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数字处理的基础是感觉统合系统而非近似数系统:一项批判性综述。

Sensory-integration system rather than approximate number system underlies numerosity processing: A critical review.

作者信息

Gebuis Titia, Cohen Kadosh Roi, Gevers Wim

机构信息

Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, 1081 HV Amsterdam, The Netherlands.

Department of Experimental Psychology, South Parks Road, Oxford OX1 3UD, United Kingdom.

出版信息

Acta Psychol (Amst). 2016 Nov;171:17-35. doi: 10.1016/j.actpsy.2016.09.003. Epub 2016 Sep 16.

Abstract

It is widely accepted that human and nonhuman species possess a specialized system to process large approximate numerosities. The theory of an evolutionarily ancient approximate number system (ANS) has received converging support from developmental studies, comparative experiments, neuroimaging, and computational modelling, and it is one of the most dominant and influential theories in numerical cognition. The existence of an ANS system is significant, as it is believed to be the building block of numerical development in general. The acuity of the ANS is related to future arithmetic achievements, and intervention strategies therefore aim to improve the ANS. Here we critically review current evidence supporting the existence of an ANS. We show that important shortcomings and confounds exist in the empirical studies on human and non-human animals as well as the logic used to build computational models that support the ANS theory. We conclude that rather than taking the ANS theory for granted, a more comprehensive explanation might be provided by a sensory-integration system that compares or estimates large approximate numerosities by integrating the different sensory cues comprising number stimuli.

摘要

人们普遍认为,人类和非人类物种拥有一个专门用于处理大量近似数量的系统。进化上古老的近似数字系统(ANS)理论得到了发展研究、比较实验、神经成像和计算建模的一致支持,它是数字认知中最具主导性和影响力的理论之一。ANS系统的存在意义重大,因为它被认为是一般数字发展的基石。ANS的敏锐度与未来的算术成就相关,因此干预策略旨在改善ANS。在这里,我们批判性地回顾了支持ANS存在的当前证据。我们表明,在关于人类和非人类动物的实证研究以及用于构建支持ANS理论的计算模型的逻辑中,存在重要的缺陷和混淆。我们得出结论,与其将ANS理论视为理所当然,一个更全面的解释可能是由一个感觉整合系统提供的,该系统通过整合构成数字刺激的不同感觉线索来比较或估计大量近似数量。

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