Synchronization of EEG Theta and Alpha Rhythms in an Unconscious Set to the Perception of an Emotional Facial Expression

  • É. A. Kostandov
  • N. S. Kurova
  • E. A. Cheremushkin
  • N. E. Petrenko
  • M. L. Ashkinazi
Article

Abstract

Coherence functions in cortical electrical potentials in the theta (4–7 Hz) and alpha ranges (8–13 Hz) recorded during the formation and testing stages of a visual set to facial images bearing an emotional expression (an angry face) were studied in healthy adult subjects (n = 35). Differences in the spatial synchronization between theta and alpha potentials were seen, especially in rigid forms of the set, in which cases of erroneous perception of facial expressions were seen with contrast and assimilative illusions. This group of subjects (n = 23) showed increases in theta potentials between the dorsolateral areas of the frontal cortex (the orbitofrontal cortex) and the temporal area in the right hemisphere. A mechanism is proposed for the development of visual illusions. Analysis of the coherence functions of cortical potentials in the theta and alpha ranges generates a “window” which can be used to study the operation of the two functional systems integrating brain activity, i.e., the corticohippocampal and frontothalamic, in the perception of a facial expression. The frontothalamic system is associated with more diffuse types of cortical activation, especially in its anterior areas. The theta rhythm system evidently facilitates integration of the frontal cortex with the temporal area in the right hemisphere and the connections of the latter with the parietal and central zones in both hemispheres.

Key words

alpha rhythm theta rhythm coherence of potentials recognition of facial expressions descending influences cognitive set internal states unconscious prefrontal cortex orbitofrontal cortex temporal cortex corticohippocampal and frontothalamic integration systems 

