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在天气预报任务中学习策略与反馈处理的关系——来自事件相关电位的证据。

On the relationship between learning strategy and feedback processing in the weather prediction task--Evidence from event-related potentials.

机构信息

Institute of Cognitive Neuroscience, Dept. of Neuropsychology, Ruhr University Bochum, Universitaetsstrasse 150, D-44801 Bochum, Germany.

出版信息

Neuropsychologia. 2013 Mar;51(4):695-703. doi: 10.1016/j.neuropsychologia.2013.01.009. Epub 2013 Jan 21.

Abstract

Previous work has shown that both declarative and non-declarative strategies can be engaged in probabilistic classification learning. With respect to the neural correlates of these strategies, earlier studies have focused on the classification process itself. In the present experiment, we asked whether the feedback for classification performance is processed differently by declarative and non-declarative learners. We recorded event-related potentials (ERPs) while participants performed a modified version of the weather prediction task, a well-known probabilistic classification learning task. ERP analysis focused on two ERP components typically associated with feedback processing, the feedback-related negativity (FRN) and the P300. FRN amplitude was not affected by learning strategy. The P300, however, was more pronounced in declarative learners, particularly at frontal electrode site Fz. In addition, P300 topography was different in declarative learners, with amplitude differences between negative and positive feedback being more pronounced over the frontal than the parietal cortex. Differences in feedback processing between groups were still seen after declarative learners had switched to a non-declarative strategy in later phases of the task. Our findings provide evidence for different neural mechanisms of feedback processing in declarative and non-declarative learning. This difference emerges at later stages of feedback processing, after the typical time window of the FRN.

摘要

先前的研究表明,陈述性策略和非陈述性策略都可以应用于概率分类学习。关于这些策略的神经关联,早期的研究主要集中在分类过程本身。在本实验中,我们想知道反馈对分类表现的处理方式是否因陈述性和非陈述性学习者而有所不同。我们记录了参与者在进行天气预测任务(一种著名的概率分类学习任务)的修改版时的事件相关电位(ERP)。ERP 分析集中在两个通常与反馈处理相关的 ERP 成分上,即反馈相关负波(FRN)和 P300。学习策略并不影响 FRN 幅度。然而,P300 在陈述性学习者中更为明显,尤其是在额极 Fz 上。此外,在陈述性学习者中,P300 的地形图不同,负反馈和正反馈之间的振幅差异在额区比顶区更为明显。在任务的后期,当陈述性学习者切换到非陈述性策略后,组间的反馈处理差异仍然存在。我们的研究结果为陈述性和非陈述性学习中的不同反馈处理神经机制提供了证据。这种差异出现在 FRN 的典型时间窗口之后的反馈处理的后期阶段。

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