The site of the Media Sphera Publishers contains materials intended solely for healthcare professionals.
By closing this message, you confirm that you are a certified medical professional or a student of a medical educational institution.

Login
EN
+7 (495) 482-4118
+7 (495) 482-0604
+8 800 250-18-12
  • (toll-free number for subscriptions)
    Mon-Fri from 10 a.m. to 6 p.m.

  • © 1998-2025
+7 (495) 482-43-29
EN
All journals
Journal
Year
Year
Search result: 0

Puchkova A.N.

Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences

Tkachenko O.N.

Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences

Gandina E.O.

Institute of Higher Nervous Activity and Neurophysiology

Shumov D.E.

Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences

High individual stability of daytime sleep EEG characteristics in nighttime sleep restriction settings

Authors:

Puchkova A.N., Tkachenko O.N., Gandina E.O., Shumov D.E.

More about the authors

Journal: S.S. Korsakov Journal of Neurology and Psychiatry. 2025;125(5‑2): 22‑26

DOI: 10.17116/jnevro202512505222

Read: 690 times

Buy for 300₽
Contact the author
Table of contents

HIGH INDIVIDUAL STABILITY OF DAYTIME SLEEP EEG CHARACTERISTICS IN NIGHTTIME SLEEP RESTRICTION SETTINGS
HIGH INDIVIDUAL STABILITY OF DAYTIME SLEEP EEG CHARACTERISTICS IN NIGHTTIME SLEEP RESTRICTION SETTINGS

To cite this article:

Puchkova AN, Tkachenko ON, Gandina EO, Shumov DE. High individual stability of daytime sleep EEG characteristics in nighttime sleep restriction settings. S.S. Korsakov Journal of Neurology and Psychiatry. 2025;125(5‑2):22‑26. (In Russ.)
https://doi.org/10.17116/jnevro202512505222

Подписка 2026 Журнал неврологии и психиатрии им. С.С. Корсакова. Спецвыпуски (S.S. Korsakov Journal of Neurology and Psychiatry (special issues))
 
МСФ на ЯМ
Использование инфографики авторами научных работ
Recommended articles:
Factors of depression acco­rding to acti­graphy in the fall season. S.S. Korsakov Journal of Neurology and Psychiatry. 2025;(5-2):27-32
Psycho-emotional state and self-reported sleep quality in students with bimo­dality of the ability to be active in the morning and evening in the sleep—wake cycle. S.S. Korsakov Journal of Neurology and Psychiatry. 2025;(7):130-134
Abstract:

OBJECTIVE

To evaluate the stability of the electroencephalogram (EEG) spectral characteristics of daytime sleep with moderate nighttime sleep deprivation.

MATERIAL AND METHODS

The study included 44 students without sleep disorders. The participants limited the nighttime sleep the day before the experiment to 5 hours; then, polysomnograms of a 90-minute daytime sleep were recorded in three repeated sessions. The obtained records were visually staged by experts. Spectral analysis of the wave amplitudes in the delta, theta, alpha, and sigma ranges and averaging for N1, N2, and N3 sleep phases in each record were performed. Stability was assessed through intra-group correlation coefficient (ICC).

RESULTS

N1 phase showed moderate individual stability (ICC 0.42—0.52) for all wave amplitudes except the sigma waves (ICC=0.68). In N2 phase, stability was increased: the sigma wave amplitude reached ICC=0.91 and 0.7—0.72 for theta and alpha wave amplitudes. In N3 phase, the delta and theta waves showed high stability (ICC=0.92—0.95). Sigma waves in the N3 phase were less stable. The results were consistent with those obtained for nighttime sleep: the sigma and delta waves were highly stable. Sigma waves (associated with sleep spindles) are most stable in N2; the delta and theta activity in N3. These observations show that despite external impacts, daytime sleep maintains intact individual neurophysiological patterns.

CONCLUSION

Daytime sleep demonstrates significant stability in the EEG spectral characteristics, especially in the deeper phases. Single EEG recording can be used in assessing individual sleep patterns, which is important for developing personalized approaches to improve the effects of sleep deprivation.

Keywords:

daytime sleep
individual characteristics
EEG spectral analysis
sleep stability

Authors:

Puchkova A.N.

Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences

Tkachenko O.N.

Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences

Gandina E.O.

Institute of Higher Nervous Activity and Neurophysiology

Shumov D.E.

Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences

Received:

20.02.2025

Accepted:

21.02.2025

Close metadata

References:

  1. Putilov AA, Sveshnikov DS, Bakaeva ZV, et al. Evening chronotype, insufficient weekday sleep, and weekday-weekend gap in sleep times: What is really to blame for a reduction in self-perceived health among university students? Chronobiology International. 2023;40(7):874-884.  https://doi.org/10.1080/07420528.2023.2222797
  2. Seoane HA, Moschetto L, Orliacq F, et al. Sleep disruption in medicine students and its relationship with impaired academic performance: a systematic review and meta-analysis. Sleep Medicine Reviews. 2020;53:101333. https://doi.org/10.1016/j.smrv.2020.101333
  3. Souabni M, Hammouda O, Romdhani M, et al. Benefits of Daytime Napping Opportunity on Physical and Cognitive Performances in Physically Active Participants: A Systematic Review. Sports Medicine. 2021;51(10):2115-2146. https://doi.org/10.1007/s40279-021-01482-1
  4. Poluektov MG, Narbut AM, Dorokhov VB. Daytime napping and its effects on memory consolidation. S.S. Korsakov Journal of Neurology and Psychiatry. 2020;120(8):127-132. (In Russ.). https://doi.org/10.17116/jnevro2020120081127
  5. Dutheil F, Danini B, Bagheri R, et al. Effects of a Short Daytime Nap on the Cognitive Performance: A Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health. 2021;18(19):10212. https://doi.org/10.3390/ijerph181910212
  6. Gander P, Signal L, Van Dongen HP. Stable inter-individual differences in slow-wave sleep during nocturnal sleep and naps. Sleep and Biological Rhythms. 2010;8(4):239-244.  https://doi.org/10.1111/j.1479-8425.2010.00454.x
  7. Perkinson-Gloor N, Hagmann-von Arx P, Brand S, et al. Intraindividual long-term stability of sleep electroencephalography in school-aged children. Sleep Medicine. 2015;16(11):1348-1351. https://doi.org/10.1016/j.sleep.2015.07.025
  8. De Gennaro L, Marzano C, Fratello F. The electroencephalographic fingerprint of sleep is genetically determined: a twin study. Annals of Neurology. 2008;64(4):455-460.  https://doi.org/10.1002/ana.21434
  9. Buckelmüller J, Landolt HP, Stassen HH, et al. Trait-like individual differences in the human sleep electroencephalogram. Neuroscience. 2006;138(1):351-356.  https://doi.org/10.1016/j.neuroscience.2005.11.005
  10. De Gennaro L, Ferrara M, Vecchio F et al. An electroencephalographic fingerprint of human sleep. NeuroImage. 2005;26(1):114-122.  https://doi.org/10.1016/j.neuroimage.2005.01.020
  11. Tan X, Campbell IG, Palagini L, et al. High internight reliability of computer-measured NREM delta, sigma, and beta: biological implications. Biological Psychiatry. 2000;48(10):1010-1019. https://doi.org/10.1016/S0006-3223(00)00873-8
  12. Ong JL, Lo JC., Patanaik A, et al. Trait‐like characteristics of sleep EEG power spectra in adolescents across sleep opportunity manipulations. Journal of Sleep Research. 2019;28(5):e12824. https://doi.org/10.1111/jsr.12824
  13. Mullins AE, Pehel S, Parekh A, et al. The stability of slow-wave sleep and EEG oscillations across two consecutive nights of laboratory polysomnography in cognitively normal older adults. Journal of Sleep Research. 2024;e14281. https://doi.org/10.1111/jsr.14281
  14. Tarokh L, Rusterholz T, Achermann P, et al. The spectrum of the non-rapid eye movement sleep electroencephalogram following total sleep deprivation is trait-like. Journal of Sleep Research. 2015;24(4):360-363.  https://doi.org/10.1111/jsr.12279
  15. Gaines J, Vgontzas AN, Fernandez-Mendoza J, et al. Short- and Long-Term Sleep Stability in Insomniacs and Healthy Controls. Sleep. 2015;38(11):1727-1734. https://doi.org/10.5665/sleep.5152
