Suppr超能文献

数量表示在人类下皮层中被编码。

Numerosity representation is encoded in human subcortex.

机构信息

Department of Psychology, Carnegie Mellon University, Pittsburgh PA 15213-3890.

Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh PA 15213-3890.

出版信息

Proc Natl Acad Sci U S A. 2017 Apr 4;114(14):E2806-E2815. doi: 10.1073/pnas.1613982114. Epub 2017 Mar 20.

Abstract

Certain numerical abilities appear to be relatively ubiquitous in the animal kingdom, including the ability to recognize and differentiate relative quantities. This skill is present in human adults and children, as well as in nonhuman primates and, perhaps surprisingly, is also demonstrated by lower species such as mosquitofish and spiders, despite the absence of cortical computation available to primates. This ubiquity of numerical competence suggests that representations that connect to numerical tasks are likely subserved by evolutionarily conserved regions of the nervous system. Here, we test the hypothesis that the evaluation of relative numerical quantities is subserved by lower-order brain structures in humans. Using a monocular/dichoptic paradigm, across four experiments, we show that the discrimination of displays, consisting of both large (5-80) and small (1-4) numbers of dots, is facilitated in the monocular, subcortical portions of the visual system. This is only the case, however, when observers evaluate larger ratios of 3:1 or 4:1, but not smaller ratios, closer to 1:1. This profile of competence matches closely the skill with which newborn infants and other species can discriminate numerical quantity. These findings suggest conservation of ontogenetically and phylogenetically lower-order systems in adults' numerical abilities. The involvement of subcortical structures in representing numerical quantities provokes a reconsideration of current theories of the neural basis of numerical cognition, inasmuch as it bolsters the cross-species continuity of the biological system for numerical abilities.

摘要

某些数字能力似乎在动物王国中相当普遍,包括识别和区分相对数量的能力。这种技能存在于人类成人和儿童、非人类灵长类动物中,甚至在蚊子鱼和蜘蛛等较低等物种中也有表现,尽管灵长类动物没有皮质计算能力。这种数字能力的普遍性表明,与数字任务相关的表示可能是由神经系统中进化保守的区域提供支持的。在这里,我们测试了这样一个假设,即相对数量的评估是由人类大脑的较低层次结构来支持的。我们使用单眼/双视范式,通过四个实验表明,在视觉系统的单眼、皮质下部分,对由大(5-80)和小(1-4)点组成的显示的辨别得到了促进。然而,只有当观察者评估较大的比例 3:1 或 4:1 时,而不是更接近 1:1 的较小比例时,才会出现这种情况。这种能力模式与新生儿和其他物种辨别数量的能力非常吻合。这些发现表明,成人的数字能力在发育和进化上较低层次的系统是保守的。皮质下结构在表示数量上的参与引发了对当前数字认知神经基础理论的重新思考,因为它增强了生物系统在数量能力方面的跨物种连续性。

相似文献

1
Numerosity representation is encoded in human subcortex.数量表示在人类下皮层中被编码。
Proc Natl Acad Sci U S A. 2017 Apr 4;114(14):E2806-E2815. doi: 10.1073/pnas.1613982114. Epub 2017 Mar 20.
8
Functional imaging of numerical processing in adults and 4-y-old children.成人和4岁儿童数字处理的功能成像
PLoS Biol. 2006 May;4(5):e125. doi: 10.1371/journal.pbio.0040125. Epub 2006 Apr 11.
10
Ontogeny of numerical abilities in fish.鱼类数量能力的个体发生。
PLoS One. 2010 Nov 24;5(11):e15516. doi: 10.1371/journal.pone.0015516.

引用本文的文献

2
Neural Basis of Number Sense in Larval Zebrafish.斑马鱼幼体数字感的神经基础
bioRxiv. 2024 Sep 5:2024.08.30.610552. doi: 10.1101/2024.08.30.610552.
7
No evidence for discontinuity between infants and adults.没有证据表明婴儿和成人之间存在间断性。
Trends Cogn Sci. 2023 Aug;27(8):694-695. doi: 10.1016/j.tics.2023.04.003. Epub 2023 Jun 13.
9
Number neurons in the nidopallium of young domestic chicks.年轻家鸡大脑神经核中的神经元数量。
Proc Natl Acad Sci U S A. 2022 Aug 9;119(32):e2201039119. doi: 10.1073/pnas.2201039119. Epub 2022 Aug 2.

本文引用的文献

2
Distinct Neural Signatures for Very Small and Very Large Numerosities.非常小和非常大数量的独特神经特征。
Front Hum Neurosci. 2017 Jan 31;11:21. doi: 10.3389/fnhum.2017.00021. eCollection 2017.
6
Neural foundations and functional specificity of number representations.数字表征的神经基础与功能特异性
Neuropsychologia. 2016 Mar;83:257-273. doi: 10.1016/j.neuropsychologia.2015.09.025. Epub 2015 Sep 25.
8
Rapid and Direct Encoding of Numerosity in the Visual Stream.视觉流中数量的快速直接编码
Cereb Cortex. 2016 Feb;26(2):748-763. doi: 10.1093/cercor/bhv017. Epub 2015 Feb 24.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验