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Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making
Perceptual decision-making requires transforming sensory information into decisions. An ambiguity of sensory input affects perceptual decisions inducing specific time-frequency patterns on EEG (electroencephalogram) signals. This paper uses a wavelet-based method to analyze how ambiguity affects EEG...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038130/ https://www.ncbi.nlm.nih.gov/pubmed/33918223 http://dx.doi.org/10.3390/s21072461 |
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author | Kuc, Alexander Grubov, Vadim V. Maksimenko, Vladimir A. Shusharina, Natalia Pisarchik, Alexander N. Hramov, Alexander E. |
author_facet | Kuc, Alexander Grubov, Vadim V. Maksimenko, Vladimir A. Shusharina, Natalia Pisarchik, Alexander N. Hramov, Alexander E. |
author_sort | Kuc, Alexander |
collection | PubMed |
description | Perceptual decision-making requires transforming sensory information into decisions. An ambiguity of sensory input affects perceptual decisions inducing specific time-frequency patterns on EEG (electroencephalogram) signals. This paper uses a wavelet-based method to analyze how ambiguity affects EEG features during a perceptual decision-making task. We observe that parietal and temporal beta-band wavelet power monotonically increases throughout the perceptual process. Ambiguity induces high frontal beta-band power at 0.3–0.6 s post-stimulus onset. It may reflect the increasing reliance on the top-down mechanisms to facilitate accumulating decision-relevant sensory features. Finally, this study analyzes the perceptual process using mixed within-trial and within-subject design. First, we found significant percept-related changes in each subject and then test their significance at the group level. Thus, observed beta-band biomarkers are pronounced in single EEG trials and may serve as control commands for brain-computer interface (BCI). |
format | Online Article Text |
id | pubmed-8038130 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80381302021-04-12 Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making Kuc, Alexander Grubov, Vadim V. Maksimenko, Vladimir A. Shusharina, Natalia Pisarchik, Alexander N. Hramov, Alexander E. Sensors (Basel) Article Perceptual decision-making requires transforming sensory information into decisions. An ambiguity of sensory input affects perceptual decisions inducing specific time-frequency patterns on EEG (electroencephalogram) signals. This paper uses a wavelet-based method to analyze how ambiguity affects EEG features during a perceptual decision-making task. We observe that parietal and temporal beta-band wavelet power monotonically increases throughout the perceptual process. Ambiguity induces high frontal beta-band power at 0.3–0.6 s post-stimulus onset. It may reflect the increasing reliance on the top-down mechanisms to facilitate accumulating decision-relevant sensory features. Finally, this study analyzes the perceptual process using mixed within-trial and within-subject design. First, we found significant percept-related changes in each subject and then test their significance at the group level. Thus, observed beta-band biomarkers are pronounced in single EEG trials and may serve as control commands for brain-computer interface (BCI). MDPI 2021-04-02 /pmc/articles/PMC8038130/ /pubmed/33918223 http://dx.doi.org/10.3390/s21072461 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kuc, Alexander Grubov, Vadim V. Maksimenko, Vladimir A. Shusharina, Natalia Pisarchik, Alexander N. Hramov, Alexander E. Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making |
title | Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making |
title_full | Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making |
title_fullStr | Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making |
title_full_unstemmed | Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making |
title_short | Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making |
title_sort | sensor-level wavelet analysis reveals eeg biomarkers of perceptual decision-making |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038130/ https://www.ncbi.nlm.nih.gov/pubmed/33918223 http://dx.doi.org/10.3390/s21072461 |
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