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Articles

The EEG indicators of the dynamic properties of sleep–wake regulating processes: comparison of the changes occurring across wake–sleep transition with the effects of prolonged wakefulness

Pages 621-643 | Received 21 Jun 2012, Accepted 13 Aug 2012, Published online: 19 Sep 2012
 

Abstract

Everyday oscillations between wakefulness and sleep might be ultimately delineated as cyclic alternations between opposing neurobiological processes, i.e. those promoting arousal and inhibiting sleep and those promoting sleep and inhibiting arousal. The question arises of whether it is possible to delineate the signatures of such regulating mechanisms in the human electroencephalogram (EEG). The major aim of the present analysis was to reveal the EEG indicators of the processes underlying wake–sleep transitions. Data included power spectra calculated for 1-min segments of 699 EEG records (315 attempts of 15 subjects to stay permanently awake for 43–61 h, 356 successful attempts of 32 subjects to fall asleep during multiple naps, and 28 commencements and terminations of all-night sleep in 14 subjects). Principal component analysis was performed on the sets of 16 single-Hz log-transformed EEG powers (1–16 Hz). A close similarity was found between the patterns of changes in the EEG measures during prolonged wakefulness and across wake–sleep transitions. The observed time courses of scores on the first and second principal components were interpreted as the pure representatives of the wake and sleep drives, respectively, while the time courses of powers in separate frequency bands might reflect simultaneous influences of both drives.

Acknowledgements

The experiments were supported by the grant numbers 07-06-00263а and 10-06-00114-а from the Russian Foundation for Basic Research, and by the grant numbers 06-06-00375a and 12-06-18001e from the Russian Foundation for Humanities. I am indebted to Olga Donskaya, Dr Evgeniy Verevkin, Dr Vladislav Palchikov, Dr Konstantin Danilenko, and Dmitriy Zolotarev (Heffele) for their help in EEG recordings and their analyses.

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