Malik-Moraleda Saima, Taliaferro Maya, Shannon Steve, Jhingan Niharika, Swords Sara, Peterson David J, Frommer Paul, Okrand Marc, Sams Jessie, Cardwell Ramsey, Freeman Cassie, Fedorenko Evelina
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139.
bioRxiv. 2024 Dec 13:2023.07.28.550667. doi: 10.1101/2023.07.28.550667.
What constitutes a language? Natural languages share features with other domains: from math, to music, to gesture. However, the brain mechanisms that process linguistic input are highly specialized, showing little response to diverse non-linguistic tasks. Here, we examine constructed languages (conlangs) to ask whether they draw on the same neural mechanisms as natural languages, or whether they instead pattern with domains like math and programming languages. Using individual-subject fMRI analyses, we show that understanding conlangs recruits the same brain areas as natural language comprehension. This result holds for Esperanto (n=19 speakers) and four fictional conlangs (Klingon (n=10), Na'vi (n=9), High Valyrian (n=3), and Dothraki (n=3)). These findings suggest that conlangs and natural languages share critical features that allow them to draw on the same representations and computations, implemented in the left-lateralized network of brain areas. The features of conlangs that differentiate them from natural languages-including recent creation by a single individual, often for an esoteric purpose, the small number of speakers, and the fact that these languages are typically learned in adulthood-appear to not be consequential for the reliance on the same cognitive and neural mechanisms. We argue that the critical shared feature of conlangs and natural languages is that they are symbolic systems capable of expressing an open-ended range of meanings about our outer and inner worlds.
什么构成了一种语言?自然语言与其他领域有共同特征:从数学到音乐,再到手势。然而,处理语言输入的大脑机制高度专业化,对各种非语言任务几乎没有反应。在这里,我们研究人造语言(世界语),以探讨它们是否与自然语言利用相同的神经机制,或者它们是否与数学和编程语言等领域具有相同模式。通过个体功能磁共振成像分析,我们发现理解世界语所激活的脑区与理解自然语言时相同。这一结果适用于世界语(19名使用者)以及四种虚构的人造语言(克林贡语(10名使用者)、纳美人语(9名使用者)、高等瓦雷利亚语(3名使用者)和多斯拉克语(3名使用者))。这些发现表明,人造语言和自然语言具有关键的共同特征,使它们能够利用相同的表征和计算方式,这些表征和计算方式由大脑左半球的脑区网络实现。人造语言与自然语言的不同特征——包括由个体新近创造,通常出于神秘目的,使用者数量较少,以及这些语言通常是在成年后学习——似乎并不影响它们对相同认知和神经机制的依赖。我们认为,人造语言和自然语言的关键共同特征在于它们是能够表达关于我们外部和内部世界的无限意义的符号系统。