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The first and second principal components of the EEG spectrum as the correlates of sleepiness

Erste und zweite Hauptkomponente des EEG-Spektrums als Korrelate für Schläfrigkeit

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Abstract

Purpose

Quantitative EEG measurement of sleepiness must be regarded both as fundamentally and practically important. In a search for the markers of physiological sleepiness, we tested whether the time course of self-perceived sleepiness/alertness correlates with the time courses of scores on principal components of the EEG spectrum.

Subjects and methods

The resting EEG was recorded in 15 healthy subjects with 2 h intervals in frontal and occipital derivations for the last 32–50 h of 44–61 h wakefulness. The correlation coefficients were calculated to test associations of the time course of self-perceived sleepiness/alertness with the time courses of spectral powers and scores on the two largest principal components of the EEG spectrum.

Results and conclusion

The results demonstrate that objective markers of sleepiness can be derived by means of principal component analysis of the EEG spectrum. A score on the 2nd principal component appears to be the most reliable correlate of sleepiness, because it exhibits the fastest decline at the boundary between wakefulness and sleep. A score on the 1st principal component was characterized by a decline before sleep onset followed by a rapid rise after it. These two scores were interpreted as the pure representatives of the wake and sleep drives, respectively, while spectral powers in separate frequency bands appear to reflect simultaneous influences of both drives.

Zusammenfassung

Einführung

Die quantitative EEG-Auswertung hat sowohl im grundsätzlichen als auch im praktischen Sinne eine große Bedeutung. Um physiologische Schäfrigkeitsmarker zu finden, haben wir untersucht, ob der Zeitablauf der subjektiven Schläfrigkeit/Wachsamkeit mit dem Zeitablauf von Parametern der Hauptkomponentenanalyse des aufgezeichneten EEG-Spektrums korreliert.

Personen und Methoden

Ein Ruhe-EEG wurde bei 15 gesunden Testpersonen mit frontalen und okzipitalen Ableitungen alle 2 h aufgezeichnet, wobei die letzten 32–50 h eines Schlafentzugs von 44–61 h herangezogen wurden. Korrelationskoeffizienten wurden errechnet, um den Zusammenhang des Zeitablaufs der subjektiven Schläfrigkeit mit dem Zeitablauf der spektralen Dichte und den 2 Hauptkomponenten des EEG-Spektrums zu testen.

Ergebnisse und Schlussfolgerung

Die Ergebnisse zeigen, dass objektive Schläfrigkeitsmarker mittels der Hauptkomponentenanalyse des EEG-Spektrums abgeleitet werden können. Der Wert der 2. Hauptkomponente scheint ein sicheres Korrelat der Schläfrigkeit zu sein, da dieser die schnellste Abnahme an der Grenze zwischen Wachen und Schlaf aufweist. Der Wert der 1. Hauptkomponente zeigt eine Abnahme vor dem Schlaf und ein schnelles Aufsteigen danach. Diese 2 Werte sind als reine Repräsentanten der Schlaf- und Wachregulation zu interpretieren, wohingegen die spektrale Dichte in getrennten Frequenzbändern die gleichzeitigen Einflüsse dieser Antriebe reflektiert.

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References

  1. Achermann P, Borbely A (1994) Simulation of daytime vigilance by the additive interaction of a homeostatic and a circadian process. Biol Cybern 71:115–121

    Article  PubMed  CAS  Google Scholar 

  2. Åkerstedt T, Gillberg M (1990) Subjective and objective sleepiness in the active individual. Int J Neurosci 52:29–37

    Article  PubMed  Google Scholar 

  3. Ǻkerstedt T, Folkard S (1995) Validation of the S and C components of the three process model of alertness regulation. Sleep 18:1–6

    PubMed  Google Scholar 

  4. Aeschbach D, Matthews JR, Postolache TT et al (1999) Two circadian rhythms in the human electroencephalogram during wakefulness. Am J Physiol (Regulatory Integrative Comp Physiol) 277:R1771–R1779

    Google Scholar 

  5. Borbély AA (1982) A two process model of sleep regulation. Hum Neurobiol 1:195–204

    PubMed  Google Scholar 

  6. Cajochen C, Brunner DP, Kräuchi K et al (1995) Power density in theta/alpha frequencies of the waking EEG progressively increases during sustained wakefulness. Sleep 18:890–894

    PubMed  CAS  Google Scholar 

  7. Czeisler CA (2011) Impact of sleepiness and sleep deficiency on public health: utility of biomarkers. J Clin Sleep Med 7(5 Suppl):6–8

    Google Scholar 

  8. Daan S, Beersma DGM, Borbély AA (1984) Timing of human sleep: recovery process gated by a circadian pacemaker. Am J Physiol (Regulatory Integrative Comp Physiol) 246:R161–R178

    Google Scholar 

  9. Dinges DF (1995) An overview of sleepiness and accidents. J Sleep Res 4(Suppl 2):4–14

    Article  PubMed  Google Scholar 

  10. Finelli LA, Baumann H, Borbely AA, Achermann P (2000) Dual electroencephalogram markers of human sleep homeostasis: correlation between theta activity in waking and slow-wave activity in sleep. Neurosci 101:523–529

