinforcer rate for each option was dependently scheduled by a concurrent variable interval. The reinforcer ratio for selecting each option was varied between sessions. Choice was quantified using both the generalized matching law sensitivity and the log odds of staying on the same versus switching to the other alternative (stay preference). The relationship between stay preference, FN, and P300 amplitudes was assessed using the innovative application of hierarchical Bayesian linear regression. The results demonstrate that stay preference was controlled by the reinforcer ratios and credibly predicted the FN amplitude but not P300 amplitude. The findings are consistent with the view that reinforcers may guide behavior by what they signal about future reinforcement, with the FN related to such a process.

摘要

鉴于环境选择适当的反应是人类行为的各个方面的组成部分。阐明选择机制的一种方法是将行为与神经相关物联系起来。电生理学证据表明,事件相关电位反馈负波(FN)和 P300 是奖励处理的有前途的神经相关物,奖励处理是学习的一个组成部分。然而,先前的研究并没有充分解决选择一种选择(选择偏好)的偏好的发展与 FN 和 P300 之间的关系。我们评估了选择偏好的变化是否可以预测个体内的 FN 和 P300 幅度。我们使用了离散试验的两种替代选择程序,其中每个选项的强化率由并发的变量间隔独立调度。每次会议之间都会改变选择每个选项的强化比率。使用广义匹配律敏感性和留在同一选项上与切换到另一个选项的对数几率(保持偏好)来量化选择。使用层次贝叶斯线性回归的创新应用评估了保持偏好,FN 和 P300 幅度之间的关系。研究结果表明,保持偏好受强化率的控制,并且可以可靠地预测 FN 幅度,但不能预测 P300 幅度。这些发现与强化物可以通过它们对未来强化的信号来指导行为的观点一致,而 FN 与该过程有关。

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