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Positive Classification Advantage: Tracing the Time Course Based on Brain Oscillation
The present study aimed to explore the modulation of frequency bands (alpha, beta, theta) underlying the positive facial expressions classification advantage within different post-stimulus time intervals (100–200 ms, 200–300 ms, 300–400 ms). For this purpose, we recorded electroencephalogram (EEG) a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5768652/ https://www.ncbi.nlm.nih.gov/pubmed/29375353 http://dx.doi.org/10.3389/fnhum.2017.00659 |
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author | Yan, Tianyi Dong, Xiaonan Mu, Nan Liu, Tiantian Chen, Duanduan Deng, Li Wang, Changming Zhao, Lun |
author_facet | Yan, Tianyi Dong, Xiaonan Mu, Nan Liu, Tiantian Chen, Duanduan Deng, Li Wang, Changming Zhao, Lun |
author_sort | Yan, Tianyi |
collection | PubMed |
description | The present study aimed to explore the modulation of frequency bands (alpha, beta, theta) underlying the positive facial expressions classification advantage within different post-stimulus time intervals (100–200 ms, 200–300 ms, 300–400 ms). For this purpose, we recorded electroencephalogram (EEG) activity during an emotion discrimination task for happy, sad and neutral faces. The correlation between the non-phase-locked power of frequency bands and reaction times (RTs) was assessed. The results revealed that beta played a major role in positive classification advantage (PCA) within the 100–200 and 300–400 ms intervals, whereas theta was important within the 200–300 ms interval. We propose that the beta band modulated the neutral and emotional face classification process, and that the theta band modulated for happy and sad face classification. |
format | Online Article Text |
id | pubmed-5768652 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57686522018-01-26 Positive Classification Advantage: Tracing the Time Course Based on Brain Oscillation Yan, Tianyi Dong, Xiaonan Mu, Nan Liu, Tiantian Chen, Duanduan Deng, Li Wang, Changming Zhao, Lun Front Hum Neurosci Neuroscience The present study aimed to explore the modulation of frequency bands (alpha, beta, theta) underlying the positive facial expressions classification advantage within different post-stimulus time intervals (100–200 ms, 200–300 ms, 300–400 ms). For this purpose, we recorded electroencephalogram (EEG) activity during an emotion discrimination task for happy, sad and neutral faces. The correlation between the non-phase-locked power of frequency bands and reaction times (RTs) was assessed. The results revealed that beta played a major role in positive classification advantage (PCA) within the 100–200 and 300–400 ms intervals, whereas theta was important within the 200–300 ms interval. We propose that the beta band modulated the neutral and emotional face classification process, and that the theta band modulated for happy and sad face classification. Frontiers Media S.A. 2018-01-11 /pmc/articles/PMC5768652/ /pubmed/29375353 http://dx.doi.org/10.3389/fnhum.2017.00659 Text en Copyright © 2018 Yan, Dong, Mu, Liu, Chen, Deng, Wang and Zhao. 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 Yan, Tianyi Dong, Xiaonan Mu, Nan Liu, Tiantian Chen, Duanduan Deng, Li Wang, Changming Zhao, Lun Positive Classification Advantage: Tracing the Time Course Based on Brain Oscillation |
title | Positive Classification Advantage: Tracing the Time Course Based on Brain Oscillation |
title_full | Positive Classification Advantage: Tracing the Time Course Based on Brain Oscillation |
title_fullStr | Positive Classification Advantage: Tracing the Time Course Based on Brain Oscillation |
title_full_unstemmed | Positive Classification Advantage: Tracing the Time Course Based on Brain Oscillation |
title_short | Positive Classification Advantage: Tracing the Time Course Based on Brain Oscillation |
title_sort | positive classification advantage: tracing the time course based on brain oscillation |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5768652/ https://www.ncbi.nlm.nih.gov/pubmed/29375353 http://dx.doi.org/10.3389/fnhum.2017.00659 |
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