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Hierarchy, Not Lexical Regularity, Modulates Low-Frequency Neural Synchrony During Language Comprehension

Neural responses appear to synchronize with sentence structure. However, researchers have debated whether this response in the delta band (0.5–3 Hz) really reflects hierarchical information or simply lexical regularities. Computational simulations in which sentences are represented simply as sequenc...

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Autores principales: Lo, Chia-Wen, Tung, Tzu-Yun, Ke, Alan Hezao, Brennan, Jonathan R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MIT Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10158645/
https://www.ncbi.nlm.nih.gov/pubmed/37215342
http://dx.doi.org/10.1162/nol_a_00077
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author Lo, Chia-Wen
Tung, Tzu-Yun
Ke, Alan Hezao
Brennan, Jonathan R.
author_facet Lo, Chia-Wen
Tung, Tzu-Yun
Ke, Alan Hezao
Brennan, Jonathan R.
author_sort Lo, Chia-Wen
collection PubMed
description Neural responses appear to synchronize with sentence structure. However, researchers have debated whether this response in the delta band (0.5–3 Hz) really reflects hierarchical information or simply lexical regularities. Computational simulations in which sentences are represented simply as sequences of high-dimensional numeric vectors that encode lexical information seem to give rise to power spectra similar to those observed for sentence synchronization, suggesting that sentence-level cortical tracking findings may reflect sequential lexical or part-of-speech information, and not necessarily hierarchical syntactic information. Using electroencephalography (EEG) data and the frequency-tagging paradigm, we develop a novel experimental condition to tease apart the predictions of the lexical and the hierarchical accounts of the attested low-frequency synchronization. Under a lexical model, synchronization should be observed even when words are reversed within their phrases (e.g., “sheep white grass eat” instead of “white sheep eat grass”), because the same lexical items are preserved at the same regular intervals. Critically, such stimuli are not syntactically well-formed; thus a hierarchical model does not predict synchronization of phrase- and sentence-level structure in the reversed phrase condition. Computational simulations confirm these diverging predictions. EEG data from N = 31 native speakers of Mandarin show robust delta synchronization to syntactically well-formed isochronous speech. Importantly, no such pattern is observed for reversed phrases, consistent with the hierarchical, but not the lexical, accounts.
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spelling pubmed-101586452023-05-19 Hierarchy, Not Lexical Regularity, Modulates Low-Frequency Neural Synchrony During Language Comprehension Lo, Chia-Wen Tung, Tzu-Yun Ke, Alan Hezao Brennan, Jonathan R. Neurobiol Lang (Camb) Research Article Neural responses appear to synchronize with sentence structure. However, researchers have debated whether this response in the delta band (0.5–3 Hz) really reflects hierarchical information or simply lexical regularities. Computational simulations in which sentences are represented simply as sequences of high-dimensional numeric vectors that encode lexical information seem to give rise to power spectra similar to those observed for sentence synchronization, suggesting that sentence-level cortical tracking findings may reflect sequential lexical or part-of-speech information, and not necessarily hierarchical syntactic information. Using electroencephalography (EEG) data and the frequency-tagging paradigm, we develop a novel experimental condition to tease apart the predictions of the lexical and the hierarchical accounts of the attested low-frequency synchronization. Under a lexical model, synchronization should be observed even when words are reversed within their phrases (e.g., “sheep white grass eat” instead of “white sheep eat grass”), because the same lexical items are preserved at the same regular intervals. Critically, such stimuli are not syntactically well-formed; thus a hierarchical model does not predict synchronization of phrase- and sentence-level structure in the reversed phrase condition. Computational simulations confirm these diverging predictions. EEG data from N = 31 native speakers of Mandarin show robust delta synchronization to syntactically well-formed isochronous speech. Importantly, no such pattern is observed for reversed phrases, consistent with the hierarchical, but not the lexical, accounts. MIT Press 2022-09-22 /pmc/articles/PMC10158645/ /pubmed/37215342 http://dx.doi.org/10.1162/nol_a_00077 Text en © 2022 Massachusetts Institute of Technology https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/.
spellingShingle Research Article
Lo, Chia-Wen
Tung, Tzu-Yun
Ke, Alan Hezao
Brennan, Jonathan R.
Hierarchy, Not Lexical Regularity, Modulates Low-Frequency Neural Synchrony During Language Comprehension
title Hierarchy, Not Lexical Regularity, Modulates Low-Frequency Neural Synchrony During Language Comprehension
title_full Hierarchy, Not Lexical Regularity, Modulates Low-Frequency Neural Synchrony During Language Comprehension
title_fullStr Hierarchy, Not Lexical Regularity, Modulates Low-Frequency Neural Synchrony During Language Comprehension
title_full_unstemmed Hierarchy, Not Lexical Regularity, Modulates Low-Frequency Neural Synchrony During Language Comprehension
title_short Hierarchy, Not Lexical Regularity, Modulates Low-Frequency Neural Synchrony During Language Comprehension
title_sort hierarchy, not lexical regularity, modulates low-frequency neural synchrony during language comprehension
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10158645/
https://www.ncbi.nlm.nih.gov/pubmed/37215342
http://dx.doi.org/10.1162/nol_a_00077
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