Abstract
Neurobiological mechanisms determining a possibility of parsimonious descriptions of the continuous sleep process as a sequence of a few all-or-nothing variables called “sleep stages” remain unknown. We tested a suggestion that stage 1 sleep (“drowsy sleep”) corresponds to a rapid decay of a wake-promoting process and that the boundary with stages 2 separates this decay from a rapid buildup of a sleep-promoting process. The analyzed dataset included power spectra calculated from the electroencephalographic (EEG) records obtained during attempts of 15 adults to stay permanently awake for 43–61 h and during multiple napping attempts of nine sleep-deprived, nine sleep-restricted, and 11 sleep-unrestricted adults. The time courses of scores on the 1st and 2nd principal components of the EEG spectra reflected the suggested phase relationships between rapid changes in the sleep- and wake-promoting processes, respectively. The 1st principal component score was permanently attenuated during wakefulness and stage 1 sleep but started to build up on the boundary with stage 2. In contrast, the 2nd principal component score started to fall down near the wake-sleep boundary but remained unchanged across stage 2. We concluded that stage 1 sleep corresponds to the decay phase of the wake-promoting process that precedes the buildup phase of the sleep-promoting process during stage 2.
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References
Tanaka H, Hayashi M, Hori T. Statistical features of hypnagogic EEG measured by a new scoring system. Sleep 1996; 19: 731–8.
Ogilvie RD. The process of falling asleep. Sleep Med. 2001; 5: 247–70.
Rechtschaffen A, Kales A, eds. A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects. UCLA Brain Information Service/Brain Research Institute: Los Angeles, 1968.
Iber C, Ancoli-Israel S, Chesson AL, Quan SF. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications. American Association of Sleep Medicine: Westchester, IL, 2007.
Silber MH, Ancoli-Israel S, Bonnet MH et al. The visual scoring of sleep in adults. J. Clin. Sleep Med. 2007; 3: 121–31.
Schulz H. Rethinking sleep analysis. J. Clin. Sleep Med. 2008; 4: 99–103.
De Gennaro L, Ferrara M, Bertini M. The boundary between wakefulness and sleep: quantitative electroencephalographic changes during the sleep onset period. Neuroscience 2001; 107: 1–11.
Wright KP, Jr, Badia P, Wauquier A. Topographical and temporal patterns of brain activity during the transition from wakefulness to sleep. Sleep 1995; 18: 880–9.
Dijk DJ, Brunner DP, Borbély AA. Time course of EEG power density during long sleep in humans. Am. J. Physiol. 1990; 258: R650–61.
Achermann P, Dijk DJ, Brunner DP, Borbély AA. A model of human sleep homeostasis based on EEG slowwave activity: quantitative comparison of data and simulations. Brain Res. Bull. 1993; 31: 97–113.
Borbély AA. A two process model of sleep regulation. Hum. Neurobiol. 1982; 1: 195–204.
Daan S, Beersma DGM, Borbély AA. Timing of human sleep: recovery process gated by a circadian pacemaker. Am. J. Physiol. 1984; 246: R161–78.
Donskaya OG, Verevkin EG, Putilov AA. The first and second principal components of the EEG spectrum as the indicators of sleepiness. Somnologie 2012; 16: 69–79.
Putilov AA. Principal component structure of wake-sleep transition: quantitative description in multiple sleep latency tests. Somnologie 2010; 14: 234–43.
Putilov AA. Prospects of using electroencephalographic signatures of the chronoregulatory processes for meaningful, parsimonious and quantitative description of the sleep-wake sub-states. Biol. Rhythm Res. 2011; 42: 181–207.
Putilov AA. Principal components of electroencephalographic spectrum as markers of opponent processes underlying ultradian sleep cycles. Chronobiol. Int. 2011; 28: 287–99.
Putilov AA, Donskaya OG, Verevkin EG. Quantification of sleepiness through principal component analysis of the EEG spectrum. Chronobiol. Int. 2012; 29: 509–22.
Putilov AA, Donskaya OG, Verevkin EG, Putilov DA. Associations of waking EEG structure with chronotype and trototype of 130 sleep deprived individuals. Biol. Rhythm Res. 2010; 41: 113–36.
Putilov AA, Donskaya OG, Verevkin EG, Shtark MB. Structuring the inter-individual variation in waking EEG can help to discriminate between the objective markers of sleep debt and sleep pressure. Somnologie 2009; 13: 72–88.
Åkerstedt T, Gillberg M. Subjective and objective sleepiness in the active individual. Int. J. Neurosci. 1990; 52: 29–37.
Henelius A, Korpela J, Huotilainen M. Individualising EEG frequency bands for sleep deprivation studies. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2011; 2011: 6083–6.
Finelli L, Borbely AA, Achermann P. Functional topography of the human nonREM sleep electroencephalogram. Eur. J. Neurosci. 2001; 13: 2282–90.
Frigo M, Johnson SG. The design and implementation of FFTW3. Proc. IEEE 2005; 93: 216–31.
Merica H, Fortune RD. State transitions between wake and sleep, and within the ultradian cycle, with focus on the link to neuronal activity. Sleep Med. Rev. 2004; 8: 473–85.
Tanaka H, Hayashi M, Hori T. Topographical characteristics of slow wave activities during the transition from wakefulness to sleep. Clin. Neurophysiol. 2000; 111: 417–27.
Morikawa T, Hayashi M, Hori T. Spatio-temporal variations of alpha and sigma band EEG in waking sleeping transition period. Percept. Mot. Skills 2002; 95: 131–54.
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Putilov, A.A., Donskaya, O.G. Rapid changes in scores on the two largest principal components of the electroencephalographic spectrum demarcate the boundaries of drowsy sleep. Sleep Biol. Rhythms 11, 154–164 (2013). https://doi.org/10.1111/sbr.12017
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DOI: https://doi.org/10.1111/sbr.12017