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

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 psychorelax ation technique. It has been demonstrated that contrary to power spectra, singularity spectra allow distin guishing 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.

Multifractal detrended fluctuation analysis of human EEG: preliminary investigation and comparison with the wavelet transform modulus maxima technique

“…Recent calculations of the degree of finite-size effects to be expected in multifractal spectrum calculations for non-multifractal processes also support these results, in that we see a larger degree of multifractality than expected by finite-size effects alone [46]. Taking into account the results presented here, results from previously published data [35][36][37], and results from numerical simulations [24,33,46], these data support the hypothesis that human EEG can be successfully modeled as a multifractal process, which may provide additional insight into changes in brain neuronal dynamics associated with pathological states. To our knowledge, these results are the first to formally assess the suitability of multifractal methods to human EEG using simulations of multifractal and monofractal data.…”

“…MF-DFA results from human EEG are comparable to those from known multifractal processes, and appear to have a larger degree of multifractality than known monofractal processes (Figure 1; also cf. [35][36][37]). Recent calculations of the degree of finite-size effects to be expected in multifractal spectrum calculations for non-multifractal processes also support these results, in that we see a larger degree of multifractality than expected by finite-size effects alone [46].…”

“…In both the current study, and in the study of WTMM analysis of sleep stage differentiation [36], it is notable that only the mean_h values vary among sleep stages. It is interesting to note that both mean_h and width_h values were found to change within subjects after exposure to a painful stimulus [37], demonstrating that different states of consciousness may result in different effects on the multifractal spectrum. Current clinical criteria for sleep staging do not include computerassisted feature detection, however the data presented here will add to emerging evidence that automatic sleep-stage detection could have a role to play in the future [49].…”

“…WTMM has been utilized in human EEG to assess differences among stages of sleep [35,36], and among different psychiatric conditions [37], therefore showing evidence of its utility in human EEG research.…”

Multifractal Detrended Fluctuation Analysis of Human EEG: Preliminary Investigation and Comparison with the Wavelet Transform Modulus Maxima Technique

“…WTMM has been utilized in human EEG to assess differences among stages of sleep [35], [36], and among different psychiatric conditions [37], therefore showing evidence of its utility in human EEG research.…”