• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

在整个语言网络中,相对于词义而言,对句法缺乏选择性。

Lack of selectivity for syntax relative to word meanings throughout the language network.

作者信息

Fedorenko Evelina, Blank Idan Asher, Siegelman Matthew, Mineroff Zachary

机构信息

Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, USA.

Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Department of Psychology, UCLA, Los Angeles, CA 90095, USA.

出版信息

Cognition. 2020 Oct;203:104348. doi: 10.1016/j.cognition.2020.104348. Epub 2020 Jun 20.

DOI:10.1016/j.cognition.2020.104348
PMID:32569894
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7483589/
Abstract

To understand what you are reading now, your mind retrieves the meanings of words and constructions from a linguistic knowledge store (lexico-semantic processing) and identifies the relationships among them to construct a complex meaning (syntactic or combinatorial processing). Do these two sets of processes rely on distinct, specialized mechanisms or, rather, share a common pool of resources? Linguistic theorizing, empirical evidence from language acquisition and processing, and computational modeling have jointly painted a picture whereby lexico-semantic and syntactic processing are deeply inter-connected and perhaps not separable. In contrast, many current proposals of the neural architecture of language continue to endorse a view whereby certain brain regions selectively support syntactic/combinatorial processing, although the locus of such "syntactic hub", and its nature, vary across proposals. Here, we searched for selectivity for syntactic over lexico-semantic processing using a powerful individual-subjects fMRI approach across three sentence comprehension paradigms that have been used in prior work to argue for such selectivity: responses to lexico-semantic vs. morpho-syntactic violations (Experiment 1); recovery from neural suppression across pairs of sentences differing in only lexical items vs. only syntactic structure (Experiment 2); and same/different meaning judgments on such sentence pairs (Experiment 3). Across experiments, both lexico-semantic and syntactic conditions elicited robust responses throughout the left fronto-temporal language network. Critically, however, no regions were more strongly engaged by syntactic than lexico-semantic processing, although some regions showed the opposite pattern. Thus, contra many current proposals of the neural architecture of language, syntactic/combinatorial processing is not separable from lexico-semantic processing at the level of brain regions-or even voxel subsets-within the language network, in line with strong integration between these two processes that has been consistently observed in behavioral and computational language research. The results further suggest that the language network may be generally more strongly concerned with meaning than syntactic form, in line with the primary function of language-to share meanings across minds.

摘要

为了理解你现在正在阅读的内容,你的大脑会从语言知识储备中检索单词和结构的含义(词汇语义处理),并识别它们之间的关系以构建复杂的意义(句法或组合处理)。这两组过程是依赖于不同的、专门的机制,还是共享一个共同的资源库呢?语言理论、语言习得与处理的实证证据以及计算建模共同描绘了一幅图景,即词汇语义和句法处理紧密相连,或许无法分开。相比之下,当前许多关于语言神经结构的提议仍然支持这样一种观点,即某些脑区选择性地支持句法/组合处理,尽管这种“句法中枢”的位置及其性质在不同提议中有所不同。在这里,我们使用一种强大的个体受试者功能磁共振成像方法,在先前研究中用于论证这种选择性的三种句子理解范式中,寻找句法处理相对于词汇语义处理的选择性:对词汇语义与形态句法违反的反应(实验1);在仅词汇项不同与仅句法结构不同的句子对中从神经抑制中恢复(实验2);以及对这些句子对的相同/不同意义判断(实验3)。在所有实验中,词汇语义和句法条件在整个左额颞语言网络中都引发了强烈的反应。然而,至关重要的是,没有哪个区域在句法处理上比词汇语义处理更活跃,尽管有些区域表现出相反的模式。因此,与当前许多关于语言神经结构的提议相反,在语言网络内的脑区甚至体素子集中,句法/组合处理与词汇语义处理是不可分离的,这与在行为和计算语言研究中一直观察到的这两个过程之间的强整合一致。结果进一步表明,语言网络可能总体上更关注意义而非句法形式,这与语言的主要功能——在不同思维之间共享意义——相符。

