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利用精确 fMRI 技术对多语者和超语者语言网络的功能特征进行研究。

Functional characterization of the language network of polyglots and hyperpolyglots with precision fMRI.

机构信息

Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.

McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.

出版信息

Cereb Cortex. 2024 Mar 1;34(3). doi: 10.1093/cercor/bhae049.

Abstract

How do polyglots-individuals who speak five or more languages-process their languages, and what can this population tell us about the language system? Using fMRI, we identified the language network in each of 34 polyglots (including 16 hyperpolyglots with knowledge of 10+ languages) and examined its response to the native language, non-native languages of varying proficiency, and unfamiliar languages. All language conditions engaged all areas of the language network relative to a control condition. Languages that participants rated as higher proficiency elicited stronger responses, except for the native language, which elicited a similar or lower response than a non-native language of similar proficiency. Furthermore, unfamiliar languages that were typologically related to the participants' high-to-moderate-proficiency languages elicited a stronger response than unfamiliar unrelated languages. The results suggest that the language network's response magnitude scales with the degree of engagement of linguistic computations (e.g. related to lexical access and syntactic-structure building). We also replicated a prior finding of weaker responses to native language in polyglots than non-polyglot bilinguals. These results contribute to our understanding of how multiple languages coexist within a single brain and provide new evidence that the language network responds more strongly to stimuli that more fully engage linguistic computations.

摘要

双语者(能说五种或更多语言的人)如何处理他们的语言,以及这一人群能告诉我们有关语言系统的哪些信息?我们使用 fMRI 技术在 34 位双语者(包括 16 位精通 10 种以上语言的超级双语者)中确定了他们的语言网络,并研究了该网络对母语、不同熟练程度的非母语以及不熟悉语言的反应。与控制条件相比,所有语言条件都能激活语言网络的所有区域。与不熟悉的语言相比,参与者评价为熟练程度较高的语言会引起更强的反应,母语除外,母语的反应与相似熟练程度的非母语相似或较弱。此外,与参与者高到中等熟练程度的语言在类型学上相关的不熟悉语言会引起比不熟悉的不相关语言更强的反应。结果表明,语言网络的反应强度与语言计算的参与程度(例如与词汇检索和句法结构构建相关)成正比。我们还复制了先前发现的双语者母语反应弱于非双语者的发现。这些结果有助于我们理解多种语言如何在一个大脑中共存,并提供新的证据表明,语言网络对更充分地参与语言计算的刺激反应更强。

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