Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology
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...
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Online Access: | http://dx.doi.org/10.1155/2012/239210 |
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doaj-150cf7ad368448eab7c79fb4094c2b372020-11-25T01:39:07ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182012-01-01201210.1155/2012/239210239210Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of MethodologyJunfeng Sun0Zhijun Li1Shanbao Tong2Med-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, ChinaDepartment of Automation, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaMed-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, ChinaFunctional 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.http://dx.doi.org/10.1155/2012/239210 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Junfeng Sun Zhijun Li Shanbao Tong |
spellingShingle |
Junfeng Sun Zhijun Li Shanbao Tong Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology Computational and Mathematical Methods in Medicine |
author_facet |
Junfeng Sun Zhijun Li Shanbao Tong |
author_sort |
Junfeng Sun |
title |
Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology |
title_short |
Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology |
title_full |
Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology |
title_fullStr |
Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology |
title_full_unstemmed |
Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology |
title_sort |
inferring functional neural connectivity with phase synchronization analysis: a review of methodology |
publisher |
Hindawi Limited |
series |
Computational and Mathematical Methods in Medicine |
issn |
1748-670X 1748-6718 |
publishDate |
2012-01-01 |
description |
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. |
url |
http://dx.doi.org/10.1155/2012/239210 |
work_keys_str_mv |
AT junfengsun inferringfunctionalneuralconnectivitywithphasesynchronizationanalysisareviewofmethodology AT zhijunli inferringfunctionalneuralconnectivitywithphasesynchronizationanalysisareviewofmethodology AT shanbaotong inferringfunctionalneuralconnectivitywithphasesynchronizationanalysisareviewofmethodology |
_version_ |
1725050326198779904 |