[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Springer Nature Link
Log in

Relationships between the EEG θ- and β-parameters and heart rate variability during human cognitive performance

  • Published:
Human Physiology Aims and scope Submit manuscript

Abstract

We studied the dynamics of spectral coherence characteristics of the EEG θ-, β1-, and β2-activity and the heart rate variability (HRV) in subjects performing cognitive tests. We found an association between the HRV parameters in the process of cognitive activity and the coherence of potentials in the EEG θ-, β1-, and β2-bands. The heart rate parameters in the baseline state and during the test performance best correlated with the levels of the right-hemispheric coherence of potentials in the θ-, β1-, and β2-bands of the baseline EEG (eyes closed). The higher coherence levels corresponded to lower values of the mean time of RR intervals (RRNN), coefficient of variation (CV), total power (TP), the power of the high-frequency (HF) and low-frequency (LF) components in the HRV spectrum. During the performance of the test, higher coherence values in the EEG θ-bands with the focus in the right temporal lead corresponded to higher LF/HF values reflecting the predominance of sympathetic effects on heart rate.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Basar, E., Oscillations in “brain-body-mind”–a holistic view including the autonomous system, Brain Res., 2008, vol. 1235, p. 2.

    Article  CAS  PubMed  Google Scholar 

  2. Bazanova, O.M., Balioz, N.V., Muravleva, K.B., and Skoraya, M.V., Effect of voluntary EEG a power increase training on heart rate variability, Hum. Physiol., 2013, vol. 39, no. 1, p. 86.

    Article  Google Scholar 

  3. Danilova, N.N. and Astaf’ev, S.V., Human attention as a specific connection between EEG rhythms and heart rate wave modulators, Zh. Vyssh. Nervn. Deyat. im. I.P. Pavlova, 2000, vol. 50, no. 5, p. 791.

    CAS  Google Scholar 

  4. Dzhebrailova, T.D., Korobeinikova, I.I., Karatygin, N.A., and Dudnik, E.N., Dynamics of EEG a activity and heart rate variability in subjects performing cognitive tests, Hum. Physiol., 2015, vol. 41, no. 6, p. 599.

    Article  Google Scholar 

  5. Klimesch, W., EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis, Brain Res. Rev., 1999, vol. 29, nos. 2–3, p. 169.

    Article  CAS  PubMed  Google Scholar 

  6. Sauseng, P., Klimesch, W., Heise, K.F., et al., Brain oscillatory substrates of visual short-term memory capacity, Curr. Biol., vol. 19, no. 21, p. 1846.

  7. Aftanas, L.I., Brak, I.V., Reva, N.V., and Pavlov, S.V., Brain oscillator systems and individual variability in the defensive cardiac reflex in humans, Ross. Fiziol. Zh. im. I.M. Sechenova, 2013, vol. 99, no. 11, p. 1342.

    CAS  PubMed  Google Scholar 

  8. Pulvermüller, F., Birbaumer, N., Lutzenberger, W., and Mohr, B., High-frequency brain activity: its possible role in attention, perception and language processing, Prog. Neurobiol., 1997, vol. 52, p. 427.

    Article  PubMed  Google Scholar 

  9. Kozhedub, R.G., Sviderskaya, N.E., and Taratynova, G.V., Spatial organization of biopotentials and original features of visual images, Zh. Vyssh. Nervn. Deyat. im. I. P. Pavlova, 2006, vol. 56, no. 4, p. 437.

    CAS  Google Scholar 

  10. Volf, N.V., Razumnikova, O.M., and Tarasova, I.V., EEG-mapping study of sex differences during verbal creative thinking, in Focus Brain Research, Resch, C.J., Ed., New York: Nova Sci. Publ., 2007, p. 123.

    Google Scholar 

  11. Machinskaya, R.I. and Kurganskii, A.V., A comparative electrophysiological study of regulatory components of working memory in adults and seven- to eightyear- old children: an analysis of coherence of EEG rhythms, Hum. Physiol., 2012, vol. 38, no. 1, p. 1.

    Article  Google Scholar 

  12. Osnovy psikhologii (Fundamentals of Psychology), Stolyarenko, L.D., Ed., Rostov-on-Don: Feniks, 2000.

  13. Mitrofanov, A.A., Computer system of analysis and topographic mapping of the brain electrical activity with neurometric bank of EEG data “Brainsys”. Description of use. Handbook of system operator. Handbook of system programmer, in Nauchno-meditsinskaya firma “Statokin” (Scientific and Medical Company “Statokin”), Moscow, 2015.

    Google Scholar 

  14. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, Circulation, 1996, vol. 93, no. 5, p. 1043.

