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Feature codes in implicit sequence learning: perceived stimulus locations transfer to motor response locations

机译:隐式序列学习中的特征代码:感知刺激位置转移到电机响应位置

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摘要

An important question in implicit sequence learning research is how the learned information is represented. In earlier models, the representations underlying implicit learning were viewed as being either purely motor or perceptual. These different conceptions were later integrated by multidimensional models such as the Dual System Model of Keele et al. (Psychol Rev 110(2):316-339, 2003). According to this model, different types of sequential information can be learned in parallel, as long as each sequence comprised only one single dimension (e.g., shapes, colors, or response locations). The term dimension, though, is underspecified as it remains an open question whether the involved learning modules are restricted to motor or to perceptual information. This study aims to show that the modules of the implicit learning system are not specific to motor or perceptual processing. Rather, each module processes an abstract feature code which represents both response- and perception-related information. In two experiments, we showed that perceiving a stimulus-location sequence transferred to a motor response-location sequence. This result shows that the mere perception of a sequential feature automatically leads to an activation of the respective motor feature, supporting the notion of abstract feature codes being the basic modules of the implicit learning system. This result could only be obtained, though, when the task instructions emphasized the encoding of the stimulus-locations as opposed to an encoding of the color features. This limitation will be discussed taking into account the importance of the instructed task set.
机译:隐式序列学习研究中的一个重要问题是如何表示学习信息。在早期的模型中,隐含学习的依据是纯粹的电动机或感知的依据。这些不同的概念稍后被多维模型(如Keele等人)的双系统模型为整合。 (心理调控110(2):316-339,2003)。根据该模型,只要每个序列仅包括一个单维(例如,形状,颜色或响应位置),就可以并行地并行学习不同类型的顺序信息。但是,术语维度是强化,因为它仍然是一个缺陷的学习模块,无论是否涉及到电机或感知信息。本研究旨在表明隐式学习系统的模块不是特定于电机或感知处理。相反,每个模块处理抽象特征代码,它代表响应和感知相关信息。在两个实验中,我们表明认为将刺激定位序列传递到电动机响应定位序列。该结果表明,仅仅对顺序特征的感知自动地导致各个电动机特征的激活,支持抽象特征代码的概念是隐式学习系统的基本模块。但是,只有在任务指令强调刺激位置的编码时才可以获得该结果,而不是对颜色特征的编码。将考虑到指示任务集的重要性,讨论此限制。

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