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Mental fatigue decreases complexity: Evidence from multiscale entropy analysis of instantaneous frequency variation in alpha rhythm

Mental fatigue (MF) jeopardizes performance and safety through a variety of cognitive impairments and according to the complexity loss theory, should represent “complexity loss” in electroencephalogram (EEG). However, the studies are few and inconsistent concerning the relationship between MF and lo...

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Autores principales: Zhai, Yawen, Li, Yan, Zhou, Shengyi, Zhang, Chenxu, Luo, Erping, Tang, Chi, Xie, Kangning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643441/
https://www.ncbi.nlm.nih.gov/pubmed/36393985
http://dx.doi.org/10.3389/fnhum.2022.906735
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author Zhai, Yawen
Li, Yan
Zhou, Shengyi
Zhang, Chenxu
Luo, Erping
Tang, Chi
Xie, Kangning
author_facet Zhai, Yawen
Li, Yan
Zhou, Shengyi
Zhang, Chenxu
Luo, Erping
Tang, Chi
Xie, Kangning
author_sort Zhai, Yawen
collection PubMed
description Mental fatigue (MF) jeopardizes performance and safety through a variety of cognitive impairments and according to the complexity loss theory, should represent “complexity loss” in electroencephalogram (EEG). However, the studies are few and inconsistent concerning the relationship between MF and loss of complexity, probably because of the susceptibility of brain waves to noise. In this study, MF was induced in thirteen male college students by a simulated flight task. Before and at the end of the task, spontaneous EEG and auditory steady-state response (ASSR) were recorded and instantaneous frequency variation (IFV) in alpha rhythm was extracted and analyzed by multiscale entropy (MSE) analysis. The results show that there were significant differences in IFV in alpha rhythm either from spontaneous EEG or from ASSR for all subjects. Therefore, the proposed method can be effective in revealing the complexity loss caused by MF in spontaneous EEG and ASSR, which may serve as a promising analyzing method to mark mild mental impairments.
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spelling pubmed-96434412022-11-15 Mental fatigue decreases complexity: Evidence from multiscale entropy analysis of instantaneous frequency variation in alpha rhythm Zhai, Yawen Li, Yan Zhou, Shengyi Zhang, Chenxu Luo, Erping Tang, Chi Xie, Kangning Front Hum Neurosci Human Neuroscience Mental fatigue (MF) jeopardizes performance and safety through a variety of cognitive impairments and according to the complexity loss theory, should represent “complexity loss” in electroencephalogram (EEG). However, the studies are few and inconsistent concerning the relationship between MF and loss of complexity, probably because of the susceptibility of brain waves to noise. In this study, MF was induced in thirteen male college students by a simulated flight task. Before and at the end of the task, spontaneous EEG and auditory steady-state response (ASSR) were recorded and instantaneous frequency variation (IFV) in alpha rhythm was extracted and analyzed by multiscale entropy (MSE) analysis. The results show that there were significant differences in IFV in alpha rhythm either from spontaneous EEG or from ASSR for all subjects. Therefore, the proposed method can be effective in revealing the complexity loss caused by MF in spontaneous EEG and ASSR, which may serve as a promising analyzing method to mark mild mental impairments. Frontiers Media S.A. 2022-10-26 /pmc/articles/PMC9643441/ /pubmed/36393985 http://dx.doi.org/10.3389/fnhum.2022.906735 Text en Copyright © 2022 Zhai, Li, Zhou, Zhang, Luo, Tang and Xie. https://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) and the copyright owner(s) 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 Human Neuroscience
Zhai, Yawen
Li, Yan
Zhou, Shengyi
Zhang, Chenxu
Luo, Erping
Tang, Chi
Xie, Kangning
Mental fatigue decreases complexity: Evidence from multiscale entropy analysis of instantaneous frequency variation in alpha rhythm
title Mental fatigue decreases complexity: Evidence from multiscale entropy analysis of instantaneous frequency variation in alpha rhythm
title_full Mental fatigue decreases complexity: Evidence from multiscale entropy analysis of instantaneous frequency variation in alpha rhythm
title_fullStr Mental fatigue decreases complexity: Evidence from multiscale entropy analysis of instantaneous frequency variation in alpha rhythm
title_full_unstemmed Mental fatigue decreases complexity: Evidence from multiscale entropy analysis of instantaneous frequency variation in alpha rhythm
title_short Mental fatigue decreases complexity: Evidence from multiscale entropy analysis of instantaneous frequency variation in alpha rhythm
title_sort mental fatigue decreases complexity: evidence from multiscale entropy analysis of instantaneous frequency variation in alpha rhythm
topic Human Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643441/
https://www.ncbi.nlm.nih.gov/pubmed/36393985
http://dx.doi.org/10.3389/fnhum.2022.906735
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