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Journal Article

Imaging structural and functional brain networks in temporal lobe epilepsy


Bernhardt,  Boris C.
Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montréal, QC, Canada;
Department Social Neuroscience, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Bernhardt, B. C., Hong, S. J., Bernasconi, A., & Bernasconi, N. (2013). Imaging structural and functional brain networks in temporal lobe epilepsy. Frontiers in Human Neuroscience, 7: 624. doi:10.3389/fnhum.2013.00624.

Cite as: http://hdl.handle.net/11858/00-001M-0000-0014-A1B3-D
Early imaging studies in temporal lobe epilepsy (TLE) focused on the search for mesial temporal sclerosis, as its surgical removal results in clinically meaningful improvement in about 70% of patients. Nevertheless, a considerable subgroup of patients continues to suffer from post-operative seizures. Although the reasons for surgical failure are not fully understood, electrophysiological and imaging data suggest that anomalies extending beyond the temporal lobe may have negative impact on outcome. This hypothesis has revived the concept of human epilepsy as a disorder of distributed brain networks. Recent methodological advances in non-invasive neuroimaging have led to quantify structural and functional networks in vivo. While structural networks can be inferred from diffusion MRI tractography and inter-regional covariance patterns of structural measures such as cortical thickness, functional connectivity is generally computed based on statistical dependencies of neurophysiological time-series, measured through functional MRI or electroencephalographic techniques. This review considers the application of advanced analytical methods in structural and functional connectivity analyses in TLE. We will specifically highlight findings from graph-theoretical analysis that allow assessing the topological organization of brain networks. These studies have provided compelling evidence that TLE is a system disorder with profound alterations in local and distributed networks. In addition, there is emerging evidence for the utility of network properties as clinical diagnostic markers. