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Network analysis for a network disorder: The emerging role of graph theory in the study of epilepsy

  • Boris C. Bernhardt
    Correspondence
    Corresponding author at: Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, H3A2B4 Montreal, QC, Canada.
    Affiliations
    Neuroimaging of Epilepsy Laboratory, Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada

    Department of Social Neuroscience, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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  • Leonardo Bonilha
    Affiliations
    Department of Neurology, Medical University of South Carolina, SC, USA
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  • Donald W. Gross
    Affiliations
    Division of Neurology, Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
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      Abstract

      Recent years have witnessed a paradigm shift in the study and conceptualization of epilepsy, which is increasingly understood as a network-level disorder. An emblematic case is temporal lobe epilepsy (TLE), the most common drug-resistant epilepsy that is electroclinically defined as a focal epilepsy and pathologically associated with hippocampal sclerosis. In this review, we will summarize histopathological, electrophysiological, and neuroimaging evidence supporting the concept that the substrate of TLE is not limited to the hippocampus alone, but rather is broadly distributed across multiple brain regions and interconnecting white matter pathways. We will introduce basic concepts of graph theory, a formalism to quantify topological properties of complex systems that has recently been widely applied to study networks derived from brain imaging and electrophysiology. We will discuss converging graph theoretical evidence indicating that networks in TLE show marked shifts in their overall topology, providing insight into the neurobiology of TLE as a network-level disorder. Our review will conclude by discussing methodological challenges and future clinical applications of this powerful analytical approach.

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