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Fractal characteristics of the functional state of the brain in patients with anxiuos phobic disorders

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Abstract

The task of estimating the functional state of the CNS with the pain syndrome in patients with anxious phobic disorders is examined. For solving the task, the methods of spectral and multifractal analyses of EEG segments are applied during the perception of psychogenic pain and its removal by the psychorelaxation technique. It has been demonstrated that contrary to power spectra, singularity spectra allow distinguishing EEGs quantitatively in the examined functional states of the brain. Pain suppression in patients with anxious phobic disorders during psychorelaxation is accompanied by changing the width of the singularity spectrum and approximation of the multifractal parameter to the value corresponding to healthy subjects.

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References

  1. Karvasarsky, B.D., Encyclopedia of Psychotherapy, St. Petersburg, Ed. Piter, 2002.

  2. Ishinova, V.A. and Svyatogor, I.A., Color Reflection of Pain in Patients with Anxious Phobic Disorders, Vestnik Mecnikov Spb. Med. Academy, 2009, vol. 31, no. 2, p. 198.

    Google Scholar 

  3. Ishinova, V.A., Svyatogor, I.A., and Reznikova, T.N., Features of Color Reflection in Psychogenic Pain in Patients with Somatoform Disorders during Psychotherapeutic Treatment, Spanish J. Psychology, 2009, vol. 12, no. 2, p. 715.

    Google Scholar 

  4. Nurujjaman, M., Narayanan, R., and Sekar Iyengar, A.N., Comparative Study of Nonlinear Properties of EEG Signals of Normal Persons and Epileptic Patients, Nonlinear Biomedical Physics, 2009, vol. 3, p. 6.

    Article  PubMed  Google Scholar 

  5. Acharya, U.R., Faust, O., Kannathal, N., et al., Nonlinear Analysis of EEG Signals at Various Sleep Stages, Comput Methods Programs Biomed., 2005, vol. 80, p. 37.

    Article  Google Scholar 

  6. Popivanov, D., Stomonyakov, V., Minchev, Z., et. al., Multifractality of Decomposed EEG during Imaginary and Real Visual-Motor Tracking, Biological Cybernetics, 2006, vol. 94, p. 149.

    Article  PubMed  CAS  Google Scholar 

  7. Mandelbrot, B.B., The Fractal Geometry of Nature, Freeman, W.H., Ed., San Francisco, 1983.

  8. Natarajan, K., Acharya, R., Alias, F., et al., Nonlinear Analysis of EEG Signals at Different Mental States, BioMedical Engineering, 2004, vol. 3, p. 7.

    Google Scholar 

  9. Indiradev, K.P., Elias, E., and Sathidevi, P.S., Complexity Analysis of Electroencephalogram Records of Epileptic Patients Using Hurst Exponent, J. Medical Engineering and Informatics, 2009, vol. 1, p. 368.

    Article  Google Scholar 

  10. Song, I.H. and Lee, D.S., Fluctuation Dynamics in Electroencephalogram Time Series, in Lecture Notes in Computer Sci., Mira, J. and ’Alvarez, J.R., Eds., Berlin: Springer-Verlag, Berlin, 2005, p. 208.

    Google Scholar 

  11. Svyatogor, I.A., Classification of EEG Patterns and Their Neurophysiological Interpretation in Dezadaptation Disorders, Biological Obratnaya Svyaz, 2000, vol. 3, no. 3, p. 10.

    Google Scholar 

  12. Svyatogor, I.A., Mochovikova, I.A., Bekshaev, S.S., and Nozdrachev, A.D., Estimation of Neurophysiological Mechanisms of Dezadaptation Disorders by EEG Patterns, J. High Nervours Activity, 2005, vol. 55, no. 2, p. 164.

    Google Scholar 

  13. Marpl, S.L., Digital and Spectral Analysis and Its Applications, Moscow: Mir, 1990.

    Google Scholar 

  14. Bacry, E., Muzy, J.F., and Arneodo, A., Singularity Spectrum of Fractal Signals: Exact Results, J. Statist. Phys., 1993, vol. 70, p. 635.

    Article  Google Scholar 

  15. Arneodo, A., Bacry, E., and Muzy, J.F., The Thermodynamics of Fractals Revisited with Wavelets, Physica A, 1995, vol. 213, p. 232.

    Article  CAS  Google Scholar 

  16. Schultz, J., Das autogene Training [The Autogenic Training], Ed. Thieme, Stutgart, 1973.

    Google Scholar 

  17. Lugova, A.M., Method of Correction of Psychoemotional State, Patent RF, no. 2313282.

  18. Sokolova, E.I., Method of Determination of Psychological State of a Person in Life, Patent RF, no. 2304985.

  19. Zirmunskaya, E.A., Clinical Electroenchephalographia, Moscow, 1991.

  20. Zirmunskaya, E.A., In Searching Explanations of EEG Featutres, Moscow: Medicine, 1996.

    Google Scholar 

  21. Grindel, O.M. and Sazonova, O.B., Introduction into Clinical EEG, Neurophysiological Studies in Clinic, Moscow: Antidor, 2001, p. 13.

    Google Scholar 

  22. Boldyreva, G.N., Electrical Activity of the Human Brain in Disruptions of Diencephal and Limbic Structures, Moscow: Nauka, 2000, p. 181.

    Google Scholar 

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Correspondence to O. E. Dick.

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Original Russian Text © O.E. Dick, I.A. Svyatogor, V.A. Ishinova, A.D. Nozdrachev, 2012, published in Fiziologiya Cheloveka, 2012, Vol. 38, No. 3, pp. 30–36.

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Dick, O.E., Svyatogor, I.A., Ishinova, V.A. et al. Fractal characteristics of the functional state of the brain in patients with anxiuos phobic disorders. Hum Physiol 38, 249–254 (2012). https://doi.org/10.1134/S036211971202003X

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  • DOI: https://doi.org/10.1134/S036211971202003X

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