Language-specific neural dynamics extend syntax into the time domain.

IF 9.8 1区 生物学 Q1 Agricultural and Biological Sciences PLoS Biology Pub Date : 2025-01-21 eCollection Date: 2025-01-01 DOI:10.1371/journal.pbio.3002968
Cas W Coopmans, Helen de Hoop, Filiz Tezcan, Peter Hagoort, Andrea E Martin
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Abstract

Studies of perception have long shown that the brain adds information to its sensory analysis of the physical environment. A touchstone example for humans is language use: to comprehend a physical signal like speech, the brain must add linguistic knowledge, including syntax. Yet, syntactic rules and representations are widely assumed to be atemporal (i.e., abstract and not bound by time), so they must be translated into time-varying signals for speech comprehension and production. Here, we test 3 different models of the temporal spell-out of syntactic structure against brain activity of people listening to Dutch stories: an integratory bottom-up parser, a predictive top-down parser, and a mildly predictive left-corner parser. These models build exactly the same structure but differ in when syntactic information is added by the brain-this difference is captured in the (temporal distribution of the) complexity metric "incremental node count." Using temporal response function models with both acoustic and information-theoretic control predictors, node counts were regressed against source-reconstructed delta-band activity acquired with magnetoencephalography. Neural dynamics in left frontal and temporal regions most strongly reflect node counts derived by the top-down method, which postulates syntax early in time, suggesting that predictive structure building is an important component of Dutch sentence comprehension. The absence of strong effects of the left-corner model further suggests that its mildly predictive strategy does not represent Dutch language comprehension well, in contrast to what has been found for English. Understanding when the brain projects its knowledge of syntax onto speech, and whether this is done in language-specific ways, will inform and constrain the development of mechanistic models of syntactic structure building in the brain.

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特定于语言的神经动力学将语法扩展到时域。
对感知的研究早就表明,大脑会在对物理环境的感官分析中添加信息。人类的一个典型例子是语言使用:为了理解像语音这样的物理信号,大脑必须添加语言知识,包括语法。然而,句法规则和表征被普遍认为是无时间性的(即抽象的,不受时间的约束),因此它们必须被翻译成时变信号以进行语音理解和生成。在这里,我们针对听荷兰语故事的人的大脑活动测试了三种不同的语法结构时间拼写模型:一个集成的自下而上解析器,一个预测性的自上而下解析器,和一个轻度预测性的左上角解析器。这些模型构建了完全相同的结构,但在大脑添加语法信息的时间上有所不同——这种差异在复杂性度量“增量节点计数”的(时间分布)中得到了体现。利用具有声学和信息论控制预测因子的时间响应函数模型,将节点计数与脑磁图获得的源重构δ带活动进行回归。左额叶和颞叶区域的神经动力学最强烈地反映了自上而下方法得出的节点计数,该方法在较早的时间内假设了语法,这表明预测结构构建是荷兰语句子理解的重要组成部分。左上角模型没有产生强烈的影响,这进一步表明,它的温和预测策略并不能很好地代表荷兰语的理解,这与对英语的理解形成了对比。了解大脑何时将句法知识投射到言语上,以及这是否以特定于语言的方式完成,将为大脑中句法结构构建的机制模型的发展提供信息和限制。
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来源期刊
PLoS Biology
PLoS Biology BIOCHEMISTRY & MOLECULAR BIOLOGY-BIOLOGY
CiteScore
15.40
自引率
2.00%
发文量
359
审稿时长
3-8 weeks
期刊介绍: PLOS Biology is the flagship journal of the Public Library of Science (PLOS) and focuses on publishing groundbreaking and relevant research in all areas of biological science. The journal features works at various scales, ranging from molecules to ecosystems, and also encourages interdisciplinary studies. PLOS Biology publishes articles that demonstrate exceptional significance, originality, and relevance, with a high standard of scientific rigor in methodology, reporting, and conclusions. The journal aims to advance science and serve the research community by transforming research communication to align with the research process. It offers evolving article types and policies that empower authors to share the complete story behind their scientific findings with a diverse global audience of researchers, educators, policymakers, patient advocacy groups, and the general public. PLOS Biology, along with other PLOS journals, is widely indexed by major services such as Crossref, Dimensions, DOAJ, Google Scholar, PubMed, PubMed Central, Scopus, and Web of Science. Additionally, PLOS Biology is indexed by various other services including AGRICOLA, Biological Abstracts, BIOSYS Previews, CABI CAB Abstracts, CABI Global Health, CAPES, CAS, CNKI, Embase, Journal Guide, MEDLINE, and Zoological Record, ensuring that the research content is easily accessible and discoverable by a wide range of audiences.
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