Mechanisms of changes in dynamical complexity of physiological signal patterns

Abstract

The monograph is a continuation of the development of the concept of reducing the dynamic complexity of physiological rhythms in the event of a pathological condition. The results presented in the monograph represent new evidence of the change in this complexity in various disorders of the functional state of the central nervous system, and give an understanding that only a complex application of a combination of nonlinear dynamics and wavelet analysis methods to the analysis of physiological signals allows, firstly, to identify statistical significant differences in the structure of the patterns of the studied signals for a healthy person and a person with functional disorders, and, secondly, to determine the biophysical mechanisms of changes in the dynamic complexity of these patterns when the functional state changes. The biophysical mechanisms underlying the change in the dynamic complexity of patterns of electrical activity of the brain and involuntary hand oscillations in the event of pathological conditions associated with anxiety-phobic disorders, vascular disorders, epileptic injuries, motor dysfunctions, and neuropathic pain are considered. It is shown that in the case of multifractal signals, these mechanisms are associated with a change in the degree of correlation of patterns due to the occurrence of fluctuations in sequential signal values, and in the case of non-fractal signals, with the occurrence of bifurcations leading to a change in oscillation modes. The possibility of using wavelet, multifractal and recurrent characteristics of EEG patterns and involuntary hand oscillations is demonstrated to assess the effectiveness of psychotherapeutic treatment in pain syndrome in patients with anxiety-phobic disorders, to find the degree of deviation of a person’s motor function from the norm and to reliably distinguish between parkinsonian and essential tremors. The mechanisms of structural rearrangements in the patterns of tremor arising during the performance of a motor task are revealed, and an explanation is obtained for the decrease in this complexity with an increase in the degree of deviation of a person’s motor function from the norm. The molecular mechanism underlying the change in the dynamic complexity of the patterns of impulse activity of sensory neurons in the event of an antinociceptive response has been identified. The monograph is addressed to both biophysicists, neurophysiologists, and clinical practitioners, since the research results presented in it allow assessing the degree of disorders of the functional state of the nervous system and represent new approaches to the diagnosis of these conditions. The monograph includes a detailed description of modern methods for analyzing the dynamics of non-stationary physiological signals and can be used by graduate students and researchers specializing in the study of the structure of dynamic changes in complex signals generated by physical, chemical, biological or economic systems.