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dc.contributor.authorBasti, Alessio
dc.contributor.authorNili, Hamed
dc.contributor.authorHauk, Olaf
dc.contributor.authorMarzetti, Laura
dc.contributor.authorHenson, Rik
dc.date.accessioned2020-07-16T23:30:42Z
dc.date.available2020-07-16T23:30:42Z
dc.date.issued2020-11-01
dc.identifier.issn1053-8119
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/308038
dc.description.abstractThe estimation of functional connectivity between regions of the brain, for example based on statistical dependencies between the time series of activity in each region, has become increasingly important in neuroimaging. Typically, multiple time series (e.g. from each voxel in fMRI data) are first reduced to a single time series that summarises the activity in a region of interest, e.g. by averaging across voxels or by taking the first principal component; an approach we call one-dimensional connectivity. However, this summary approach ignores potential multi-dimensional connectivity between two regions, and a number of recent methods have been proposed to capture such complex dependencies. Here we review the most common multi-dimensional connectivity methods, from an intuitive perspective, from a formal (mathematical) point of view, and through a number of simulated and real (fMRI and MEG) data examples that illustrate the strengths and weaknesses of each method. The paper is accompanied with both functions and scripts, which implement each method and reproduce all the examples.
dc.format.mediumPrint-Electronic
dc.languageeng
dc.publisherElsevier BV
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBrain
dc.subjectHumans
dc.subjectMagnetic Resonance Imaging
dc.subjectMagnetoencephalography
dc.subjectModels, Theoretical
dc.subjectConnectome
dc.titleMulti-dimensional connectivity: a conceptual and mathematical review.
dc.typeArticle
prism.publicationDate2020
prism.publicationNameNeuroimage
prism.startingPage117179
prism.volume221
dc.identifier.doi10.17863/CAM.55133
dcterms.dateAccepted2020-07-14
rioxxterms.versionofrecord10.1016/j.neuroimage.2020.117179
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2020-11
dc.contributor.orcidHauk, Olaf [0000-0003-0817-6054]
dc.contributor.orcidHenson, Rik [0000-0002-0712-2639]
dc.identifier.eissn1095-9572
rioxxterms.typeJournal Article/Review
pubs.funder-project-idMRC (unknown)
pubs.funder-project-idMedical Research Council (MC_UU_00005/14)
pubs.funder-project-idMedical Research Council (MC_UU_00005/8)
cam.orpheus.counter2
rioxxterms.freetoread.startdate2023-07-16


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's licence is described as Attribution-NonCommercial-NoDerivatives 4.0 International