  16. Shi Y, Ren R, Zhang Y, et al. High stability of EEG spectral power across polysomnography and multiple sleep latency tests in good sleepers and chronic insomniacs. Behavioural Brain Research. 2024;463:114913. https://doi.org/10.1016/j.bbr.2024.114913
  17. Poon JJY, Chapman JL, Wong KKH, et al. Intra‐individual stability of NREM sleep quantitative EEG measures in obstructive sleep apnea. Journal of Sleep Research. 2019;28(6):e12838. https://doi.org/10.1111/jsr.12838
  18. Valdez P, Ramírez C, García A. Circadian rhythms in cognitive performance: implications for neuropsychological assessment. ChronoPhysiology and Therapy. 2012;2:81-92.  https://doi.org/10.2147/CPT.S32586
  19. Borbély AA, Daan S, Wirz‐Justice A, et al. The two‐process model of sleep regulation: a reappraisal. Journal of Sleep Research. 2016;25(2):131-143.  https://doi.org/10.1111/jsr.12371
  20. Fushimi A, Hayashi M. Pattern of slow-wave sleep in afternoon naps. Sleep and Biological Rhythms. 2008;6(3):187-189.  https://doi.org/10.1111/j.1479-8425.2008.00350.x
  21. Putilov A, Sveshnikov D, Yakunina E, et al. How to quantify sleepiness during an attempt to sleep? Physiological Measurement. 2024;45(9):5008. https://doi.org/10.1088/1361-6579/ad7930
  22. Puchkova AN, Gandina EO, Tkachenko ON. Individual stability of daytime sleep structure in subjects without sleep disorders. Environment and Human: Ecological Studies. 2024;14(3):376-390. (In Russ.). https://doi.org/10.31862/2500-2961-2024-14-3-376-390
  23. Gramfort A. MEG and EEG data analysis with MNE-Python. Frontiers in Neuroscience. 2013;7(267). https://doi.org/10.3389/fnins.2013.00267
  24. Liljequist D, Elfving B, Skavberg Roaldsen K. Intraclass correlation — A discussion and demonstration of basic features. PLoS ONE. 2019;14(7):e0219854. https://doi.org/10.1371/journal.pone.0219854
  25. Tucker AM, Dinges DF, Van Dongen HPA. Trait interindividual differences in the sleep physiology of healthy young adults. Journal of Sleep Research. 2007;16(2):170-180.  https://doi.org/10.1111/j.1365-2869.2007.00594.x
  26. Stokes PA, Rath P, Possidente T, et al. Transient oscillation dynamics during sleep provide a robust basis for electroencephalographic phenotyping and biomarker identification. Sleep. 2023;46(1):zsac223. https://doi.org/10.1093/sleep/zsac223
  27. Ambrosius U, Lietzenmaier S, Wehrle R, et al. Heritability of Sleep Electroencephalogram. Biological Psychiatry. 2008;64(4):344-348.  https://doi.org/10.1016/j.biopsych.2008.03.002
Contact the author
Email
Message
The publishing house "Media Sphere" does not provide treatment services, does not give recommendations on contacting medical institutions and specific specialists, on the prescription of medicines and dietary supplements.

Email Confirmation

An email was sent to test@gmail.com with a confirmation link. Follow the link from the letter to complete the registration on the site.

Email Confirmation

Contact us
If you have any questions, complaints or suggestions, please use this feedback form.
Email
Message
The publishing house "Media Sphere" does not provide treatment services, does not give recommendations on contacting medical institutions and specific specialists, on the prescription of medicines and dietary supplements.
Submit Application

You can become an author of one of our magazines, send a request and we will consider it in during the day.

Name
Phone
E-mail
Message
Login
Registration
E-mail
Password
Forgot Password?

Log in to the site using your account in one of the services

Password recovery
E-mail
Login
Register

We use cооkies to improve the performance of the site. By staying on our site, you agree to the terms of use of cооkies. To view our Privacy and Cookie Policy, please. click here.