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简单的算术:对于高度数学焦虑的个体来说并不简单。

Simple arithmetic: not so simple for highly math anxious individuals.

机构信息

Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.

Department of Psychology, The University of Chicago, Chicago, IL 60637, USA.

出版信息

Soc Cogn Affect Neurosci. 2017 Dec 1;12(12):1940-1949. doi: 10.1093/scan/nsx121.

Abstract

Fluency with simple arithmetic, typically achieved in early elementary school, is thought to be one of the building blocks of mathematical competence. Behavioral studies with adults indicate that math anxiety (feelings of tension or apprehension about math) is associated with poor performance on cognitively demanding math problems. However, it remains unclear whether there are fundamental differences in how high and low math anxious individuals approach overlearned simple arithmetic problems that are less reliant on cognitive control. The current study used functional magnetic resonance imaging to examine the neural correlates of simple arithmetic performance across high and low math anxious individuals. We implemented a partial least squares analysis, a data-driven, multivariate analysis method to measure distributed patterns of whole-brain activity associated with performance. Despite overall high simple arithmetic performance across high and low math anxious individuals, performance was differentially dependent on the fronto-parietal attentional network as a function of math anxiety. Specifically, low-compared to high-math anxious individuals perform better when they activate this network less-a potential indication of more automatic problem-solving. These findings suggest that low and high math anxious individuals approach even the most fundamental math problems differently.

摘要

简单算术的流畅性通常在小学早期就已经达到,被认为是数学能力的基础之一。对成年人的行为研究表明,数学焦虑(对数学感到紧张或担忧的感觉)与认知要求高的数学问题表现不佳有关。然而,目前尚不清楚在处理依赖认知控制较少的过度学习简单算术问题时,高数学焦虑和低数学焦虑个体是否存在基本差异。本研究使用功能磁共振成像技术,研究了高数学焦虑和低数学焦虑个体在简单算术表现方面的神经相关性。我们实施了偏最小二乘分析,这是一种数据驱动的多元分析方法,用于测量与表现相关的全脑活动的分布式模式。尽管高数学焦虑和低数学焦虑个体的简单算术表现总体上都很高,但表现却因数学焦虑的不同而依赖于额顶注意网络。具体来说,与高数学焦虑个体相比,低数学焦虑个体在较少激活该网络时表现更好——这可能表明他们的问题解决更加自动化。这些发现表明,即使是最基本的数学问题,高数学焦虑和低数学焦虑个体的处理方式也不同。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e90a/5716197/32fbe0730a44/nsx121f1.jpg

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