References

  1. 1.
    J. Bendat and A. Piersol, Measurement and Analysis of Random Data [Russian translation], Mir, Moscow (1989).Google Scholar
  2. 2.
    É. A. Kostandov, N. S. Kurova, E. A. Cheremushkin, I. A. Yakovenko, N. E. Petrenko, and M. L. Ashkinazi, “The set as a regulatory factor in the recognition of facial emotional expressions,” Zh. Vyssh. Nerv. Deyat., 56, No. 5, 581–589 (2006).Google Scholar
  3. 3.
    É. A. Kostandov, N. S. Kurova, E. A. Cheremushkin, and N. E. Petrenko, “Dynamics of the spatial organization of cortical electrical activity during the formation and actualization of a cognitive set to facial expressions,” Zh. Vyssh. Nerv. Deyat., 57, No. 1, 33–42 (2007).Google Scholar
  4. 4.
    M. N. Livanov and V. N. Dumenko, “Neurophysiological aspects of studies of the systems organization of brain activity,” in: Temporospatial Organization of Potentials and Systems Activity in the Brain [in Russian], P. V. Simonov (ed.), Nauka, Moscow (1989), pp. 229–248.Google Scholar
  5. 5.
    R. I. Machinskaya, “Neurophysiological mechanisms of voluntary attention (an analytical review),” Zh. Vyssh. Nerv. Deyat., 53, No. 2, 133–151 (2003).Google Scholar
  6. 6.
    D. N. Uznadze “Experimental bases of the psychological set,” in: Experimental Studies in the Psychology of the Set [in Russian], Academy of the Georgian SSR Press, Tbilisi (1958), pp. 5–126.Google Scholar
  7. 7.
    D. A. Farber, T. G. Beteleva, A. S. Gorev, N. V. Dubrovinskaya, and R. I. Machinskaya, “Functional organization of the developing brain in the formation of cognitive activity,” in: Developmental Physiology in Children [in Russian], M. M. Bezrukikh and D. A. Farber (eds.), NPO Obrazovanie ot A do Ya, Moscow (2000), pp. 82–103.Google Scholar
  8. 8.
    C. Andrew and G. Pfurtscheller, “Event-related coherence as a tool for studying dynamic integration of brain regions,” EEG Clin. Neurophysiol., 98, No. 2, 144–148 (1996).CrossRefGoogle Scholar
  9. 9.
    M. Bar, M. Neta, and H. Linz, “Very first impressions,” Emotion, 6, No. 2, 269–278 (2006).CrossRefPubMedGoogle Scholar
  10. 10.
    M. Bastiansen and P. Hagoort, “Event-induced theta responses as a window on the dynamics of memory,” Cortex, 39, 967–992 (2003).CrossRefGoogle Scholar
  11. 11.
    J. B. Caplan, J. R. Marsden, A. Schulze-Bonhage, R. Aschenbrenner-Scheibe, E. L. Newman, and M. L. Kahana, “Human thetaoscillations related to sensorimotor integration and spatial learning,” J. Neurosci., 23, No. 11, 4726–4736 (2003).PubMedGoogle Scholar
  12. 12.
    P. Ekman and W. V. Frisen, Pictures of Facial Affect, Consulting Psychological Press, Palo Alto (CA) (1976).Google Scholar
  13. 13.
    H. Fisher, J. Sandblom, J. Gavazzeni, P. Franson, Ch. Wright, and Y. Bäckman, “Age-differential patterns of brain activation during perception of angry faces,” Neurosci. Lett., 386, 99–104 (2005).CrossRefGoogle Scholar
  14. 14.
    M. A. Guevara and M. Corsi-Carbera, “EEG coherence or EEG correlation?” Int. J. Psychophysiol., 23, No. 3, 145–153 (1996).CrossRefPubMedGoogle Scholar
  15. 15.
    M. E. Hasselmo and H. Eichenbaum, “Hippocampal mechanisms for the context-depended retrieval of episodes,” Neural Networks, 18, 1172–1190 (2005).CrossRefPubMedGoogle Scholar
  16. 16.
    I. G. Kirk and J. C. Mackay, “The role of theta-range oscillations in synchronizing and integrating activity in distributed mnemonic networks,” Cortex, 39, 993–1008 (2003).CrossRefPubMedGoogle Scholar
  17. 17.
    W. Klimesch, “EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis,” Brain Res. Rev., 29, 169–195 (1999).CrossRefPubMedGoogle Scholar
  18. 18.
    K. Kveraga, A. S. Ghuman, and M. Bar, “Top-down predictions in the cognitive brain,” Brain Cog., 65, No. 2, 145–168 (2007).CrossRefGoogle Scholar
  19. 19.
    M. Molle, L. Marshall, J. L. Fehm, and J. Born, “EEG theta synchronization conjoined with alpha desynchronisation indicate intentional encoding,” Eur. J. Neurosci., 15, No. 5, 923–928 (2002).CrossRefPubMedGoogle Scholar
  20. 20.
    K. A. Paller, Ch. Ranganath, R. Gonsalves, K. S. Yabar, T. B. Parrash, D. R. Gitelman, M. Marsel-Mesulam, and P. J. Reber, “Neural correlates of person recognition,” Learn. Mem., 10, 253–260 (2003).CrossRefPubMedGoogle Scholar
  21. 21.
    P. Rappelsberger, D. Lacroix, and H. Petsche, “Amplitude and coherence mapping: its application in psycho- and pathophysiological studies,” in: Quantitative EEG Analysis – Clinical Utility and New Methods, M. Roter and U. Zwiener (eds.), Universitatsverlag, Jena (1993), pp. 179–186.Google Scholar
  22. 22.
    P. Rappelsberger, “Probability mapping of power and coherence: Technical aspects,” in: EEG and Thinking, H. Petsche and S. Etlinger (eds.), Oesterreichische Akad. Wissenschaften, Vienna (1998), pp. 63–78.Google Scholar
  23. 23.
    K. Sergerie, M. Lepage, and J. Y. Armony, “A face to remember: emotional expression modulates prefrontal activity during memory formation,” Neuroimage, 24, 580–585 (2005).CrossRefPubMedGoogle Scholar
  24. 24.
    H. Tomita, M. Ohbayashi, K. Nakahara, I. Hasegava, and Y. Miyashita, “Top-down signal from prefrontal cortex in executive control of memory retrieval,” Nature, 401, 699–703 (1999).CrossRefPubMedGoogle Scholar
  25. 25.
    L. M. Williams, K. J. Brown, P. Das, W. Boucsein, E. N. Sokolov, M. J. Brammer, Olivieri, A. S. Reduto, and E. Gordon, “The dynamics of cortico-amygdalar and autonomic activity over the experimental time course of fear perception,” Cog. Brain Res., 21, 114–123 (2004).CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2009

Authors and Affiliations

  • É. A. Kostandov
    • 1
  • N. S. Kurova
    • 1
  • E. A. Cheremushkin
    • 1
  • N. E. Petrenko
    • 2
  • M. L. Ashkinazi
    • 1
  1. 1.Institute of Higher Nervous Activity and NeurophysiologyRussian Academy of SciencesMoscowRussia
  2. 2.Institute of Age PhysiologyRussian Academy of EducationMoscowRussia

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