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Pre- and post-target cortical processes predict speech-in-noise performance

Understanding speech in noise (SiN) is a complex task that recruits multiple cortical subsystems. There is a variance in individuals’ ability to understand SiN that cannot be explained by simple hearing profiles, which suggests that central factors may underlie the variance in SiN ability. Here, we...

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Autores principales: Kim, Subong, Schwalje, Adam T., Liu, Andrew S., Gander, Phillip E., McMurray, Bob, Griffiths, Timothy D., Choi, Inyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8291856/
https://www.ncbi.nlm.nih.gov/pubmed/33387631
http://dx.doi.org/10.1016/j.neuroimage.2020.117699
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author Kim, Subong
Schwalje, Adam T.
Liu, Andrew S.
Gander, Phillip E.
McMurray, Bob
Griffiths, Timothy D.
Choi, Inyong
author_facet Kim, Subong
Schwalje, Adam T.
Liu, Andrew S.
Gander, Phillip E.
McMurray, Bob
Griffiths, Timothy D.
Choi, Inyong
author_sort Kim, Subong
collection PubMed
description Understanding speech in noise (SiN) is a complex task that recruits multiple cortical subsystems. There is a variance in individuals’ ability to understand SiN that cannot be explained by simple hearing profiles, which suggests that central factors may underlie the variance in SiN ability. Here, we elucidated a few cortical functions involved during a SiN task and their contributions to individual variance using both within- and across-subject approaches. Through our within-subject analysis of source-localized electroencephalography, we investigated how acoustic signal-to-noise ratio (SNR) alters cortical evoked responses to a target word across the speech recognition areas, finding stronger responses in left supramarginal gyrus (SMG, BA40 the dorsal lexicon area) with quieter noise. Through an individual differences approach, we found that listeners show different neural sensitivity to the background noise and target speech, reflected in the amplitude ratio of earlier auditory-cortical responses to speech and noise, named as an internal SNR. Listeners with better internal SNR showed better SiN performance. Further, we found that the post-speech time SMG activity explains a further amount of variance in SiN performance that is not accounted for by internal SNR. This result demonstrates that at least two cortical processes contribute to SiN performance independently: pre-target time processing to attenuate neural representation of background noise and post-target time processing to extract information from speech sounds.
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spelling pubmed-82918562021-07-20 Pre- and post-target cortical processes predict speech-in-noise performance Kim, Subong Schwalje, Adam T. Liu, Andrew S. Gander, Phillip E. McMurray, Bob Griffiths, Timothy D. Choi, Inyong Neuroimage Article Understanding speech in noise (SiN) is a complex task that recruits multiple cortical subsystems. There is a variance in individuals’ ability to understand SiN that cannot be explained by simple hearing profiles, which suggests that central factors may underlie the variance in SiN ability. Here, we elucidated a few cortical functions involved during a SiN task and their contributions to individual variance using both within- and across-subject approaches. Through our within-subject analysis of source-localized electroencephalography, we investigated how acoustic signal-to-noise ratio (SNR) alters cortical evoked responses to a target word across the speech recognition areas, finding stronger responses in left supramarginal gyrus (SMG, BA40 the dorsal lexicon area) with quieter noise. Through an individual differences approach, we found that listeners show different neural sensitivity to the background noise and target speech, reflected in the amplitude ratio of earlier auditory-cortical responses to speech and noise, named as an internal SNR. Listeners with better internal SNR showed better SiN performance. Further, we found that the post-speech time SMG activity explains a further amount of variance in SiN performance that is not accounted for by internal SNR. This result demonstrates that at least two cortical processes contribute to SiN performance independently: pre-target time processing to attenuate neural representation of background noise and post-target time processing to extract information from speech sounds. 2020-12-30 2021-03 /pmc/articles/PMC8291856/ /pubmed/33387631 http://dx.doi.org/10.1016/j.neuroimage.2020.117699 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Article
Kim, Subong
Schwalje, Adam T.
Liu, Andrew S.
Gander, Phillip E.
McMurray, Bob
Griffiths, Timothy D.
Choi, Inyong
Pre- and post-target cortical processes predict speech-in-noise performance
title Pre- and post-target cortical processes predict speech-in-noise performance
title_full Pre- and post-target cortical processes predict speech-in-noise performance
title_fullStr Pre- and post-target cortical processes predict speech-in-noise performance
title_full_unstemmed Pre- and post-target cortical processes predict speech-in-noise performance
title_short Pre- and post-target cortical processes predict speech-in-noise performance
title_sort pre- and post-target cortical processes predict speech-in-noise performance
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8291856/
https://www.ncbi.nlm.nih.gov/pubmed/33387631
http://dx.doi.org/10.1016/j.neuroimage.2020.117699
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