相似文献

1
Lack of selectivity for syntax relative to word meanings throughout the language network.在整个语言网络中,相对于词义而言,对句法缺乏选择性。
Cognition. 2020 Oct;203:104348. doi: 10.1016/j.cognition.2020.104348. Epub 2020 Jun 20.
2
Lexico-semantics obscures lexical syntax.词汇语义模糊了词汇句法。
Front Lang Sci. 2023;2. doi: 10.3389/flang.2023.1217837. Epub 2023 Aug 9.
3
An Attempt to Conceptually Replicate the Dissociation between Syntax and Semantics during Sentence Comprehension.尝试在句子理解过程中再现句法和语义之间的分离。
Neuroscience. 2019 Aug 10;413:219-229. doi: 10.1016/j.neuroscience.2019.06.003. Epub 2019 Jun 11.
4
Seeing words in context: the interaction of lexical and sentence level information during reading.在语境中理解词汇:阅读过程中词汇与句子层面信息的交互作用。
Brain Res Cogn Brain Res. 2004 Mar;19(1):59-73. doi: 10.1016/j.cogbrainres.2003.10.022.
5
Common and distinct neural substrates for pragmatic, semantic, and syntactic processing of spoken sentences: an fMRI study.口语句子语用、语义和句法处理的共同及不同神经基质:一项功能磁共振成像研究
J Cogn Neurosci. 2000 Mar;12(2):321-41. doi: 10.1162/089892900562138.
6
Lexical and syntactic representations in the brain: an fMRI investigation with multi-voxel pattern analyses.大脑中的词汇和句法表征:基于多体素模式分析的 fMRI 研究。
Neuropsychologia. 2012 Mar;50(4):499-513. doi: 10.1016/j.neuropsychologia.2011.09.014. Epub 2011 Sep 17.
7
Interplay between syntax and semantics during sentence comprehension: ERP effects of combining syntactic and semantic violations.句子理解过程中句法与语义的相互作用:句法和语义违反相结合的事件相关电位效应
J Cogn Neurosci. 2003 Aug 15;15(6):883-99. doi: 10.1162/089892903322370807.
8
Neural correlates of semantic-driven syntactic parsing in sentence comprehension.句子理解中语义驱动句法分析的神经关联
Neuroimage. 2024 Apr 1;289:120543. doi: 10.1016/j.neuroimage.2024.120543. Epub 2024 Feb 17.
9
What role does the anterior temporal lobe play in sentence-level processing? Neural correlates of syntactic processing in semantic variant primary progressive aphasia.前部颞叶在句子层面的处理中扮演什么角色?语义变异原发性进行性失语症中句法处理的神经相关物。
J Cogn Neurosci. 2014 May;26(5):970-85. doi: 10.1162/jocn_a_00550. Epub 2013 Dec 17.
10
Frequency tagging of syntactic structure or lexical properties; a registered MEG study.句法结构或词汇属性的频率标记;一项已注册的脑磁图研究。
Cortex. 2022 Jan;146:24-38. doi: 10.1016/j.cortex.2021.09.012. Epub 2021 Oct 20.

引用本文的文献

1
Active use of latent tree-structured sentence representation in humans and large language models.人类和大语言模型中潜在树状结构句子表征的积极应用。
Nat Hum Behav. 2025 Sep 10. doi: 10.1038/s41562-025-02297-0.
2
Neural basis of linguistic factors involved in thought: an fMRI study with native signers.思维中语言因素的神经基础:一项针对本土手语使用者的功能磁共振成像研究。
Front Psychol. 2025 Aug 14;16:1582136. doi: 10.3389/fpsyg.2025.1582136. eCollection 2025.
3
Personalized neuroimaging reveals the impact of children's interests on language processing in the brain.个性化神经成像揭示了儿童兴趣对大脑语言处理的影响。
Imaging Neurosci (Camb). 2024 Oct 30;2. doi: 10.1162/imag_a_00339. eCollection 2024.
4
Binomial order is a speech marker of psychosis and thought disorder.二项式顺序是精神病和思维障碍的言语标记。
Sci Rep. 2025 Aug 6;15(1):28819. doi: 10.1038/s41598-025-14681-x.
5
Relationship between grammar and schizophrenia: a systematic review and meta-analysis.语法与精神分裂症之间的关系:一项系统综述和荟萃分析。
Commun Med (Lond). 2025 Jun 16;5(1):235. doi: 10.1038/s43856-025-00944-1.
6
Cortical language areas are coupled via a soft hierarchy of model-based linguistic features.皮质语言区域通过基于模型的语言特征的软层次结构相互耦合。
bioRxiv. 2025 Jun 3:2025.06.02.657491. doi: 10.1101/2025.06.02.657491.
7
A two-dimensional space of linguistic representations shared across individuals.个体间共享的语言表征二维空间。
bioRxiv. 2025 May 23:2025.05.21.655330. doi: 10.1101/2025.05.21.655330.
8
Innate network mechanisms of temporal pole for semantic cognition in neonatal and adult twin studies.新生儿和成人双胞胎研究中颞极语义认知的先天网络机制
Nat Commun. 2025 Apr 23;16(1):3835. doi: 10.1038/s41467-025-58896-y.
9
Constructed languages are processed by the same brain mechanisms as natural languages.人造语言和自然语言由相同的大脑机制进行处理。
Proc Natl Acad Sci U S A. 2025 Mar 25;122(12):e2313473122. doi: 10.1073/pnas.2313473122. Epub 2025 Mar 17.
10
Universality of representation in biological and artificial neural networks.生物和人工神经网络中表征的普遍性。
bioRxiv. 2024 Dec 26:2024.12.26.629294. doi: 10.1101/2024.12.26.629294.

