Introduction

Abstract

It is known that any physiological system is capable of adapting to constantly changing environmental conditions, due to which its physiological parameters are characterized by significant variability. The signals generated by physiological systems have the properties of nonlinearity and nonstationarity. This means that small changes in system parameters can cause significant changes in the system responses, i.e. signals, and the signal structure changes significantly over time. The dynamic complexity of signal patterns indicates the presence of structural rearrangements reflecting their nonstationarity. The question naturally arises: due to what biophysical mechanisms there are changes in the pattern structure in case of violations of the functional state of the system? The monograph is devoted to the study of the dynamic complexity of the temporal organization of physiological signal patterns reflecting the variability and nonstationarity of the temporal dynamics of physiological processes. It is believed that this complexity is based on the diversity of the control processes of functional nerve connections, and the pathology of the control process is associated with the loss of the dynamic complexity of patterns, the emergence of a dominant pattern or even a dominant frequency, leading to the inability of the physiological system to respond to unpredictable stimuli in a varied and adequate manner. The concept of reducing the dynamic complexity of physiological rhythms in the event of a pathological condition first appeared in the works of American physicists, who showed that some fundamental parameters of physiological rhythms, for example, the degree of multifractality of heart rhythm intervals in a healthy person is statistically stable, and aging or a disease associated with heart rhythm disturbances , leads to the loss of this multifractality. The results presented in this monograph are a continuation of the development of this concept. These results reveal the mechanisms of changes in this complexity and provide new evidence of changes in this complexity in various disorders of the functional state of the central nervous system associated with anxiety-phobic disorders, vascular disorders, epileptic injuries, motor dysfunctions, and neuropathic pain. For the first time, the possibility of using wavelet, multifractal and recurrent characteristics of EEG patterns and involuntary hand oscillations was shown 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. For the first time, the mechanisms of structural rearrangements in the patterns of tremor arising during the performance of a motor task were identified, and an explanation was obtained for the decrease in this complexity with an increase in the degree of deviation of a person’s motor function from the norm. For the first time, 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 determined. The monograph contains 7 chapters. The first chapter discusses the main methods of analysis of non-stationary physiological signals. The second chapter is devoted to elucidating the mechanisms underlying the changes in the dynamic complexity of EEG patterns in disorders of the functional state of the brain associated with epileptic injuries, and modeling the possibility of automatic detection of epileptic discharges based on wavelet and multifractal characteristics of EEG patterns in a patient with symptomatic partial epilepsy. The third chapter explains the mechanisms for correcting anxiety-phobic states. For this, the changes occurring in the EEG patterns during the presentation of a painful stimulus and in the process of eliminating the pain sensation using the psychorelaxation technique in healthy individuals are considered; these changes are compared with changes in EEG patterns during psychorelaxation in patients with anxiety-phobic disorders. The fourth and fifth chapters are devoted to the analysis of changes occurring in reactive EEG patterns in disorders of the functional state of the central nervous system associated with vascular pathology of the brain and cardiac arrhythmias of varying severity. The sixth chapter examines the mechanisms of changes in the dynamic complexity of hand tremor with an increase in the degree of motor disorders. The seventh chapter is devoted to the determination of the mechanisms of changes in the dynamic complexity of the patterns of impulse activity of nociceptors when the antinociceptive response occurs. The monograph is addressed to specialists in the field of studying the structure of dynamic changes in both the bioelectrical activity of the brain and the activity of individual neurons during the development of various kinds of pathological conditions. The results presented in the monograph can be used in clinical practice to solve a number of clinical tasks, such as automatic detection of epileptic discharges in patients with partial epilepsy, assessment of the effectiveness of psychotherapeutic influence and the degree of psychoemotional excitability, the degree of deviation of a person’s motor function from the norm and a reliable distinction between parkinsonian and essential tremor. This study was supported by the Program of Fundamental Scientific Research of State Academies for 2013–2020 (GP-14, Section 64). The authors are deeply grateful to the staff of the I.P. Pavlov Institute of Physiology, Russian Academy of Sciences, whose joint scientific results were used to one degree or another in writing the book. Among them, we would like to highlight B.V. Krylov and V.B. Plakhova, the senior researchers of Laboratory for physiology of excitable membranes for useful discussions and their help with data recordings for experimental families of currents via the Na V 1.8 channels and I.A. Svyatogor, the senior researcher of Laboratory for interception for her help with EEG data recordings. We are grateful to the management of St. Petersburg State University for interest in this book and support for its publication.