4.6 Article

Changes in EEG permutation entropy in the evening and in the transition from wake to sleep

期刊

SLEEP
卷 44, 期 4, 页码 -

出版社

OXFORD UNIV PRESS INC
DOI: 10.1093/sleep/zsaa226

关键词

sleep need; electroencephalography; complexity; entropy; multiscale analysis

资金

  1. National Natural Science Foundation of China [61401518]
  2. Fonds National de la Recherche Scientifique (FNRS-Belgium)
  3. Wallonia-Brussels International
  4. National Institutes of Health, National Heart Lung and Blood Institute [R24 HL114473, RFP 75N92019R002, U01HL53916, U01HL53931, U01HL53934, U01HL53937, U01HL53938, U01HL53940, U01HL53941, U01HL64360]
  5. University of Liege
  6. Double FirstClass University project of China

向作者/读者索取更多资源

The study demonstrates that Multiscale Permutation Entropy (MSPE) significantly decreases before sleep onset and in the transition from wakefulness to sleep, effectively discriminating between different sleep stages and showing correlation with spectral measures of EEG related to sleep need.
Quantifying the complexity of the EEG signal during prolonged wakefulness and during sleep is gaining interest as an additional mean to characterize the mechanisms associated with sleep and wakefulness regulation. Here, we characterized how EEG complexity, as indexed by Multiscale Permutation Entropy (MSPE), changed progressively in the evening prior to light off and during the transition from wakefulness to sleep. We further explored whether MSPE was able to discriminate between wakefulness and sleep around sleep onset and whether MSPE changes were correlated with spectral measures of the EEG related to sleep need during concomitant wakefulness (theta power-P-theta: 4-8 Hz). To address these questions, we took advantage of large datasets of several hundred of ambulatory EEG recordings of individual of both sexes aged 25-101 years. Results show that MSPE significantly decreases before light off (i.e. before sleep time) and in the transition from wakefulness to sleep onset. Furthermore, MSPE allows for an excellent discrimination between pre-sleep wakefulness and early sleep. Finally, we show that MSPE is correlated with concomitant P-theta. Yet, the direction of the latter correlation changed from before light-off to the transition to sleep. Given the association between EEG complexity and consciousness, MSPE may track efficiently putative changes in consciousness preceding sleep onset. An MSPE stands as a comprehensive measure that is not limited to a given frequency band and reflects a progressive change brain state associated with sleep and wakefulness regulation. It may be an effective mean to detect when the brain is in a state close to sleep onset.

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