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自发与训练后的数字能力。研究非人类动物数字能力的两种主要工具之间的比较。

Spontaneous versus trained numerical abilities. A comparison between the two main tools to study numerical competence in non-human animals.

作者信息

Agrillo Christian, Bisazza Angelo

机构信息

Department of General Psychology, University of Padova, Italy.

Department of General Psychology, University of Padova, Italy.

出版信息

J Neurosci Methods. 2014 Aug 30;234:82-91. doi: 10.1016/j.jneumeth.2014.04.027. Epub 2014 May 2.

Abstract

A large body of experimental evidence shows that animals as diverse as mammals, birds, and fish are capable of processing numerical information. Considerable differences have been reported in some cases among species and a wide debate currently surrounds the issue of whether all vertebrates share the same numerical systems or not. Part of the problem is due to the fact that these studies often use different methods, a circumstance that potentially introduces confounding factors in a comparative analysis. In most studies, two main methodological approaches have been used: spontaneous choice tests and training procedures. The former approach consists of presenting to the subjects two groups of biologically-relevant stimuli (e.g., food items or social companions) differing in numerosity with the assumption that if they are able to discriminate between the two quantities, they are expected to spontaneously select the larger/smaller quantity. In the latter approach, subjects undergo extensive training in which some neutral stimuli (e.g., a quantity of dots) are associated with a reward and the capacity to learn a numerical rule is taken as evidence of numerical abilities. We review the literature on this topic, highlighting the relevance, and potential weaknesses in controlling confounding factors obtained with either approach.

摘要

大量实验证据表明,哺乳动物、鸟类和鱼类等多种动物都有处理数字信息的能力。在某些情况下,不同物种之间已报告存在相当大的差异,目前围绕所有脊椎动物是否共享相同数字系统这一问题存在广泛争论。部分问题在于这些研究通常使用不同方法,这种情况在比较分析中可能会引入混杂因素。在大多数研究中,使用了两种主要的方法:自发选择测试和训练程序。前一种方法是向受试者呈现两组数量不同的与生物相关的刺激物(例如食物或社交伙伴),假设如果它们能够区分这两个数量,就会自发选择较大/较小的数量。在后一种方法中,受试者要接受广泛训练,其中一些中性刺激物(例如一定数量的点)与奖励相关联,学习数字规则的能力被视为数字能力的证据。我们回顾了关于这一主题的文献,强调了每种方法在控制混杂因素方面的相关性和潜在弱点。

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