Using the Envelope of the Electroencephalogram as a Model for Gaussianity during Sleep and Anesthesia

Despite the significant differences between sleeping and being under anesthesia, i.e., a physiological process vs. a pharmacologically induced state, they share notable similarities. This is particularly evident when examining the electroencephalogram (EEG), where the spectral content of both states reveals marked increased power within delta (1 - 4 Hz) and alpha (8 - 13 Hz) frequency ranges. To further explore this, a novel analytical framework called the coefficient of variation of the envelope (CVE) was utilized to assess the alpha and delta EEG envelopes during sleep and general anesthesia. This measure is sensitive to different underlying neural dynamics by linking signal morphology and signal energy, specifically through examining deviations from Gaussianity as a marker of synchronicity. Stable episodes were extracted from patients under general anesthesia and controls in non-REM sleep stage 2 and 3. After filtering the EEGs to isolate the delta and alpha bands, the EEG data was segmented into 24-second intervals with a 50% overlap. In addition to the envelope’s energy, CVEs were calculated using the Hilbert transformation. Cutoff values for Gaussianity were derived from simulated EEG signals. CVE values outside the 99% confidence intervals (CI) of the simulated data are considered to indicate either rhythmic (CV E < lowerCI) or pulsatile (CV E > upperCI) activity. The findings revealed differences in CVEs across both delta and alpha-band filtered EEG. Specifically, during sleep, CVEs derived from the delta band were more frequently classified as pulsatile and fell less often within the gaussian range, compared to those observed during general anesthesia. Similar distinctions were observed for alpha-band oscillations. Although the spectral content related to delta and alpha power may appear similar, the morphology of the underlying neural oscillations differs. These differences are critical points that differentiate anesthesia from sleep.

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Publication Details

Journal
IFAC-PapersOnLine
Published
2025-01-01
DOI
https://doi.org/10.1016/j.ifacol.2025.03.051
Primary Topic
EEG and Brain-Computer Interfaces
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article
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article

Using the Envelope of the Electroencephalogram as a Model for Gaussianity during Sleep and Anesthesia

Matthias Kreuzer, Juliana Zimmermann, Julian Ostertag, Gerhard Schneider et al.
IFAC-PapersOnLine
EEG and Brain-Computer Interfaces
article

Using the Envelope of the Electroencephalogram as a Model for Gaussianity during Sleep and Anesthesia

Matthias Kreuzer, Juliana Zimmermann, Julian Ostertag, Gerhard Schneider, Tobias Kraft-Blank
article en

Abstract

Despite the significant differences between sleeping and being under anesthesia, i.e., a physiological process vs. a pharmacologically induced state, they share notable similarities. This is particularly evident when examining the electroencephalogram (EEG), where the spectral content of both states reveals marked increased power within delta (1 - 4 Hz) and alpha (8 - 13 Hz) frequency ranges. To further explore this, a novel analytical framework called the coefficient of variation of the envelope (CVE) was utilized to assess the alpha and delta EEG envelopes during sleep and general anesthesia. This measure is sensitive to different underlying neural dynamics by linking signal morphology and signal energy, specifically through examining deviations from Gaussianity as a marker of synchronicity. Stable episodes were extracted from patients under general anesthesia and controls in non-REM sleep stage 2 and 3. After filtering the EEGs to isolate the delta and alpha bands, the EEG data was segmented into 24-second intervals with a 50% overlap. In addition to the envelope’s energy, CVEs were calculated using the Hilbert transformation. Cutoff values for Gaussianity were derived from simulated EEG signals. CVE values outside the 99% confidence intervals (CI) of the simulated data are considered to indicate either rhythmic (CV E < lowerCI) or pulsatile (CV E > upperCI) activity. The findings revealed differences in CVEs across both delta and alpha-band filtered EEG. Specifically, during sleep, CVEs derived from the delta band were more frequently classified as pulsatile and fell less often within the gaussian range, compared to those observed during general anesthesia. Similar distinctions were observed for alpha-band oscillations. Although the spectral content related to delta and alpha power may appear similar, the morphology of the underlying neural oscillations differs. These differences are critical points that differentiate anesthesia from sleep.

IFAC-PapersOnLineVol. 59(1)
Klinik und Poliklinik für Urologie (DE)
Openalex Percentile: Top 94%
EEG and Brain-Computer Interfaces
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