Using variance information in magnetoencephalography measures of functional connectivity

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dc.contributor.authorHall E.L.
dc.contributor.authorWoolrich M.W.
dc.contributor.authorThomaz C.E.
dc.contributor.authorMorris P.G.
dc.contributor.authorBrookes M.J.
dc.date.accessioned2019-08-19T23:45:24Z
dc.date.available2019-08-19T23:45:24Z
dc.date.issued2013
dc.description.abstractThe use of magnetoencephalography (MEG) to assess long range functional connectivity across large scale distributed brain networks is gaining popularity. Recent work has shown that electrodynamic networks can be assessed using both seed based correlation or independent component analysis (ICA) applied to MEG data and further that such metrics agree with fMRI studies. To date, techniques for MEG connectivity assessment have typically used a variance normalised approach, either through the use of Pearson correlation coefficients or via variance normalisation of envelope timecourses prior to ICA. Here, we show that the use of variance information (i.e. data that have not been variance normalised) in source space projected Hilbert envelope time series yields important spatial information, and is of significant functional relevance. Further, we show that employing this information in functional connectivity analyses improves the spatial delineation of network nodes using both seed based and ICA approaches. The use of variance is particularly important in MEG since the non-independence of source space voxels (brought about by the ill-posed MEG inverse problem) means that spurious signals can exist in areas of low signal variance. We therefore suggest that this approach be incorporated into future studies. © 2012.
dc.description.firstpage203
dc.description.lastpage212
dc.description.volume67
dc.identifier.citationHALL, E. L.; WOOLRICH, M. M.; THOMAZ, C. E.; MORRIS, P. G.; BROOKES, M. J.. Using variance information in magnetoencephalography measures of functional connectivity. Neuroimage (Orlando, Fla. Print), v. 67, p. 203-212, 2013.
dc.identifier.doi10.1016/j.neuroimage.2012.11.011
dc.identifier.issn1053-8119
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/1266
dc.relation.ispartofNeuroImage
dc.rightsAcesso Restrito
dc.subject.otherlanguageBeamformer
dc.subject.otherlanguageFunctional connectivity
dc.subject.otherlanguageHilbert envelope
dc.subject.otherlanguageICA
dc.subject.otherlanguageMEG
dc.subject.otherlanguageNetworks
dc.subject.otherlanguageSeed based correlation
dc.titleUsing variance information in magnetoencephalography measures of functional connectivity
dc.typeArtigo
fei.scopus.citations39
fei.scopus.eid2-s2.0-84870982206
fei.scopus.updated2024-03-04
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84870982206&origin=inward
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