Low-frequency cortical activity reflects context-dependent parsing of word sequences

Summary: During speech listening, it has been hypothesized that the brain builds representations of linguistic structures like sentences, which are tracked by neural activity entrained to the rhythm of these structures. Alternatively, others proposed that these sentence-tracking neural activities ma...

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Main Authors: Honghua Chen, Minhui Zhang, Tianyi Ye, Max A. Wolpert, Nai Ding
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:iScience
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Online Access:http://www.sciencedirect.com/science/article/pii/S2589004225009113
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author Honghua Chen
Minhui Zhang
Tianyi Ye
Max A. Wolpert
Nai Ding
author_facet Honghua Chen
Minhui Zhang
Tianyi Ye
Max A. Wolpert
Nai Ding
author_sort Honghua Chen
collection DOAJ
description Summary: During speech listening, it has been hypothesized that the brain builds representations of linguistic structures like sentences, which are tracked by neural activity entrained to the rhythm of these structures. Alternatively, others proposed that these sentence-tracking neural activities may reflect the predictability or syntactic properties of individual words. Here, to disentangle the neural responses to sentences and words, we design word sequences that are parsed into different sentences in different contexts. By analyzing neural activity recorded by magnetoencephalography, we find that low-frequency neural activity strongly depends on context—the difference between MEG responses to the same word sequence in two contexts yields a low-frequency signal, which precisely tracks sentences. The predictability and syntactic properties of words can partly explain the neural response in each context but not the difference between contexts. In summary, low-frequency neural activity encodes sentences and can reliably reflect how same-word sequences are parsed in different contexts.
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publishDate 2025-06-01
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spelling doaj-art-0b9c5c0e17bb4d5085f6af0e0010083c2025-08-20T01:52:55ZengElsevieriScience2589-00422025-06-0128611265010.1016/j.isci.2025.112650Low-frequency cortical activity reflects context-dependent parsing of word sequencesHonghua Chen0Minhui Zhang1Tianyi Ye2Max A. Wolpert3Nai Ding4Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, ChinaKey Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, ChinaDepartment of Linguistics, Georgetown University, Washington, DC 20057, USAKey Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China; Corresponding authorKey Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China; Nanhu Brain-computer Interface Institute, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, The MOE Frontier Science Center for Brain Science & Brain-machine Integration, Zhejiang University, Hangzhou 310027, China; Corresponding authorSummary: During speech listening, it has been hypothesized that the brain builds representations of linguistic structures like sentences, which are tracked by neural activity entrained to the rhythm of these structures. Alternatively, others proposed that these sentence-tracking neural activities may reflect the predictability or syntactic properties of individual words. Here, to disentangle the neural responses to sentences and words, we design word sequences that are parsed into different sentences in different contexts. By analyzing neural activity recorded by magnetoencephalography, we find that low-frequency neural activity strongly depends on context—the difference between MEG responses to the same word sequence in two contexts yields a low-frequency signal, which precisely tracks sentences. The predictability and syntactic properties of words can partly explain the neural response in each context but not the difference between contexts. In summary, low-frequency neural activity encodes sentences and can reliably reflect how same-word sequences are parsed in different contexts.http://www.sciencedirect.com/science/article/pii/S2589004225009113NeuroscienceCognitive neuroscience
spellingShingle Honghua Chen
Minhui Zhang
Tianyi Ye
Max A. Wolpert
Nai Ding
Low-frequency cortical activity reflects context-dependent parsing of word sequences
iScience
Neuroscience
Cognitive neuroscience
title Low-frequency cortical activity reflects context-dependent parsing of word sequences
title_full Low-frequency cortical activity reflects context-dependent parsing of word sequences
title_fullStr Low-frequency cortical activity reflects context-dependent parsing of word sequences
title_full_unstemmed Low-frequency cortical activity reflects context-dependent parsing of word sequences
title_short Low-frequency cortical activity reflects context-dependent parsing of word sequences
title_sort low frequency cortical activity reflects context dependent parsing of word sequences
topic Neuroscience
Cognitive neuroscience
url http://www.sciencedirect.com/science/article/pii/S2589004225009113
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AT minhuizhang lowfrequencycorticalactivityreflectscontextdependentparsingofwordsequences
AT tianyiye lowfrequencycorticalactivityreflectscontextdependentparsingofwordsequences
AT maxawolpert lowfrequencycorticalactivityreflectscontextdependentparsingofwordsequences
AT naiding lowfrequencycorticalactivityreflectscontextdependentparsingofwordsequences