SNARC和MARC(反应码语言标记)效应的符号调制。

Hans-Christoph Nuerk, Wiebke Iversen, Klaus Willmes
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引用次数: 211

摘要

数大小和数奇偶表示是基本的数表示。然而,奇偶性的表征比量级的表征要少得多:因此,我们通过检查(新)反应码的语言标记性(MARC)效应来研究它:如果刺激和反应码都具有相同的(一致的)语言标记性(偶数-右,奇数-左),则促进反应,而不一致的条件(偶数-左,奇数-右)导致干扰。我们系统地检查了MARC(奇偶性)和响应码的空间数值关联(SNARC;不同的数字符号(积极的阿拉伯语,消极的阿拉伯语,数字词)和不同的数据分析方法的影响。在奇偶性判断任务中,snarc效应表示的幅度表示在除负数以外的所有符号中都被复制。在所有的分析中都发现了数字词的marc效应,但其他符号的marc效应不太一致。相反,Sternberg(1969)使用非度量的多维标度(MDS)程序对反应时间(RT)数据进行了相关分析,得出了奇偶性和所有符号的响应码之间的明确关联(marc效应),但很少有snarc效应的证据。我们讨论了这些符号特异性的MARC和SNARC效应在多大程度上限制了当前的数字处理模型,并详细阐述了MARC效应可能的功能轨迹。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Notational modulation of the SNARC and the MARC (linguistic markedness of response codes) effect.

Number magnitude and number parity representation are fundamental number representations. However, the representation of parity is much less understood than that of magnitude: Therefore, we investigated it by examining the (new) Linguistic Markedness of Response Codes (MARC) effect: Responses are facilitated if stimuli and response codes both have the same (congruent) linguistic markedness (even-right, odd-left) while incongruent conditions (even-left, odd-right) lead to interference. We examined systematically the MARC (for parity) and the Spatial Numerical Association of Response Codes (SNARC; for magnitude) effect for different number notations (positive Arabic, negative Arabic, number words) and with different methods of data analysis. In a parity judgement task, the SNARCeffect indicating a magnitude representation was replicated for all notations except for negative numerals. The MARCeffect was found for number words in all analyses, but less consistently for the other notations. In contrast, a correlational analysis of the reaction time (RT) data, as suggested by Sternberg (1969) using a nonmetric multi-dimensional scaling (MDS) procedure, produced a clear association of parity and response code for all notations (MARCeffect), but little evidence of the SNARCeffect. We discuss the extent to which these notation-specific MARC and SNARC effects constrain current models of number processing and elaborate on the possible functional locus of the MARC effect.

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