Open AccessFunctional connectivity changes in multiple sclerosis patients: A graph analytical study of MEG resting state data
Author(s) -
Schoonheim Menno M.,
Geurts Jeroen J.G.,
Landi Doriana,
Douw Linda,
van der Meer Marieke L.,
Vrenken Hugo,
Polman Chris H.,
Barkhof Frederik,
Stam Cornelis J.
Publication year - 2013
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.21424
Subject(s) - magnetoencephalography , resting state fmri , multiple sclerosis , neuropsychology , neuroscience , cognition , clustering coefficient , connectome , power graph analysis , psychology , graph , functional connectivity , electroencephalography , cluster analysis , artificial intelligence , computer science , psychiatry , theoretical computer science
Abstract Multiple sclerosis (MS) is characterized by extensive damage in the central nervous system. Within this field, there is a strong need for more advanced, functional imaging measures, as abnormalities measured with structural imaging insufficiently explain clinicocognitive decline in MS. In this study we investigated functional connectivity changes in MS using resting‐state magnetoencephalography (MEG). Data from 34 MS patients and 28 age and gender‐matched controls was assessed using synchronization likelihood (SL) as a measure of functional interaction strength between brain regions, and graph analysis to characterize topological patterns of connectivity changes. Cognition was assessed using extensive neuropsychological evaluation. Structural measures included brain and lesion volumes, using MRI. Results show SL increases in MS patients in theta, lower alpha and beta bands, with decreases in the upper alpha band. Graph analysis revealed a more regular topology in the lower alpha band in patients, indicated by an increased path length (λ) and clustering coefficient (γ). Attention and working memory domains were impaired, with decreased brain volumes. A stepwise linear regression model using clinical, MRI and MEG parameters as predictors revealed that only increases in lower alpha band γ predicted impaired cognition. Cognitive impairments and related altered connectivity patterns were found to be especially predominant in male patients. These results show specific functional changes in MS as measured with MEG. Only changes in network topology were related to poorer cognitive outcome. This indicates the value of graph analysis beyond traditional structural and functional measures, with possible implications for diagnostic and/or prognostic purposes in MS. Hum Brain Mapp, 2013. © 2011 Wiley Periodicals, Inc.