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Pre-stimulus EEG Microstates Correlate With Anticipatory Alpha Desynchronization

In the last decades, several electrophysiological markers have been investigated to better understand how humans precede a signaled event. Among others, the pre-stimulus microstates’ topography, representing the whole brain activity, has been proposed as a promising index of the anticipatory period...

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Autores principales: Spadone, Sara, Croce, Pierpaolo, Zappasodi, Filippo, Capotosto, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267023/
https://www.ncbi.nlm.nih.gov/pubmed/32536858
http://dx.doi.org/10.3389/fnhum.2020.00182
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author Spadone, Sara
Croce, Pierpaolo
Zappasodi, Filippo
Capotosto, Paolo
author_facet Spadone, Sara
Croce, Pierpaolo
Zappasodi, Filippo
Capotosto, Paolo
author_sort Spadone, Sara
collection PubMed
description In the last decades, several electrophysiological markers have been investigated to better understand how humans precede a signaled event. Among others, the pre-stimulus microstates’ topography, representing the whole brain activity, has been proposed as a promising index of the anticipatory period in several cognitive tasks. However, to date, a clear relationship between the metrics of the pre-stimulus microstates [i.e., the global explained variance (GEV) and the frequency of occurrence (FOO)] and well-known electroencephalography marker of the anticipation (i.e., the alpha power reduction) has not been investigated. Here, after extracting the microstates during the expectancy of the semantic memory task, we investigate the correlations between the microstate features and the anticipatory alpha (8–12 Hz) power reduction (i.e., the event-related de-synchronization of the alpha rhythms; ERD) that is widely interpreted as a functional correlate of brain activation. We report a positive correlation between the occurrence of the dominant, but not non-dominant, microstate and both the mean amplitude of high-alpha ERD and the magnitude of the alpha ERD peak so that the stronger the decrease (percentage) in the alpha power, the higher the FOO of the dominant microstate. Moreover, we find a positive correlation between the occurrence of the dominant microstate and the latency of the alpha ERD peak, suggesting that subjects with higher FOO present the stronger alpha ERD closely to the target. These correlations are not significant between the GEV and all anticipatory alpha ERD indices. Our results suggest that only the occurrence of the dominant, but not non-dominant, microstate should be considered as a useful electrophysiological correlate of the cortical activation.
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spelling pubmed-72670232020-06-12 Pre-stimulus EEG Microstates Correlate With Anticipatory Alpha Desynchronization Spadone, Sara Croce, Pierpaolo Zappasodi, Filippo Capotosto, Paolo Front Hum Neurosci Neuroscience In the last decades, several electrophysiological markers have been investigated to better understand how humans precede a signaled event. Among others, the pre-stimulus microstates’ topography, representing the whole brain activity, has been proposed as a promising index of the anticipatory period in several cognitive tasks. However, to date, a clear relationship between the metrics of the pre-stimulus microstates [i.e., the global explained variance (GEV) and the frequency of occurrence (FOO)] and well-known electroencephalography marker of the anticipation (i.e., the alpha power reduction) has not been investigated. Here, after extracting the microstates during the expectancy of the semantic memory task, we investigate the correlations between the microstate features and the anticipatory alpha (8–12 Hz) power reduction (i.e., the event-related de-synchronization of the alpha rhythms; ERD) that is widely interpreted as a functional correlate of brain activation. We report a positive correlation between the occurrence of the dominant, but not non-dominant, microstate and both the mean amplitude of high-alpha ERD and the magnitude of the alpha ERD peak so that the stronger the decrease (percentage) in the alpha power, the higher the FOO of the dominant microstate. Moreover, we find a positive correlation between the occurrence of the dominant microstate and the latency of the alpha ERD peak, suggesting that subjects with higher FOO present the stronger alpha ERD closely to the target. These correlations are not significant between the GEV and all anticipatory alpha ERD indices. Our results suggest that only the occurrence of the dominant, but not non-dominant, microstate should be considered as a useful electrophysiological correlate of the cortical activation. Frontiers Media S.A. 2020-05-27 /pmc/articles/PMC7267023/ /pubmed/32536858 http://dx.doi.org/10.3389/fnhum.2020.00182 Text en Copyright © 2020 Spadone, Croce, Zappasodi and Capotosto. 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) 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 Neuroscience
Spadone, Sara
Croce, Pierpaolo
Zappasodi, Filippo
Capotosto, Paolo
Pre-stimulus EEG Microstates Correlate With Anticipatory Alpha Desynchronization
title Pre-stimulus EEG Microstates Correlate With Anticipatory Alpha Desynchronization
title_full Pre-stimulus EEG Microstates Correlate With Anticipatory Alpha Desynchronization
title_fullStr Pre-stimulus EEG Microstates Correlate With Anticipatory Alpha Desynchronization
title_full_unstemmed Pre-stimulus EEG Microstates Correlate With Anticipatory Alpha Desynchronization
title_short Pre-stimulus EEG Microstates Correlate With Anticipatory Alpha Desynchronization
title_sort pre-stimulus eeg microstates correlate with anticipatory alpha desynchronization
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267023/
https://www.ncbi.nlm.nih.gov/pubmed/32536858
http://dx.doi.org/10.3389/fnhum.2020.00182
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