Changes in EEG time series before, during and after removing a pain syndrome by applying the psychorelaxation technique are examined for healthy subjects and patients with chronic psychogenic pain disorders connected with disruptions of interrelations between cortex and subcortex on the thalamic and the brain-stem level. The degree of psychorelaxation and decrease of the pain syndromes is estimated as a change in the multifractality degree gained by the wavelet transform modulus maxima method. For the healthy subjects we observe the reliable decrease of the multifractality degree and the enhancement of the anticorrelated dynamics of consecutive EEG values during the pain and their recovery up to the previous values during psychorelaxation. The all healthy subjects notice that the pain syndrome disappears. The analogous dynamics in the multifractality and the improvement of the functional state are observed only for 70% “thalamic” patients. For other 30% patients of the group the multifractality degree remains less than for the healthy subjects. For all the “brain-stem” patients during relaxation the multifractality degree remains high and the singularity spectrum corresponds to both the correlated and anticorrelated dynamics. The study demonstrates that the changes in the multifractality give a good ability to estimate the psychorelaxation efficiency for the healthy and pathological human brain.
[1]
In-Ho Song,et al.
Fluctuation Dynamics in Electroencephalogram Time Series
,
2005,
IWINAC.
[2]
John Suckling,et al.
Generic aspects of complexity in brain imaging data and other biological systems
,
2009,
NeuroImage.
[3]
I. A. Svyatogor,et al.
Features of Color Reflection in Psychogenic Pain in Patients with Somatoform Disorders during Psychotherapeutic Treatment
,
2009,
The Spanish journal of psychology.
[4]
M. Hersen,et al.
Encyclopedia of psychotherapy
,
2002
.
[5]
John Suckling,et al.
Monofractal and multifractal dynamics of low frequency endogenous brain oscillations in functional MRI
,
2008,
Human brain mapping.
[6]
E. Bacry,et al.
Singularity spectrum of fractal signals from wavelet analysis: Exact results
,
1993
.
[7]
D. Popivanov,et al.
Multifractality of decomposed EEG during imaginary and real visual-motor tracking
,
2006,
Biological Cybernetics.