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Is Order the Defining Feature of Magnitude Representation? An ERP Study on Learning Numerical Magnitude and Spatial Order of Artificial Symbols

机译:是量级表示的定义特征? ERp研究学习数值幅度和人工符号的空间秩序

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摘要

Using an artificial-number learning paradigm and the ERP technique, the present study investigated neural mechanisms involved in the learning of magnitude and spatial order. 54 college students were divided into 2 groups matched in age, gender, and school major. One group was asked to learn the associations between magnitude (dot patterns) and the meaningless Gibson symbols, and the other group learned the associations between spatial order (horizontal positions on the screen) and the same set of symbols. Results revealed differentiated neural mechanisms underlying the learning processes of symbolic magnitude and spatial order. Compared to magnitude learning, spatial-order learning showed a later and reversed distance effect. Furthermore, an analysis of the order-priming effect showed that order was not inherent to the learning of magnitude. Results of this study showed a dissociation between magnitude and order, which supports the numerosity code hypothesis of mental representations of magnitude.
机译:本研究使用人工数学习范例和ERP技术,研究了涉及量级和空间顺序学习的神经机制。 54名大学生分为年龄,性别和学校专业相匹配的两组。一组被要求学习幅度(点图案)和无意义的吉布森符号之间的关联,另一组被学习空间顺序(屏幕上的水平位置)与同一组符号之间的关联。结果揭示了不同的神经机制,这些机制是符号幅度和空间顺序的学习过程的基础。与量级学习相比,空间顺序学习显示出较晚的反向距离效应。此外,对阶次启动效应的分析表明,阶次不是学习量级所固有的。这项研究的结果显示了量级和阶数之间的分离,这支持了量级的心理表征的数字编码假说。

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