  15. Mikhailov, V.M., Variabel’nost’ ritma serdtsa: opyt prakticheskogo primeneniya metoda (Heart Rate Variability: Experience of Practical Application of the Method), Ivanovo: Ivanov. Gos. Med. Akad., 2002.

    Google Scholar 

  16. Mashin, V.A., Variabel’nost’ serdechnogo ritma: trekhfaktornaya model’ VSR v issledovaniyakh funktsional’nykh sostoyanii cheloveka (Heart Rate Variability: The Three-factor Model of HRV in Investigations of Human Functional States), Lambert Acad. Publ., 2012, p. 580.

    Google Scholar 

  17. Rebrova, O.Yu., Statisticheskii analiz meditsinskikh dannykh. Primenenie paketa prikladnykh programm Statistica (Statistical Analysis of Medical Data. Application of the Statistica Software Package), Moscow: MediaSfera, 2002.

    Google Scholar 

  18. Biryukova, E.V., Kazakova, V.V., Vasilyuk, N.A., and Andrianov, V.V., Physiological indices of students performing educational tests, Sechenovskii Vestn., 2013, no. 4(14), p. 35.

    Google Scholar 

  19. Baevskii, R.M., Estimation and prediction of functional changes in organisms in space flight, Usp. Fiziol. Nauk, 2006, vol. 37, no. 3, p. 42.

    CAS  PubMed  Google Scholar 

  20. Dzhebrailova, T.D., Suleimanova, R.G., Ivanova, L.I., and Ivanova, L.V., Individual specificity of the autonomic support of purposive activity in students performing computer-aided tests, Hum. Physiol., 2012, vol. 38, no. 5, p. 500.

    Article  Google Scholar 

  21. Dzhebrailova, T.D., Korobeinikova, I.I., Dudnik, E.N., and Karatygin, N.A., Autonomic correlates of individual differences in human intellectual activity, Hum. Physiol., 2013, vol. 39, no. 1, p. 78.

    Article  Google Scholar 

  22. Dzhebrailova, T.D. and Korobeinikova, I.I., Spatial organization of EEG ß-2 rhythm and efficiency of human cognitive activity, Zh. Vyssh. Nervn. Deyat. im. I.P. Pavlova, 2013, vol. 63, no. 6, p. 667.

    CAS  Google Scholar 

  23. Boldyreva, G.N., Zhavoronkova, L.A., Sharova, E.V., and Dobronravova, I.S., Intracerebral EEG functioning as a reflexion of the systemic brain organization in norm and pathology, Zh. Vyssh. Nervn. Deyat. im. I.P. Pavlova, 2003, vol. 53, no. 4, p. 391.

    CAS  Google Scholar 

  24. Livanov, M.N. and Dumenko, V.I., Neurophysiological aspects of studies of the systems organization of brain activity, Usp. Fiziol. Nauk, 1987, vol. 18, no. 3, p. 6.

    CAS  PubMed  Google Scholar 

  25. Batuev, A.S. and Iovleva, N.N., A change in the EEG spectral coherent characteristics in the early postnatal period in mothers with the anxious-depressive background mood, Zh. Vyssh. Nervn. Deyat. im. I. P. Pavlova, 2003, vol. 53, no. 6, p. 712.

    CAS  Google Scholar 

  26. Heller, W. and Nitschke, J.B., Regional brain activity and emotion: a framework for understanding cognition in depression, Cognit. Emotion, 1997, vol. 11, nos. 5–6, p. 637.

    Article  Google Scholar 

  27. Luriya, A.R., Vysshie korkovye funktsii i ikh narusheniya pri lokal’nykh porazheniyakh mozga (Higher Human Cortical Functions and Their Disorders in Local Brain Lesions), Moscow: Izd. Mosk. Gos. Univ., 1962.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Anokhin Research Institute of Normal Physiology, Moscow, Russia

    T. D. Dzhebrailova, I. I. Korobeinikova, N. A. Karatygin & E. N. Dudnik

  2. Sechenov First Moscow State Medical University, Moscow, Russia

    T. D. Dzhebrailova & E. N. Dudnik

Authors
  1. T. D. Dzhebrailova
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. I. I. Korobeinikova
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. N. A. Karatygin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. E. N. Dudnik
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to T. D. Dzhebrailova.

Additional information

Original Russian Text © T.D. Dzhebrailova, I.I. Korobeinikova, N.A. Karatygin, E.N. Dudnik, 2017, published in Fiziologiya Cheloveka, 2017, Vol. 43, No. 2, pp. 91–105.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dzhebrailova, T.D., Korobeinikova, I.I., Karatygin, N.A. et al. Relationships between the EEG θ- and β-parameters and heart rate variability during human cognitive performance. Hum Physiol 43, 199–212 (2017). https://doi.org/10.1134/S0362119717010030

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0362119717010030

Keywords

Search

Navigation