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Coupling of the β Rhythm and Slow Electric Activity of the Cerebral Cortex during the Performance of Go/NoGo Tasks and the Identification of the Facial Expression

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Abstract

We investigated the interaction of β-rhythm parameters with α and θ rhythms in a paradigm of cognitive set as a response on facial expression in 35 healthy adults. Data were analyzed by means of continuous wavelet transform on the basis of “maternal” complex Morlet-wavelet in a range of 1–35 Hz. Distribution cards of the values of the wavelet-transform coefficient (WLC) module characterizing potentials amplitude were analyzed. We used indicators of the mean and maximal WLC levels. A significant interaction between β2 and α rhythms at the mean WLC level at the stage of set formation was revealed in a group with rigid set, and a correlation coefficient was 0.57. The interaction between β2 and θ rhythms at the mean WLC level (correlation coefficient was 0.74) and WLC maximum (correlation coefficient was 0.8) at the same experimental stage in the group with the flexible set was found.

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References

  1. Kostandov, E.A. and Cheremushkin, E.A., Psychophysiological signs of high-flexible forms of set on the emotionally negative facial expression, Zh. Vyssh. Nervn. Deyat. im. I. P. Pavlova, 2013, vol. 63, no. 2, p.175.

    CAS  Google Scholar 

  2. Yakovenko, I.A., Cheremushkin, E.A., and Kozlov, M.K., Changes in the beta rhythm on acquisition of a set to an emotional facial expression with lengthening of the time interval between the warning and trigger stimuli, Neurosci. Behav. Physiol., 2014, vol. 44, no. 9, p. 1031.

    Article  Google Scholar 

  3. Engel, A.K., Fries, P., and Singer, W., Dynamic predictions: Oscillations and synchrony in top-down processing, Nat. Rev. Neurosci., 2001, vol. 2, no. 10, p.704.

    Article  CAS  PubMed  Google Scholar 

  4. Engel, A.K. and Fries, P., Beta-band oscillations—signalling the status quo?, Curr. Opin. Neurobiol., 2010, vol. 20, no. 2, p.156.

    Article  CAS  PubMed  Google Scholar 

  5. Yakovenko, I.A., Kozlov, M.K., and Cheremushkin, E.A., Changes in the evoked beta rhythm in the cerebral cortical hemispheres on formation of a set to an emotional facial expression in conditions of loading on working memory, Zh. Vyssh. Nervn. Deyat. im. I.P. Pavlova, 2012, vol. 62, no. 3, p.302.

    Google Scholar 

  6. Bibbig, A., Middleton, S., Racca, C., et al., Beta rhythms (15–20 Hz) generated by nonreciprocal communication in hippocampus, J. Neurophysiol., 2007, vol. 97, no. 4, p. 2812.

    Article  PubMed  Google Scholar 

  7. Linás, R.R., Grace, A.A., and Yarom, Y., In vitro neurons in mammalian cortical layer 4 exhibit intrinsic oscillatory activity in the 10-to 50-Hz frequency range, Proc. Natl. Acad. Sci. U. S. A., 1991, vol. 88, no. 3, p.897.

    Article  Google Scholar 

  8. Steriade, M., Grouping of brain rhythms in corticothalamic systems, Neuroscience, 2006, vol. 137, no. 4, p. 1087.

    Article  CAS  PubMed  Google Scholar 

  9. Uhlhaas, P.J., Haenschel, C., Nickolic, D., and Singer, W., The role of oscillations and synchrony in cortical networks and their putative relevance for the pathophysiology of schizophrenia, Schizophr. Bull., 2008, vol. 34, no. 5, p.927.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Sarnthein, J., Morel, A., and von Stein, Jeanmonod D., Thalamic theta fields potentials and EEG: High thalamocortical coherence in patients with neurogenic pain, epilepsy and movement disorders, Thalamus Relat. Syst., 2003, vol. 2, no. 3, p.231.

    Article  Google Scholar 

  11. Rodríguez-Martínez, E.I., Barriga-Paulino, C.I., Rojas-Benjumea, M.A., and Gómez, C.M., Co-maturation of theta and low-beta rhythms during child development, Brain Topogr., 2015, vol. 28, no. 2, p.250.

