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Neural decoding of single vowels during covert articulation using electrocorticography
The human brain has important abilities for manipulating phonemes, the basic building blocks of speech; these abilities represent phonological processing. Previous studies have shown change in the activation levels of broad cortical areas such as the premotor cortex, the inferior frontal gyrus, and...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3945950/ https://www.ncbi.nlm.nih.gov/pubmed/24639642 http://dx.doi.org/10.3389/fnhum.2014.00125 |
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author | Ikeda, Shigeyuki Shibata, Tomohiro Nakano, Naoki Okada, Rieko Tsuyuguchi, Naohiro Ikeda, Kazushi Kato, Amami |
author_facet | Ikeda, Shigeyuki Shibata, Tomohiro Nakano, Naoki Okada, Rieko Tsuyuguchi, Naohiro Ikeda, Kazushi Kato, Amami |
author_sort | Ikeda, Shigeyuki |
collection | PubMed |
description | The human brain has important abilities for manipulating phonemes, the basic building blocks of speech; these abilities represent phonological processing. Previous studies have shown change in the activation levels of broad cortical areas such as the premotor cortex, the inferior frontal gyrus, and the superior temporal gyrus during phonological processing. However, whether these areas actually convey signals to representations related to individual phonemes remains unclear. This study focused on single vowels and investigated cortical areas important for representing single vowels using electrocorticography (ECoG) during covert articulation. To identify such cortical areas, we used a neural decoding approach in which machine learning models identify vowels. A decoding model was trained on the ECoG signals from individual electrodes placed on the subjects' cortices. We then statistically evaluated whether each decoding model showed accurate identification of vowels, and we found cortical areas such as the premotor cortex and the superior temporal gyrus. These cortical areas were consistent with previous findings. On the other hand, no electrodes over Broca's area showed significant decoding accuracies. This was inconsistent with findings from a previous study showing that vowels within the phonemic sequence of words can be decoded using ECoG signals from Broca's area. Our results therefore suggest that Broca's area is involved in the processing of vowels within phonemic sequences, but not in the processing of single vowels. |
format | Online Article Text |
id | pubmed-3945950 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-39459502014-03-17 Neural decoding of single vowels during covert articulation using electrocorticography Ikeda, Shigeyuki Shibata, Tomohiro Nakano, Naoki Okada, Rieko Tsuyuguchi, Naohiro Ikeda, Kazushi Kato, Amami Front Hum Neurosci Neuroscience The human brain has important abilities for manipulating phonemes, the basic building blocks of speech; these abilities represent phonological processing. Previous studies have shown change in the activation levels of broad cortical areas such as the premotor cortex, the inferior frontal gyrus, and the superior temporal gyrus during phonological processing. However, whether these areas actually convey signals to representations related to individual phonemes remains unclear. This study focused on single vowels and investigated cortical areas important for representing single vowels using electrocorticography (ECoG) during covert articulation. To identify such cortical areas, we used a neural decoding approach in which machine learning models identify vowels. A decoding model was trained on the ECoG signals from individual electrodes placed on the subjects' cortices. We then statistically evaluated whether each decoding model showed accurate identification of vowels, and we found cortical areas such as the premotor cortex and the superior temporal gyrus. These cortical areas were consistent with previous findings. On the other hand, no electrodes over Broca's area showed significant decoding accuracies. This was inconsistent with findings from a previous study showing that vowels within the phonemic sequence of words can be decoded using ECoG signals from Broca's area. Our results therefore suggest that Broca's area is involved in the processing of vowels within phonemic sequences, but not in the processing of single vowels. Frontiers Media S.A. 2014-03-07 /pmc/articles/PMC3945950/ /pubmed/24639642 http://dx.doi.org/10.3389/fnhum.2014.00125 Text en Copyright © 2014 Ikeda, Shibata, Nakano, Okada, Tsuyuguchi, Ikeda and Kato. http://creativecommons.org/licenses/by/3.0/ 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 Ikeda, Shigeyuki Shibata, Tomohiro Nakano, Naoki Okada, Rieko Tsuyuguchi, Naohiro Ikeda, Kazushi Kato, Amami Neural decoding of single vowels during covert articulation using electrocorticography |
title | Neural decoding of single vowels during covert articulation using electrocorticography |
title_full | Neural decoding of single vowels during covert articulation using electrocorticography |
title_fullStr | Neural decoding of single vowels during covert articulation using electrocorticography |
title_full_unstemmed | Neural decoding of single vowels during covert articulation using electrocorticography |
title_short | Neural decoding of single vowels during covert articulation using electrocorticography |
title_sort | neural decoding of single vowels during covert articulation using electrocorticography |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3945950/ https://www.ncbi.nlm.nih.gov/pubmed/24639642 http://dx.doi.org/10.3389/fnhum.2014.00125 |
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