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Characterizing Neural Entrainment to Hierarchical Linguistic Units using Electroencephalography (EEG)
To understand speech, listeners have to combine the words they hear into phrases and sentences. Recent magnetoencephalography (MEG) and electrocorticography (ECoG) studies show that cortical activity is concurrently entrained/synchronized to the rhythms of multiple levels of linguistic units includi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5624994/ https://www.ncbi.nlm.nih.gov/pubmed/29033809 http://dx.doi.org/10.3389/fnhum.2017.00481 |
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author | Ding, Nai Melloni, Lucia Yang, Aotian Wang, Yu Zhang, Wen Poeppel, David |
author_facet | Ding, Nai Melloni, Lucia Yang, Aotian Wang, Yu Zhang, Wen Poeppel, David |
author_sort | Ding, Nai |
collection | PubMed |
description | To understand speech, listeners have to combine the words they hear into phrases and sentences. Recent magnetoencephalography (MEG) and electrocorticography (ECoG) studies show that cortical activity is concurrently entrained/synchronized to the rhythms of multiple levels of linguistic units including words, phrases, and sentences. Here we investigate whether this phenomenon can be observed using electroencephalography (EEG), a technique that is more widely available than MEG and ECoG. We show that the EEG responses concurrently track the rhythms of hierarchical linguistic units such as syllables/words, phrases, and sentences. The strength of the sentential-rate response correlates with how well each subject can detect random words embedded in a sequence of sentences. In contrast, only a syllabic-rate response is observed for an unintelligible control stimulus. In sum, EEG provides a useful tool to characterize neural encoding of hierarchical linguistic units, potentially even in individual participants. |
format | Online Article Text |
id | pubmed-5624994 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-56249942017-10-13 Characterizing Neural Entrainment to Hierarchical Linguistic Units using Electroencephalography (EEG) Ding, Nai Melloni, Lucia Yang, Aotian Wang, Yu Zhang, Wen Poeppel, David Front Hum Neurosci Neuroscience To understand speech, listeners have to combine the words they hear into phrases and sentences. Recent magnetoencephalography (MEG) and electrocorticography (ECoG) studies show that cortical activity is concurrently entrained/synchronized to the rhythms of multiple levels of linguistic units including words, phrases, and sentences. Here we investigate whether this phenomenon can be observed using electroencephalography (EEG), a technique that is more widely available than MEG and ECoG. We show that the EEG responses concurrently track the rhythms of hierarchical linguistic units such as syllables/words, phrases, and sentences. The strength of the sentential-rate response correlates with how well each subject can detect random words embedded in a sequence of sentences. In contrast, only a syllabic-rate response is observed for an unintelligible control stimulus. In sum, EEG provides a useful tool to characterize neural encoding of hierarchical linguistic units, potentially even in individual participants. Frontiers Media S.A. 2017-09-28 /pmc/articles/PMC5624994/ /pubmed/29033809 http://dx.doi.org/10.3389/fnhum.2017.00481 Text en Copyright © 2017 Ding, Melloni, Yang, Wang, Zhang and Poeppel. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Ding, Nai Melloni, Lucia Yang, Aotian Wang, Yu Zhang, Wen Poeppel, David Characterizing Neural Entrainment to Hierarchical Linguistic Units using Electroencephalography (EEG) |
title | Characterizing Neural Entrainment to Hierarchical Linguistic Units using Electroencephalography (EEG) |
title_full | Characterizing Neural Entrainment to Hierarchical Linguistic Units using Electroencephalography (EEG) |
title_fullStr | Characterizing Neural Entrainment to Hierarchical Linguistic Units using Electroencephalography (EEG) |
title_full_unstemmed | Characterizing Neural Entrainment to Hierarchical Linguistic Units using Electroencephalography (EEG) |
title_short | Characterizing Neural Entrainment to Hierarchical Linguistic Units using Electroencephalography (EEG) |
title_sort | characterizing neural entrainment to hierarchical linguistic units using electroencephalography (eeg) |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5624994/ https://www.ncbi.nlm.nih.gov/pubmed/29033809 http://dx.doi.org/10.3389/fnhum.2017.00481 |
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