Inferring functional neural connectivity with phase synchronization analysis: a review of methodology.

Computational and Mathematical Methods in Medicine
Junfeng SunShanbao Tong

Abstract

Functional neural connectivity is drawing increasing attention in neuroscience research. To infer functional connectivity from observed neural signals, various methods have been proposed. Among them, phase synchronization analysis is an important and effective one which examines the relationship of instantaneous phase between neural signals but neglecting the influence of their amplitudes. In this paper, we review the advances in methodologies of phase synchronization analysis. In particular, we discuss the definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronization and the extensions of phase synchronization analysis. In practice, phase synchronization analysis may be affected by observational noise, insufficient samples of the signals, volume conduction, and reference in recording neural signals. We make comments and suggestions on these issues so as to better apply phase synchronization analysis to inferring functional connectivity from neural signals.

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Citations

Jul 13, 2013·IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society·Xiangfei HongShanbao Tong
Dec 1, 2012·Computational and Mathematical Methods in Medicine·Muhammad Rehan, Keum-Shik Hong
Oct 12, 2016·Frontiers in Human Neuroscience·Yuezhi LiYong Hu
Oct 31, 2017·Biological cybernetics·Peter G TothOndrej Pokora
Jun 19, 2013·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Björn KralemannMichael Rosenblum
Apr 27, 2021·The Journal of Biological Chemistry·Dinesh KankanamgeAjith Karunarathne

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