title: Mechanisms of changes in dynamical complexity of physiological signal patterns
metadata.name: dc.contributor.author
metadata.value: Dik, Olga E.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Nozdrachev, Alexander D.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2020-12-01T18:58:05Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2020-12-01T18:58:05Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2019
metadata.lang: -
metadata.name: dc.identifier.isbn
metadata.value: 978-5-288-05932-2
metadata.lang: -
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/11701/9785288059322
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/21145
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: 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.
metadata.lang: en_GB
metadata.name: dc.description.sponsorship
metadata.value: This research was carried out with the financial support of the Fundamental Research Science
  Program in State Academies for 2013–2020 (GP-14, section 64).
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: physiological signal patterns
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: multifractality
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: EEG
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: anxiety-phobic disorders
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: vascular disorders
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: epileptic injuries
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: parkinsonian and essential tremor
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: wavelet transform
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: intermittent photic stimulation
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: recurrence
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: dynamical complexity
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: bifurcation analysis
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: bursting activity
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: nociceptive neuron model
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Mechanisms of changes in dynamical complexity of physiological signal patterns
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Book
metadata.lang: en_GB
resources.filename: 519004-Дик,Ноздрачев_WoS.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/21145/1/519004-%d0%94%d0%b8%d0%ba%2c%d0%9d%d0%be%d0%b7%d0%b4%d1%80%d0%b0%d1%87%d0%b5%d0%b2_WoS.pdf
resources.format: Adobe PDF
resources.size: 15,36 MB