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Spectral EEG correlations from the different phases of general anesthesia
INTRODUCTION: Electroencephalography (EEG) signals contain transient oscillation patterns commonly used to classify brain states in responses to action, sleep, coma or anesthesia. METHODS: Using a time-frequency analysis of the EEG, we search for possible causal correlations between the successive p...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025404/ https://www.ncbi.nlm.nih.gov/pubmed/36950512 http://dx.doi.org/10.3389/fmed.2023.1009434 |
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author | Sun, Christophe Longrois, Dan Holcman, David |
author_facet | Sun, Christophe Longrois, Dan Holcman, David |
author_sort | Sun, Christophe |
collection | PubMed |
description | INTRODUCTION: Electroencephalography (EEG) signals contain transient oscillation patterns commonly used to classify brain states in responses to action, sleep, coma or anesthesia. METHODS: Using a time-frequency analysis of the EEG, we search for possible causal correlations between the successive phases of general anesthesia. We hypothesize that it could be possible to anticipate recovery patterns from the induction or maintenance phases. For that goal, we track the maximum power of the α−band and follow its time course. RESULTS AND DISCUSSION: We quantify the frequency shift of the α−band during the recovery phase and the associated duration. Using Pearson coefficient and Bayes factor, we report non-significant linear correlation between the α−band frequency and duration shifts during recovery and the presence of the δ or the α rhythms during the maintenance phase. We also found no correlations between the α−band emergence trajectory and the total duration of the flat EEG epochs (iso-electric suppressions) induced by a propofol bolus injected during induction. Finally, we quantify the instability of the α−band using the mathematical total variation that measures possible deviations from a flat line. To conclude, the present correlative analysis shows that EEG dynamics extracted from the initial and maintenance phases of general anesthesia cannot anticipate both the emergence trajectory and the extubation time. |
format | Online Article Text |
id | pubmed-10025404 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100254042023-03-21 Spectral EEG correlations from the different phases of general anesthesia Sun, Christophe Longrois, Dan Holcman, David Front Med (Lausanne) Medicine INTRODUCTION: Electroencephalography (EEG) signals contain transient oscillation patterns commonly used to classify brain states in responses to action, sleep, coma or anesthesia. METHODS: Using a time-frequency analysis of the EEG, we search for possible causal correlations between the successive phases of general anesthesia. We hypothesize that it could be possible to anticipate recovery patterns from the induction or maintenance phases. For that goal, we track the maximum power of the α−band and follow its time course. RESULTS AND DISCUSSION: We quantify the frequency shift of the α−band during the recovery phase and the associated duration. Using Pearson coefficient and Bayes factor, we report non-significant linear correlation between the α−band frequency and duration shifts during recovery and the presence of the δ or the α rhythms during the maintenance phase. We also found no correlations between the α−band emergence trajectory and the total duration of the flat EEG epochs (iso-electric suppressions) induced by a propofol bolus injected during induction. Finally, we quantify the instability of the α−band using the mathematical total variation that measures possible deviations from a flat line. To conclude, the present correlative analysis shows that EEG dynamics extracted from the initial and maintenance phases of general anesthesia cannot anticipate both the emergence trajectory and the extubation time. Frontiers Media S.A. 2023-03-06 /pmc/articles/PMC10025404/ /pubmed/36950512 http://dx.doi.org/10.3389/fmed.2023.1009434 Text en Copyright © 2023 Sun, Longrois and Holcman. 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 | Medicine Sun, Christophe Longrois, Dan Holcman, David Spectral EEG correlations from the different phases of general anesthesia |
title | Spectral EEG correlations from the different phases of general anesthesia |
title_full | Spectral EEG correlations from the different phases of general anesthesia |
title_fullStr | Spectral EEG correlations from the different phases of general anesthesia |
title_full_unstemmed | Spectral EEG correlations from the different phases of general anesthesia |
title_short | Spectral EEG correlations from the different phases of general anesthesia |
title_sort | spectral eeg correlations from the different phases of general anesthesia |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025404/ https://www.ncbi.nlm.nih.gov/pubmed/36950512 http://dx.doi.org/10.3389/fmed.2023.1009434 |
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