    Article  PubMed  Google Scholar 

  12. de Munk, J.C., Goncalves, S.I., Mammoliti, R., et al., Interaction between different EEG frequency bands and their effect on alpha-fMRI correlation, NeuroImage, 2009, vol. 47, no. 1, p.69.

    Article  Google Scholar 

  13. Roopun, A.K., Kramer, M.A., Carrasedo, L.M., et al., Temporal interaction between cortical rhythms, Front. Neuroisci., 2008, vol. 2, no. 2, p.145.

    Article  Google Scholar 

  14. Nikulin, V.V., Nolte, G., and Curio, G., Cross-frequency decomposition: A novel technique for studying interactions between neuronal oscillation with different frequencies, Clin. Neurophysiol., 2012, vol. 123, no. 7, p. 1353.

    Article  PubMed  Google Scholar 

  15. Niculin, V.V. and Brismar, T., Phase synchronization between alpha and beta oscillation in the human electroencephalogram, Neuroscience, 2006, vol. 137, no. 2, p.647.

    Article  Google Scholar 

  16. Schanze, T. and Eckhorn, R., Phase correlation among rhythms present at different frequencies: Spectral methods, application to microelectrode recordings from visual cortex and functional implications, Int. J. Psychophysiol., 1997, vol. 26, nos. 1-3, p.171.

    CAS  PubMed  Google Scholar 

  17. Tass, P.A., Fieseler, T., Dammers, J., et al., Synchronization tomography: A method for three-dimensional localization of phase synchronized neuronal population in the human brain using magnetoencephalography, Phys. Rev. Lett., 2003, vol. 90, no. 8, p. 088101.

    Article  CAS  PubMed  Google Scholar 

  18. Uznadze, D.N., Experimental basics of set psychology, in Eksperimental’nye issledovaniya po psikhologii ustanovki (Experimental Studies on the Set Psychology), Tbilisi: Izd. Akad. Nauk GSSR, 1958, p.5.

    Google Scholar 

  19. Ekman, P. and Friesen, W.V., Pictures of Facial Affect, Palo Alto, Calif.: Consult Psychol. Press, 1976.

    Google Scholar 

  20. Chik, D., Theta-alpha cross-frequency synchronization facilitates working memory control—A modeling study, Springer Plus, 2013, vol. 2, no. 14, p.1.

    Google Scholar 

  21. van der Meij, R., Kahana, M., and Maris, E., Phaseamplitude coupling in human electroencephalography is spatially distributed and phase diverse, J. Neurosci., 2012, vol. 32, no. 1, p.111.

    Article  PubMed  Google Scholar 

  22. Roux, F. and Uhlhaas, P.J., Working memory and neural oscillations: Alpha-gamma versus theta-gamma codes for distinct WM information?, Trends Cognit. Sci., 2014, vol. 18, no. 1, p.16.

    Article  Google Scholar 

  23. Astasheva, E.V., Investigation of oscillatory activity and interrelations of structures in the limbic system of the brain, Fundam. Issled., Biol. Nauki, 2011, no. 12, part 4, p.699.

    Google Scholar 

  24. Fries, P., A mechanism for cognitive dynamics: Neuronal communication through neuronal coherence, Trends Cognit. Neurosci., 2005, vol. 9, no. 10, p. 474.

    Article  Google Scholar 

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Authors and Affiliations

  1. Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Moscow, 117485, Russia

    I. A. Yakovenko, E. A. Cheremushkin & M. K. Kozlov

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  1. I. A. Yakovenko
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  2. E. A. Cheremushkin
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  3. M. K. Kozlov
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Correspondence to I. A. Yakovenko.

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Original Russian Text © I.A. Yakovenko, E.A. Cheremushkin, M.K. Kozlov, 2017, published in Fiziologiya Cheloveka, 2017, Vol. 43, No. 6, pp. 37–44.

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Yakovenko, I.A., Cheremushkin, E.A. & Kozlov, M.K. Coupling of the β Rhythm and Slow Electric Activity of the Cerebral Cortex during the Performance of Go/NoGo Tasks and the Identification of the Facial Expression. Hum Physiol 43, 637–643 (2017). https://doi.org/10.1134/S0362119717050164

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  • DOI: https://doi.org/10.1134/S0362119717050164

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