    Article  CAS  Google Scholar 

  11. Frigo M, Johnson SG (2005) The design and implementation of FFTW3. Proc IEEE 93:216–231

    Article  Google Scholar 

  12. Leproult R, Colecchia EF, Berardi AM et al (2003) Individual differences in subjective and objective alertness during sleep deprivation are stable and unrelated. Am J Physiol (Regulatory Integrative Comp Physiol) 284:R280–R290

    Google Scholar 

  13. Lorenzo I, Ramos J, Arce C et al (1995) Effect of total sleep deprivation on reaction time and waking EEG activity in man. Sleep 18:346–354

    PubMed  CAS  Google Scholar 

  14. Leger D (1994) The cost of sleep-related accidents: a report for the National Commission of Sleep Disorders Research. Sleep 17:84–93

    PubMed  CAS  Google Scholar 

  15. Mitler MM, Carskadon MA, Czeisler CA et al (1988) Catastrophes, sleep, and public policy: consensus report. Sleep 11:100–109

    PubMed  CAS  Google Scholar 

  16. Makeig S, Jung TP (1995) Changes in alertness are a principal component of the variance in the EEG spectrum. Neuroreport 7:213–216

    PubMed  CAS  Google Scholar 

  17. Mullington JM, Czeisler CA, Goel N et al (2011) Panel discussion: current status of measuring sleepiness. J Clin Sleep Med 7(5 Suppl):22–25

    Google Scholar 

  18. Oken BS, Salinsky M (1992) Alertness and attention: basic science and electrophysiologic correlates. J Clin Neurophysiol 9:480–494

    Article  PubMed  CAS  Google Scholar 

  19. Putilov AA (2010) Principal component structure of wake-sleep transition: quantitative description in multiple sleep latency tests. Somnologie 14:234–243

    Article  Google Scholar 

  20. Putilov AA (2011) Prospects of using electroencephalographic signatures of the chronoregulatory processes for meaningful, parsimonious and quantitative description of the sleep-wake sub-states. Biol Rhythm Res 42:181–207

    Article  Google Scholar 

  21. Putilov AA (2011) Principal components of electroencephalographic spectrum as markers of opponent processes underlying ultradian sleep cycles. Chronobiol Int 28:287–299

    Article  PubMed  Google Scholar 

  22. Putilov AA, Donskaya OG, Verevkin EG et al (2009) Chronotype, somnotype and trototype as the predictors of the time course of subjective and objective indexes of sleepiness in sleep deprived subjects. In: Fulke P, Vaughan S (eds) Sleep deprivation: causes, effects and treatment. Nova Science, New York, pp 95–142

  23. Putilov AA, Donskaya OG, Verevkin EG, Shtark MB (2009) Structuring the inter-individual variation in waking EEG can help to discriminate between the objective markers of sleep debt and sleep pressure. Somnologie 13:72–88

    Article  Google Scholar 

  24. Quan SF (2011) Finding a research path for the identification of biomarkers of sleepiness. J Clin Sleep Med 7(5 Suppl):4–5

    Google Scholar 

  25. Quan SF, Shaw PJ, Naidoo N et al (2011) Panel discussion: can there be a biomarker for sleepiness? J Clin Sleep Med 7(5 Suppl):45–48

    Google Scholar 

  26. Samkoff JS, Jacques CH (1991) A review of studies concerning effects of sleep deprivation and fatigue on residents’ performance. Acad Med 66:687–693

    Article  PubMed  CAS  Google Scholar 

  27. Stampi C, Stone P, Michimori A (1995) A new quantitative method for assessing sleepiness: the alpha attenuation test. Work and Stress 9:368–376

    Article  Google Scholar 

  28. Strijkstra AM, Beersma DG, Drayer B et al (2003) Subjective sleepiness correlates negatively with global alpha (8–12 Hz) and positively with central frontal theta (4–8 Hz) frequencies in the human resting awake electroencephalogram. Neurosci Lett 340:17–20

    Article  PubMed  CAS  Google Scholar 

  29. Van Dongen HPA (2006) Shift work and inter-individual differences in sleep and sleepiness. Chronobiol Int 23:1139–1147

    Article  Google Scholar 

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Acknowledgments

The experiments were supported by the grants from the Russian Foundation for Basic Research and the Russian Foundation for Humanities (07-06-00263а, 08-04-01071-а, 10-06-00114-а, and 06-06-00375-a).

Conflict of interest

No statement made.

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Authors and Affiliations

  1. Research Institute for Molecular Biology and Biophysics, Siberian Branch of the Russian Academy of Medical Sciences, Novosibirsk, Russia

    O.G. Donskaya, E.G. Verevkin &  A.A. Putilov

  2. -, 11, Nipkowstr., 12489, Berlin, Germany

    A.A. Putilov

Authors
  1. O.G. Donskaya
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  2. E.G. Verevkin
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  3. A.A. Putilov
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Correspondence to A.A. Putilov.

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Donskaya, O., Verevkin, E. & Putilov, A. The first and second principal components of the EEG spectrum as the correlates of sleepiness. Somnologie 16, 69–79 (2012). https://doi.org/10.1007/s11818-012-0561-1

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  • DOI: https://doi.org/10.1007/s11818-012-0561-1

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