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Sources of Variation in the Spectral Slope of the Sleep EEG
The 1/f spectral slope of the electroencephalogram (EEG) estimated in the γ frequency range has been proposed as an arousal marker that differentiates wake, nonrapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep. Here, we sought to replicate and extend these findings in a large sampl...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society for Neuroscience
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9512622/ https://www.ncbi.nlm.nih.gov/pubmed/36123117 http://dx.doi.org/10.1523/ENEURO.0094-22.2022 |
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author | Kozhemiako, Nataliia Mylonas, Dimitris Pan, Jen Q. Prerau, Michael J. Redline, Susan Purcell, Shaun M. |
author_facet | Kozhemiako, Nataliia Mylonas, Dimitris Pan, Jen Q. Prerau, Michael J. Redline, Susan Purcell, Shaun M. |
author_sort | Kozhemiako, Nataliia |
collection | PubMed |
description | The 1/f spectral slope of the electroencephalogram (EEG) estimated in the γ frequency range has been proposed as an arousal marker that differentiates wake, nonrapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep. Here, we sought to replicate and extend these findings in a large sample, providing a comprehensive characterization of how slope changes with age, sex, and its test-retest reliability as well as potential confounds that could affect the slope estimation. We used 10,255 whole-night polysomnograms (PSGs) from the National Sleep Research Resource (NSRR). All preprocessing steps were performed using an open-source Luna package and the spectral slope was estimated by fitting log-log linear regression models on the absolute power from 30 to 45 Hz separately for wake, NREM, and REM stages. We confirmed that the mean spectral slope grows steeper going from wake to NREM to REM sleep. We found that the choice of mastoid referencing scheme modulated the extent to which electromyogenic, or electrocardiographic artifacts were likely to bias 30- to 45-Hz slope estimates, as well as other sources of technical, device-specific bias. Nonetheless, within individuals, slope estimates were relatively stable over time. Both cross-sectionally and longitudinal, slopes tended to become shallower with increasing age, particularly for REM sleep; males tended to show flatter slopes than females across all states. Our findings support that spectral slope can be a valuable arousal marker for both clinical and research endeavors but also underscore the importance of considering interindividual variation and multiple methodological aspects related to its estimation. |
format | Online Article Text |
id | pubmed-9512622 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Society for Neuroscience |
record_format | MEDLINE/PubMed |
spelling | pubmed-95126222022-09-27 Sources of Variation in the Spectral Slope of the Sleep EEG Kozhemiako, Nataliia Mylonas, Dimitris Pan, Jen Q. Prerau, Michael J. Redline, Susan Purcell, Shaun M. eNeuro Research Article: New Research The 1/f spectral slope of the electroencephalogram (EEG) estimated in the γ frequency range has been proposed as an arousal marker that differentiates wake, nonrapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep. Here, we sought to replicate and extend these findings in a large sample, providing a comprehensive characterization of how slope changes with age, sex, and its test-retest reliability as well as potential confounds that could affect the slope estimation. We used 10,255 whole-night polysomnograms (PSGs) from the National Sleep Research Resource (NSRR). All preprocessing steps were performed using an open-source Luna package and the spectral slope was estimated by fitting log-log linear regression models on the absolute power from 30 to 45 Hz separately for wake, NREM, and REM stages. We confirmed that the mean spectral slope grows steeper going from wake to NREM to REM sleep. We found that the choice of mastoid referencing scheme modulated the extent to which electromyogenic, or electrocardiographic artifacts were likely to bias 30- to 45-Hz slope estimates, as well as other sources of technical, device-specific bias. Nonetheless, within individuals, slope estimates were relatively stable over time. Both cross-sectionally and longitudinal, slopes tended to become shallower with increasing age, particularly for REM sleep; males tended to show flatter slopes than females across all states. Our findings support that spectral slope can be a valuable arousal marker for both clinical and research endeavors but also underscore the importance of considering interindividual variation and multiple methodological aspects related to its estimation. Society for Neuroscience 2022-09-21 /pmc/articles/PMC9512622/ /pubmed/36123117 http://dx.doi.org/10.1523/ENEURO.0094-22.2022 Text en Copyright © 2022 Kozhemiako et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. |
spellingShingle | Research Article: New Research Kozhemiako, Nataliia Mylonas, Dimitris Pan, Jen Q. Prerau, Michael J. Redline, Susan Purcell, Shaun M. Sources of Variation in the Spectral Slope of the Sleep EEG |
title | Sources of Variation in the Spectral Slope of the Sleep EEG |
title_full | Sources of Variation in the Spectral Slope of the Sleep EEG |
title_fullStr | Sources of Variation in the Spectral Slope of the Sleep EEG |
title_full_unstemmed | Sources of Variation in the Spectral Slope of the Sleep EEG |
title_short | Sources of Variation in the Spectral Slope of the Sleep EEG |
title_sort | sources of variation in the spectral slope of the sleep eeg |
topic | Research Article: New Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9512622/ https://www.ncbi.nlm.nih.gov/pubmed/36123117 http://dx.doi.org/10.1523/ENEURO.0094-22.2022 |
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