Functional networks of the brain: from connectivity restoration to dynamic integration

被引:27
|
作者
Khramov, A. E. [1 ,2 ]
Frolov, N. S. [1 ]
Maksimenko, V. A. [1 ]
Kurkin, S. A. [1 ]
Kazantsev, V. B. [1 ]
Pisarchik, A. N. [1 ,3 ]
机构
[1] Innopolis Univ, Ctr Technol Robot & Mechatron Components, Lab Neurosci & Cognit Technol, Ul Univ Skaya 1, Innopolis 420500, Tatarstan, Russia
[2] VM Razumovsky Saratov State Med Univ, Ul Bolshaya Kazachia 112, Saratov 410012, Russia
[3] Univ Politecn Madrid, Ctr Biomed Technol, Campus Montegancedo, Madrid 28223, Spain
基金
俄罗斯科学基金会; 俄罗斯基础研究基金会;
关键词
functional connectivity; synchronization; complex networks; neural networks; analysis of electroencephalograms and magnetoencephalograms; RICH-CLUB ORGANIZATION; PARTIAL DIRECTED COHERENCE; NONLINEAR GRANGER CAUSALITY; GRAPH-THEORETICAL ANALYSIS; NEURAL MASS MODEL; PHASE-SYNCHRONIZATION; MOTOR-IMAGERY; SMALL-WORLD; CORTICAL CONNECTIVITY; EEG-DATA;
D O I
10.3367/UFNe.2020.06.038807
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
A review of physical and mathematical methods for reconstructing the functional networks of the brain based on recorded brain activity is presented. Various methods are considered, as are their advantages and disadvantages and limitations of the application. Problems applying the theory of complex networks to reconstructed functional networks of the brain to explain the effects of dynamic integration in the brain and their influence on the diverse functionality of the brain and consciousness, as well as processes leading to the pathological activity of the central nervous system, are examined. Questions concerning the application of these approaches are considered both to describe the functioning of the brain in various cognitive and pathological processes and to create new brain-computer interfaces based on the detection of changes in functional connections in the brain.
引用
收藏
页码:584 / 616
页数:33
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