使用相关比率法比较分析健康人和抑郁症患者脑电图的通道间关系

IF 4.033 Q4 Biochemistry, Genetics and Molecular Biology Biophysics Pub Date : 2023-12-13 DOI:10.1134/S000635092304019X
M. E. Sobolev, A. L. Gorelik, O. L. Vlasova
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引用次数: 0

摘要

摘要在对抑郁症患者的研究中,采用了一种基于脑电图通道相互关系分析的方法,该方法使用相关比率能够客观地评估任何模型(线性和非线性)中的关系特性。基于构建的相关比率矩阵,分析配对关系与确定规范和病理不同参数的可能性。还发现了导联之间关系的方向性。在我们看来,最显著的差异是大脑半球间枕部关系的差异。这种方法可以成为确定抑郁状态和其他神经精神疾病的独特定量标记的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Comparative Analysis of Interchannel Relationships on Electroencephalograms in Healthy People and Patients with Depression Using the Method of Correlation Ratios

During the study of patients with depression, an approach was applied to the clinical material based on the analysis of the interrelationships of electroencephalogram channels using correlation ratios capable of objectively assessing the properties of relationships in any of their models (linear and nonlinear). The possibility of analyzing paired relationships with the determination of parameters that differ for norm and pathology was shown based on the constructed correlation ratio matrices. The directionality of the relationships between the leads was also found. The most significant differences, in our opinion, were differences in interhemispheric occipital relationships. This approach can become the basis for determining unique quantitative markers of both depressive states and other neuropsychiatric disorders.

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来源期刊
Biophysics
Biophysics Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
1.20
自引率
0.00%
发文量
67
期刊介绍: Biophysics is a multidisciplinary international peer reviewed journal that covers a wide scope of problems related to the main physical mechanisms of processes taking place at different organization levels in biosystems. It includes structure and dynamics of macromolecules, cells and tissues; the influence of environment; energy transformation and transfer; thermodynamics; biological motility; population dynamics and cell differentiation modeling; biomechanics and tissue rheology; nonlinear phenomena, mathematical and cybernetics modeling of complex systems; and computational biology. The journal publishes short communications devoted and review articles.
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