Print Email Facebook Twitter Disruption of Functional Brain Networks in Alzheimer’s Disease: What Can We Learn from Graph Spectral Analysis of Resting-State Magnetoencephalography? Title Disruption of Functional Brain Networks in Alzheimer’s Disease: What Can We Learn from Graph Spectral Analysis of Resting-State Magnetoencephalography? Author De Haan, W. Van der Flier, W.M. Wang, H. Van Mieghem, P.F.A. Scheltens, P. Stam, C.J. Faculty Electrical Engineering, Mathematics and Computer Science Date 2012-06-11 Abstract In Alzheimer’s disease (AD), structural and functional brain network organization is disturbed. However, many of the present network analysis measures require a priori assumptions and methodological choices that influence outcomes and interpretations. Graph spectral analysis (GSA) is a more direct algebraic method that describes network properties, which might lead to more reliable results. In this study, GSA was applied to magnetoencephalography (MEG) data to explore functional network integrity in AD. Sensor-level resting-state MEG was performed in 18 Alzheimer patients (age 67 – 9, 6 women) and 18 healthy controls (age 66 – 9, 11 women). Weighted, undirected graphs were constructed based on functional connectivity analysis using the Synchronization likelihood, and GSA was performed with a focus on network connectivity, synchronizability, and node centrality. The main outcomes were a global loss of network connectivity and altered synchronizability in most frequency bands. Eigenvector centrality mapping confirmed the hub status of the parietal areas, and demonstrated a low centrality of the left temporal region in the theta band in AD patients that was strongly related to the mini mental state examination (global cognitive function test) score (r = 0.67, p = 0.001). Summarizing, GSA is a theoretically solid approach that is able to detect the disruption of functional network topology in AD. In addition to the previously reported overall connectivity losses and parietal area hub status, impaired network synchronizability and a clinically relevant left temporal centrality loss were found in AD patients. Our findings imply that GSA is valuable for the purpose of studying altered brain network topology and dynamics in AD. Subject dementiaeigenvector centralityelectrophysiologyfunctional connectivitymagnetoencephalographynetworkneurophysiologyresting-state To reference this document use: http://resolver.tudelft.nl/uuid:838ec651-1c5f-46b3-bd2b-34288fa6b812 DOI https://doi.org/10.1089/brain.2011.0043 Publisher Mary Ann Liebert ISSN 2158-0014 Source Brain Connectivity, 2 (2), 2012 Part of collection Institutional Repository Document type journal article Rights (c) 2012 Mary Ann Liebert Files PDF Wang_2012.pdf 482.21 KB Close viewer /islandora/object/uuid:838ec651-1c5f-46b3-bd2b-34288fa6b812/datastream/OBJ/view