TY - JOUR
T1 - Graph theoretical analysis of magnetoencephalographic functional connectivity in Alzheimers disease
AU - Stam, C.J.
AU - de Haan, W.
AU - Daffertshofer, A.
AU - Jones, B.F.
AU - Manshanden, I.
AU - Walsum, A.M.
AU - Montez, T.
AU - Verbunt, J.P.A.
AU - de Munck, J.C.
AU - Berendse, H.W.
AU - Scheltens, P.
AU - van Dijk, B.W.
N1 - J English Article de Haan, W, UV Univ, Med Ctr, Alzheimer Ctr, Dept Neurol, POB 7057, NL-1007 MB Amsterdam, Netherlands [email protected] 77 5 OXFORD UNIV PRESS OXFORD GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND BRAIN JAN Part 1 Discipline: Clinical Neurology; Neurosciences 398FN
PY - 2009
Y1 - 2009
N2 - In this study we examined changes in the large-scale structure of resting-state brain networks in patients with Alzheimer's disease compared with non-demented controls, using concepts from graph theory. Magneto-encephalograms (MEG) were recorded in 18 Alzheimer's disease patients and 18 non-demented control subjects in a no-task, eyes-closed condition. For the main frequency bands, synchronization between all pairs of MEG channels was assessed using a phase lag index (PLI, a synchronization measure insensitive to volume conduction). PLI-weighted connectivity networks were calculated, and characterized by a mean clustering coefficient and path length. Alzheimer's disease patients showed a decrease of mean PLI in the lower alpha and beta band. In the lower alpha band, the clustering coefficient and path length were both decreased in Alzheimer's disease patients. Network changes in the lower alpha band were better explained by a 'Targeted Attack' model than by a 'Random Failure' model. Thus, Alzheimer's disease patients display a loss of resting-state functional connectivity in lower alpha and beta bands even when a measure insensitive to volume conduction effects is used. Moreover, the large-scale structure of lower alpha band functional networks in Alzheimer's disease is more random. The modelling results suggest that highly connected neural network 'hubs' may be especially at risk in Alzheimer's disease. © The Author (2008). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.
AB - In this study we examined changes in the large-scale structure of resting-state brain networks in patients with Alzheimer's disease compared with non-demented controls, using concepts from graph theory. Magneto-encephalograms (MEG) were recorded in 18 Alzheimer's disease patients and 18 non-demented control subjects in a no-task, eyes-closed condition. For the main frequency bands, synchronization between all pairs of MEG channels was assessed using a phase lag index (PLI, a synchronization measure insensitive to volume conduction). PLI-weighted connectivity networks were calculated, and characterized by a mean clustering coefficient and path length. Alzheimer's disease patients showed a decrease of mean PLI in the lower alpha and beta band. In the lower alpha band, the clustering coefficient and path length were both decreased in Alzheimer's disease patients. Network changes in the lower alpha band were better explained by a 'Targeted Attack' model than by a 'Random Failure' model. Thus, Alzheimer's disease patients display a loss of resting-state functional connectivity in lower alpha and beta bands even when a measure insensitive to volume conduction effects is used. Moreover, the large-scale structure of lower alpha band functional networks in Alzheimer's disease is more random. The modelling results suggest that highly connected neural network 'hubs' may be especially at risk in Alzheimer's disease. © The Author (2008). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.
U2 - https://doi.org/10.1093/brain/awn262
DO - https://doi.org/10.1093/brain/awn262
M3 - Article
C2 - 18952674
SN - 0006-8950
VL - 132
SP - 213
EP - 224
JO - Brain
JF - Brain
ER -