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双神经网络模型在言语和语言演变中的应用。

Dual Neural Network Model for the Evolution of Speech and Language.

机构信息

Neurobiology of Vocal Communication, Werner Reichardt Centre for Integrative Neuroscience, University of Tübingen, Otfried-Müller-Strasse 25, 72076 Tübingen, Germany.

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

出版信息

Trends Neurosci. 2016 Dec;39(12):813-829. doi: 10.1016/j.tins.2016.10.006. Epub 2016 Nov 22.

Abstract

Explaining the evolution of speech and language poses one of the biggest challenges in biology. We propose a dual network model that posits a volitional articulatory motor network (VAMN) originating in the prefrontal cortex (PFC; including Broca's area) that cognitively controls vocal output of a phylogenetically conserved primary vocal motor network (PVMN) situated in subcortical structures. By comparing the connections between these two systems in human and nonhuman primate brains, we identify crucial biological preadaptations in monkeys for the emergence of a language system in humans. This model of language evolution explains the exclusiveness of non-verbal communication sounds (e.g., cries) in infants with an immature PFC, as well as the observed emergence of non-linguistic vocalizations in adults after frontal lobe pathologies.

摘要

解释言语和语言的演变是生物学面临的最大挑战之一。我们提出了一个双重网络模型,假设一个自愿的发音运动神经网络(VAMN)起源于前额叶皮层(PFC;包括布罗卡区),它认知地控制位于皮质下结构中的进化上保守的主要发声运动神经网络(PVMN)的发声输出。通过比较人类和非人类灵长类动物大脑中这两个系统之间的连接,我们确定了猴子在人类语言系统出现之前的关键生物预适应。这种语言进化模型解释了不成熟的 PFC 婴儿中非语言交流声音(例如哭声)的独特性,以及额叶病变后成年人出现非语言发声的现象。

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