title: Inferring functional neural connectivity with phase synchronization analysis: a review of methodology.
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.
authors.affiliation: Med-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.
authors.forename: Junfeng
authors.initials: J
authors.lastname: Sun
authors.forename: Zhijun
authors.initials: Z
authors.lastname: Li
authors.forename: Shanbao
authors.initials: S
authors.lastname: Tong
mesh_terms: D003198:Computer Simulation; D003344:Cortical Synchronization / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D049490:Systems Biology; D013598:Systems Theory