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灵长类动物大脑“数量神经元”对抽象数量的编码。

Coding of abstract quantity by 'number neurons' of the primate brain.

机构信息

Animal Physiology, Institute of Neurobiology, University of Tübingen, Auf der Morgenstelle 28, 72076 Tübingen, Germany.

出版信息

J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 2013 Jan;199(1):1-16. doi: 10.1007/s00359-012-0763-9. Epub 2012 Oct 10.

DOI:10.1007/s00359-012-0763-9
PMID:23052854
Abstract

Humans share with nonhuman animals a quantification system for representing the number of items as nonverbal mental magnitudes. Over the past decade, the anatomical substrates and neuronal mechanisms of this quantification system have been unraveled down to the level of single neurons. Work with behaviorally trained nonhuman primates identified a parieto-frontal cortical network with individual neurons selectively tuned to the number of items. Such 'number neurons' can track items across space, time, and modality to encode numerosity in a most abstract, supramodal way. The physiological properties of these neurons can explain fundamental psychophysical phenomena during numerosity judgments. Functionally overlapping groups of parietal neurons represent not only numerable-discrete quantity (numerosity), but also innumerable-continuous quantity (extent) and relations between quantities (proportions), supporting the idea of a generalized magnitude system in the brain. These studies establish putative homologies between the monkey and human brain and demonstrate the suitability of nonhuman primates as model system to explore the neurobiological roots of the brain's nonverbal quantification system, which may constitute the evolutionary foundation of all further, more elaborate numerical skills in humans.

摘要

人类和非人类动物共享一个用于表示项目数量的非言语心理量的量化系统。在过去的十年中,这个量化系统的解剖学基础和神经元机制已经被揭示到单个神经元的水平。对经过行为训练的非人类灵长类动物的研究确定了一个顶叶-额叶皮质网络,其中单个神经元对项目数量具有选择性。这种“数字神经元”可以跨空间、时间和模态追踪项目,以最抽象、超模态的方式对数量进行编码。这些神经元的生理特性可以解释数量判断过程中的基本心理物理现象。功能上重叠的顶叶神经元群不仅代表可计数的离散数量(数量),还代表不可计数的连续数量(范围)和数量之间的关系(比例),支持大脑中存在广义数量系统的观点。这些研究在猴子和人类大脑之间建立了假定的同源性,并证明了非人类灵长类动物作为模型系统的适用性,以探索大脑非言语量化系统的神经生物学基础,这可能构成了人类所有进一步、更精细的数字技能的进化基础。

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