Skip to main content
Log in

EEG alpha indices depending on the menstrual cycle phase and salivary progesterone level

  • Published:
Human Physiology Aims and scope Submit manuscript

Abstract

The effects of neurohumoral status on the EEG α activity were studied in 78 women (18–27 years old) during one or two menstrual cycles using a within-subjects design. The psychometric and electroencephalographic (EEG) indices of α waves, basal body temperature, and salivary progesterone level were monitored every two or three days. The menstrual and follicular recording sessions occurred before the basal temperature rise caused by ovulation, the luteal recording session occurred after the increase in progesterone level by more than 20% compared to the day before, and the premenstrual recording sessions occurred after the decrease in progesterone level by more than 20% compared to the day before. The EEG, electromyographic (EMG) and electrocardiographic (ECG) characteristics of cognitive efficiency and psycho-emotional tension were recorded at rest and during task performance. The experiments were started in the menstrual phase in half the subjects and in the luteal phase in the other half. Psychometric characteristics, EEG α activity, EMG and ECG indices were compared for all the five phases at rest and in response to cognitive task performance. The results have shown that all psychometric and α EEG indices are menstrual-cycle-dependent. The maximum cognitive fluency, α peak frequency, α band width, and power in the α2 frequency band are observed in the luteal phase, while the maximum power in the low-frequency α1 band, as well as visual and cognitive activation calculated from α power reduction, are observed in the follicular phase of the menstrual cycle. The hypothesis that EEG α activity depends on the neurohumoral status is supported by the positive correlation of salivary progesterone level with the α peak frequency and the power in the α2 band and its negative correlation with the power in the α1 band. It is concluded that psycho-physiological recording sessions in women must be carried out with due consideration of the menstrual cycle phase.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Kaplan, B.J., Whitsett, S.F., and Robinson, J.W., Menstrual cycle phase is a potential confound in psychophysiology research, Psychophysiology, 1990, vol. 27, no. 4, p. 445.

    Article  PubMed  CAS  Google Scholar 

  2. Bazanova, O.M., Comments for current interpretation EEG alpha activity: a review and analysis, J. Behav. Brain Sci., 2012, vol. 2, no. 2, p. 239.

    Article  Google Scholar 

  3. Kaneda, Y., Ikuta, T., Nakayama, H., Kagawa, K., and Furuta, N., Visual evoked potential and electroencephalogram of healthy females during the menstrual cycle, J. Med. Invest., 1997, vol. 44, nos. 1–2, p. 41.

    PubMed  CAS  Google Scholar 

  4. Solís-Ortíz, S., Campos, R.G., Félix, J., and Obregón, O., Coincident frequencies and relative phases among brain activity and hormonal signals, Behav. Brain Funct., 2009, no. 14, p. 5.

    Google Scholar 

  5. Becker, D., Creutzfeldt, O.D., Schwibbe, M., and Wuttke, W., Changes in physiological, EEG and psychological parameters in women during the spontaneous menstrual cycle and following oral contraceptives, Psychoneuroendocrinology, 1982, vol. 7, no. 1, p. 75.

    Article  PubMed  CAS  Google Scholar 

  6. Vasil’eva, V.V., Spectral and coherent EEG characteristics in women in different phases of the menstrual cycle, Byull. Exp. Biol. Med. RAMN, 2005, no. 10, p. 374.

    Google Scholar 

  7. Güntekin, B. and Başar, E., Brain oscillations are highly influenced by gender differences, Int. J. Psychophysiol., 2007, vol. 65, no. 3, p. 294.

    Article  PubMed  Google Scholar 

  8. Crawford, F.S., Waves, McGraw-Hill, 1968.

    Google Scholar 

  9. Klimesch, W., Doppelmayr, M., Pachinger, T., and Ripper, B., Brain oscillations and human memory: EEG correlates in the upper alpha and theta band, Neurosci. Lett., 1997, vol. 238, nos. 1–2, p. 9.

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  11. Alexeeva, M.V., Balioz, N.V., Muravlyova, K.B., Sapina, E.V., and Bazanova, O.M., Training for Voluntarily Increasing Individual Upper α Power as a Method for Cognitive Enhancement, Hum. Physiol., 2012, vol. 38, no. 1, p. 40.

    Article  Google Scholar 

  12. Bazanova, O.M., and Aftanas, L.I., Learning success and individual frequency dynamic characteristics of α activity of electroencephalogram, Vestn. RAMN, 2006, vol. 6, p. 30.

    Google Scholar 

  13. Bazanova, O.M., Mernaya, E.M., and Shtark, M.B., Biocontrol in psychomotor training: electrophysiological substantiation, Ross. Fiziol. Zh. im. I.M. Sechenova, 2008, vol. 94, no. 5, p. 539.

    PubMed  CAS  Google Scholar 

  14. Klimesch, W., Sauseng, P., and Hanslmayr, S., EEG alpha oscillations: the inhibition-timing hypothesis, Brain Res. Rev., 2007, vol. 53, p. 63.

    Article  PubMed  Google Scholar 

  15. Del Percio, C., Infarinato, F., Marzano, N., et al., Reactivity of alpha rhythms to eyes opening is lower in athletes than non-athletes: a high-resolution EEG study, Int. J. Psychophysiol., 2011, vol. 82, no. 3, p. 240.

    Article  PubMed  Google Scholar 

  16. Barry, R.J., Clarke, A.R., and Johnstone, S.J., EEG differences between eyes-closed and eyes-open resting conditions, Clin. Neurophysiol., 2007, vol. 118, p. 2765.

