Reviews of topical problems

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

  a, b,  a,  a,  a,  a,  a, c
a Innopolis University, Universitetskaya Str. 1, Innopolis, Tatarstan, 420500, Russian Federation
b Saratov State Medical University named after V. I. Razumovsky, Bolshaya Kazachya str. 112, Saratov, 410012, Russian Federation
c Center for Biomedical Technology Technical University of Madrid, Campus Montegancedo, Pozuelo de Alarcón, Madrid, 28223, Spain

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.

Fulltext is available at IOP
Keywords: functional connectivity, synchronization, complex networks, neural networks, analysis of electroencephalograms and magnetoencephalograms
PACS: 05.45.−a, 05.45.Tp, 05.45.Xt,, 87.85.dd, (all)
DOI: 10.3367/UFNe.2020.06.038807
Citation: Hramov A E, Frolov N S, Maksimenko V A, Kurkin S A, Kazantsev V B, Pisarchik A N "Functional networks of the brain: from connectivity restoration to dynamic integration" Phys. Usp. 64 584–616 (2021)
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Received: 29th, March 2020, revised: 28th, June 2020, 29th, June 2020

Оригинал: Храмов А Е, Фролов Н С, Максименко В А, Куркин С А, Казанцев В Б, Писарчик А Н «Функциональные сети головного мозга: от восстановления связей до динамической интеграции» УФН 191 614–650 (2021); DOI: 10.3367/UFNr.2020.06.038807

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