Whole brain functional connectivity using phase locking measures of resting state magnetoencephalography

The analysis of spontaneous functional connectivity (sFC) reveals the statistical connections between regions of the brain consistent with underlying functional communication networks within the brain. In this work, we describe the implementation of a complete all-to-all network analysis of resting...

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Main Authors:	Schmidt, Benjamin T., Ghuman, Avniel S., Huppert, Theodore J.
Format:	Online
Language:	English
Published:	Frontiers Media S.A. 2014
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4071638/

id	pubmed-4071638
recordtype	oai_dc
spelling	pubmed-40716382014-07-11 Whole brain functional connectivity using phase locking measures of resting state magnetoencephalography Schmidt, Benjamin T. Ghuman, Avniel S. Huppert, Theodore J. Neuroscience The analysis of spontaneous functional connectivity (sFC) reveals the statistical connections between regions of the brain consistent with underlying functional communication networks within the brain. In this work, we describe the implementation of a complete all-to-all network analysis of resting state neuronal activity from magnetoencephalography (MEG). Using graph theory to define networks at the dipole level, we established functionally defined regions by k-means clustering cortical surface locations using Eigenvector centrality (EVC) scores from the all-to-all adjacency model. Permutation testing was used to estimate regions with statistically significant connections compared to empty room data, which adjusts for spatial dependencies introduced by the MEG inverse problem. In order to test this model, we performed a series of numerical simulations investigating the effects of the MEG reconstruction on connectivity estimates. We subsequently applied the approach to subject data to investigate the effectiveness of our method in obtaining whole brain networks. Our findings indicated that our model provides statistically robust estimates of functional region networks. Application of our phase locking network methodology to real data produced networks with similar connectivity to previously published findings, specifically, we found connections between contralateral areas of the arcuate fasciculus that have been previously investigated. The use of data-driven methods for neuroscientific investigations provides a new tool for researchers in identifying and characterizing whole brain functional connectivity networks. Frontiers Media S.A. 2014-06-11 /pmc/articles/PMC4071638/ /pubmed/25018690 http://dx.doi.org/10.3389/fnins.2014.00141 Text en Copyright © 2014 Schmidt, Ghuman and Huppert. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Schmidt, Benjamin T. Ghuman, Avniel S. Huppert, Theodore J.
spellingShingle	Schmidt, Benjamin T. Ghuman, Avniel S. Huppert, Theodore J. Whole brain functional connectivity using phase locking measures of resting state magnetoencephalography
author_facet	Schmidt, Benjamin T. Ghuman, Avniel S. Huppert, Theodore J.
author_sort	Schmidt, Benjamin T.
title	Whole brain functional connectivity using phase locking measures of resting state magnetoencephalography
title_short	Whole brain functional connectivity using phase locking measures of resting state magnetoencephalography
title_full	Whole brain functional connectivity using phase locking measures of resting state magnetoencephalography
title_fullStr	Whole brain functional connectivity using phase locking measures of resting state magnetoencephalography
title_full_unstemmed	Whole brain functional connectivity using phase locking measures of resting state magnetoencephalography
title_sort	whole brain functional connectivity using phase locking measures of resting state magnetoencephalography
description	The analysis of spontaneous functional connectivity (sFC) reveals the statistical connections between regions of the brain consistent with underlying functional communication networks within the brain. In this work, we describe the implementation of a complete all-to-all network analysis of resting state neuronal activity from magnetoencephalography (MEG). Using graph theory to define networks at the dipole level, we established functionally defined regions by k-means clustering cortical surface locations using Eigenvector centrality (EVC) scores from the all-to-all adjacency model. Permutation testing was used to estimate regions with statistically significant connections compared to empty room data, which adjusts for spatial dependencies introduced by the MEG inverse problem. In order to test this model, we performed a series of numerical simulations investigating the effects of the MEG reconstruction on connectivity estimates. We subsequently applied the approach to subject data to investigate the effectiveness of our method in obtaining whole brain networks. Our findings indicated that our model provides statistically robust estimates of functional region networks. Application of our phase locking network methodology to real data produced networks with similar connectivity to previously published findings, specifically, we found connections between contralateral areas of the arcuate fasciculus that have been previously investigated. The use of data-driven methods for neuroscientific investigations provides a new tool for researchers in identifying and characterizing whole brain functional connectivity networks.
publisher	Frontiers Media S.A.
publishDate	2014
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4071638/
_version_	1612106350329856000

Whole brain functional connectivity using phase locking measures of resting state magnetoencephalography

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