Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Ding, Nai, Melloni, Lucia, Yang, Aotian, Wang, Yu, Zhang, Wen, Poeppel, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
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
_version_ 1783268329789587456
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
work_keys_str_mv AT dingnai characterizingneuralentrainmenttohierarchicallinguisticunitsusingelectroencephalographyeeg
AT mellonilucia characterizingneuralentrainmenttohierarchicallinguisticunitsusingelectroencephalographyeeg
AT yangaotian characterizingneuralentrainmenttohierarchicallinguisticunitsusingelectroencephalographyeeg
AT wangyu characterizingneuralentrainmenttohierarchicallinguisticunitsusingelectroencephalographyeeg
AT zhangwen characterizingneuralentrainmenttohierarchicallinguisticunitsusingelectroencephalographyeeg
AT poeppeldavid characterizingneuralentrainmenttohierarchicallinguisticunitsusingelectroencephalographyeeg