本文引用的文献

1
Composition is the Core Driver of the Language-selective Network.成分是语言选择网络的核心驱动因素。
Neurobiol Lang (Camb). 2020 Mar 1;1(1):104-134. doi: 10.1162/nol_a_00005. eCollection 2020.
2
Agrammatism and Paragrammatism: A Cortical Double Dissociation Revealed by Lesion-Symptom Mapping.语法缺失与错语症:通过病损-症状映射揭示的皮质双重分离
Neurobiol Lang (Camb). 2020;1(2):208-225. doi: 10.1162/nol_a_00010. Epub 2020 Jun 1.
3
Incremental Language Comprehension Difficulty Predicts Activity in the Language Network but Not the Multiple Demand Network.语言理解难度的逐渐增加可预测语言网络的活动,但不能预测多重需求网络的活动。
Cereb Cortex. 2021 Jul 29;31(9):4006-4023. doi: 10.1093/cercor/bhab065.
4
Semantic and syntactic composition of minimal adjective-noun phrases in Dutch: An MEG study.荷兰语中最小的形容词-名词短语的语义和句法构成:一项 MEG 研究。
Neuropsychologia. 2021 May 14;155:107754. doi: 10.1016/j.neuropsychologia.2021.107754. Epub 2021 Jan 18.
5
Discourse-level comprehension engages medial frontal Theory of Mind brain regions even for expository texts.即使对于说明文,语篇层面的理解也会激活内侧前额叶心理理论脑区。
Lang Cogn Neurosci. 2020;35(6):780-796. doi: 10.1080/23273798.2018.1525494. Epub 2018 Sep 26.
6
Situating the left-lateralized language network in the broader organization of multiple specialized large-scale distributed networks.将左侧语言网络置于多个专门化的大规模分布式网络的更广泛组织中。
J Neurophysiol. 2020 Nov 1;124(5):1415-1448. doi: 10.1152/jn.00753.2019. Epub 2020 Sep 23.
7
Extraction from subjects: Differences in acceptability depend on the discourse function of the construction.从主体中提取:可接受性的差异取决于结构的语篇功能。
Cognition. 2020 Nov;204:104293. doi: 10.1016/j.cognition.2020.104293. Epub 2020 Jul 27.
8
Variability in the analysis of a single neuroimaging dataset by many teams.由多个团队对单个神经影像学数据集进行分析的可变性。
Nature. 2020 Jun;582(7810):84-88. doi: 10.1038/s41586-020-2314-9. Epub 2020 May 20.
9
No evidence for differences among language regions in their temporal receptive windows.没有证据表明语言区域之间在时间接受窗口方面存在差异。
Neuroimage. 2020 Oct 1;219:116925. doi: 10.1016/j.neuroimage.2020.116925. Epub 2020 May 11.
10
The Domain-General Multiple Demand (MD) Network Does Not Support Core Aspects of Language Comprehension: A Large-Scale fMRI Investigation.域泛型多重需求(MD)网络并不支持语言理解的核心方面:一项大规模 fMRI 研究。
J Neurosci. 2020 Jun 3;40(23):4536-4550. doi: 10.1523/JNEUROSCI.2036-19.2020. Epub 2020 Apr 21.