Principal Components of Electroencephalographic Spectrum as Markers of Opponent Processes Underlying Ultradian Sleep Cycles

Abstract

Sleep-wake regulation involves reciprocal interactions between sleep- and wake-promoting processes that inhibit one another. To uncover the signatures of the opponent processes underlying ultradian sleep cycles, principal component analysis was performed on the sets of 16 single-Hz log-transformed electroencephalographic (EEG) power densities (1–16 Hz frequency range). Data were collected during unrestricted night sleep followed by 9 20-min naps (14 women aged 17–55 yrs) and during 12 20-min naps after either restriction or deprivation of sleep (9 males and 9 males, respectively, aged 18–22 yrs). It was found that any subset of power spectra could be reduced to the invariant four–principal component structure. The time courses of scores on these four components might be interpreted as the spectral EEG markers of the kinetics of two pairs of opponent chronoregulatory processes. In a sequence of ultradian sleep cycles, the 1st and 2nd components represent the alternations between competing drives for sleep and wakefulness, respectively, whereas the 3rd and 4th components reflect the alternations between light and deep sleep, respectively. The results suggest that principal component structuring of EEG spectrum can be employed for derivation of the parameters of the quantitative models conceptualizing the three major aspects of sleep-wake regulation—homeostatic, circadian, and ultradian processes. (Author correspondence: [email protected])

Keywords:

• EEG spectrum
• Opponent-process model
• Principal component analysis
• Sleep-wake regulation
• Two-process model

ACKNOWLEDGMENTS

The experiments were supported by the grants numbers 07-06-00263a, 08-04-01071-a, and 10-06-00114-a from the Russian Foundation for Basic Research, and by the grant number 06-06-00375a from the Russian Foundation for Humanities. I am indebted to Dr. Vladislav Palchikov, Dr. Konstantin Danilenko, Dr. Evgeniy Verevkin, Dmitriy Zolotarev (Heffele), and Olga Donskaya for their help in EEG recordings and analyses. I am also grateful to the three anonymous reviewers for their constructive critique, comments, and suggestions, which have essentially improved this paper.

Declaration of Interest: The author reports no conflicts of interest. The author alone is responsible for the content and writing of the paper.