    Article  PubMed  Google Scholar 

  17. Cacioppo, J.T., Feelings and emotions: roles for electrophysiological markers, Biol. Psychol., 2004, vol. 67, nos. 1–2, p. 235.

    Article  PubMed  Google Scholar 

  18. Livanov, M.N., Prostranstvenno-vremennaya organizatsiya potentsialov i sistemnaya deyatel’nost’ golovnogo mozga (izbrannye trudy) (Spatiotemporal Organization of Potentials and System Activity of the Brain: Selected Works), Moscow: Nauka, 1989.

    Google Scholar 

  19. Bazanova, O.M., Variability and reproducibility of individual alpha rhythm frequency of EEG depending on experimental conditions, Zh. Vyssh. Nervn. Ddeyat., 2011, vol. 61, no. 1, p. 102.

    CAS  Google Scholar 

  20. Machinskaya, R.I., Krupskaya, E.V., Kurganskii, A.V., and D’yachenko, S.D., Individual peculiarities of perception of visual hierarchic stimuli at the global and local levels under conditions of free recognition and directed attention, Zh. Vyssh. Nervn. Deyat., 2009, vol. 59, no. 5, p. 527.

    Google Scholar 

  21. Bechtereva, N.P., Bundzen, P.V., and Gogolitsyn, Yu.L., Mozgovye kody psikhicheskoi deyatel’nosti (Brain Codes of Psychic Activity), Leningrad: Nauka, 1977.

    Google Scholar 

  22. Bijleveld, E., Scheepers, D., and Ellemers, N., The cortisol response to anticipated intergroup interactions predicts self-reported prejudice, PLoS One, 2012, vol. 7, no. 3, e3368.1.

    Article  Google Scholar 

  23. Mazaheri, A., and Jensen, O., Posterior α-Activity Is not Phase-Reset by Visual Stimuli, Proc. Nat. Acad. Sci. U.S.A., 2006, vol. 103, no. 8, p. 2948.

    Article  CAS  Google Scholar 

  24. Tenke, C.E. and Kayser, J., Reference-free quantification of EEG spectra: combining current source density (CSD) and frequency principal components analysis (fPCA), Clin. Neurophysiol., 2005, vol. 116, no. 12, p. 2826.

    Article  PubMed  Google Scholar 

  25. Kaiser, D.A., Basic principles of quantitative EEG, J. Adult Dev., 2005, vol. 12, nos. 2–3, p. 99.

    Article  Google Scholar 

  26. Gingnell, M., Morell, A., Bannbers, E., Wikstrom, J., and Sundstrom Poromaa, I., Menstrual cycle effects on amygdala reactivity to emotional stimulation in premenstrual dysphoric disorder, Horm Behav., 2012, vol. 62, no. 4, p. 400.

    Article  PubMed  Google Scholar 

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

    Article  Google Scholar 

  28. Alexander, D.M., Arns, M.W., Paul, R.H., et al., EEG markers for cognitive decline in elderly subjects with subjective memory complaints, J. Integr. Neurosci., 2006, vol. 5, no. 1, p. 49.

    Article  PubMed  Google Scholar 

  29. Gordon, E., Integrative Neuroscience, Neuropsychopharmacol., 2003, vol. 28, no. 1, p. 22.

    Google Scholar 

  30. Michel, M.M. and Jacobs, R.A., Parameter learning but not structure learning: a bayesian network model of constraints on early perceptual learning, J. Vis., 2007, vol. 7, no. 1, p. 4.

    Article  PubMed  Google Scholar 

  31. Valeev, R.G., Trufakin, S.V., Aftanas, L.I., Kozlov, V.A., and Trufakin, V.A., Neuroimmune relationships in humans under conditions of physiological rest and negative emotional activation, Byull. Sib. Otd. RAMN, 2008, vol. 3, p. 46.

    Google Scholar 

  32. Brümmer, V., Schneider, S., Abel, T., Vogt, T., and Struder, H.K., Brain cortical activity is influenced by exercise mode and intensity, Med. Sci. Sports Exerc., 2011, vol. 43, no. 10, p. 1863.

    Article  PubMed  Google Scholar 

  33. Doppelmayr, M., Klimesch, W., Sauseng, P., et al., Intelligence related differences in EEG-bandpower, Neurosci. Lett., 2005, vol. 381, no. 3, p. 309.

    Article  PubMed  CAS  Google Scholar 

  34. Bazanova, O.M., and Mernaya, E.M., Alpha-activity fluctuations in various hormonal states and associated with them musical performance proved differently in the opposite individual alpha peak frequency groups, Rev. Espan. Neuropsicol., 2008, vol. 10, no. 1, p. 100.

    Google Scholar 

  35. Hummel, F., Saur, R., Lasogga, S., et al., To act or not to act: neural correlates of executive control of learned motor behavior, NeuroImage, 2004, no. 23, p. 1391.

    Google Scholar 

  36. Baulieu, E.E., Schumacher, M., Koenig, H., et al., Progesterone as a neurosteroid: actions within the nervous system, Cell Mol. Neurobiol., 1996, vol. 16, no. 2, p. 143.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

Original Russian Text © O.M. Bazanova, A.V. Kondratenko, O.I. Kuzminova, K.B. Muravlyova, S.E. Petrova, 2014, published in Fiziologiya Cheloveka, 2014, Vol. 40, No. 2, pp. 31–40.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bazanova, O.M., Kondratenko, A.V., Kuzminova, O.I. et al. EEG alpha indices depending on the menstrual cycle phase and salivary progesterone level. Hum Physiol 40, 140–148 (2014). https://doi.org/10.1134/S0362119714020030

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0362119714020030

Keywords

Navigation