title: Disrupted Brain Functional Organization in Epilepsy Revealed by Graph Theory Analysis.
abstract: The human brain is a complex and dynamic system that can be modeled as a large-scale brain network to better understand the reorganizational changes secondary to epilepsy. In this study, we developed a brain functional network model using graph theory methods applied to resting-state fMRI data acquired from a group of epilepsy patients and age- and gender-matched healthy controls. A brain functional network model was constructed based on resting-state functional connectivity. A minimum spanning tree combined with proportional thresholding approach was used to obtain sparse connectivity matrices for each subject, which formed the basis of brain networks. We examined the brain reorganizational changes in epilepsy thoroughly at the level of the whole brain, the functional network, and individual brain regions. At the whole-brain level, local efficiency was significantly decreased in epilepsy patients compared with the healthy controls. However, global efficiency was significantly increased in epilepsy due to increased number of functional connections between networks (although weakly connected). At the functional network level, there were significant proportions of newly formed connections between the default mode network and other networks and between the subcortical network and other networks. There was a significant proportion of decreasing connections between the cingulo-opercular task control network and other networks. Individual brain regions from different functional networks, however, showed a distinct pattern of reorganizational changes in epilepsy. These findings suggest that epilepsy alters brain efficiency in a consistent pattern at the whole-brain level, yet alters brain functional networks and individual brain regions differently.
authors: 1 Department of Biomedical Engineering, University of Wisconsin-Madison , Madison, Wisconsin.|2 Department of Radiology, University of Wisconsin-Madison , Madison, Wisconsin.
authors: Jie
authors: J
authors: Song
authors: 2 Department of Radiology, University of Wisconsin-Madison , Madison, Wisconsin.
authors: Veena A
authors: VA
authors: Nair
authors: 2 Department of Radiology, University of Wisconsin-Madison , Madison, Wisconsin.
authors: Wolfgang
authors: W
authors: Gaggl
authors: 1 Department of Biomedical Engineering, University of Wisconsin-Madison , Madison, Wisconsin.|2 Department of Radiology, University of Wisconsin-Madison , Madison, Wisconsin.|3 Neuroscience Training Program, University of Wisconsin-Madison , Madison, Wisconsin.|4 Medical Scientist Training Program, University of Wisconsin-Madison , Madison, Wisconsin.|5 Department of Neurology, University of Wisconsin-Madison , Madison, Wisconsin.|6 Department of Psychiatry, University of Wisconsin-Madison , Madison, Wisconsin.|7 Department of Psychology, University of Wisconsin-Madison , Madison, Wisconsin.
authors: Vivek
authors: V
authors: Prabhakaran
mesh_terms: D000328:Adult; D001921:Brain / Q000503:physiopathology*; D001931:Brain Mapping; D016022:Case-Control Studies; D004827:Epilepsy / Q000473:pathology*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging; D008297:Male; D009415:Nerve Net / Q000503:physiopathology; D009434:Neural Pathways / Q000503:physiopathology*; D018709:Statistics, Nonparametric; D055815:Young Adult
keywords: epilepsy; functional networks; graph theory; network analysis
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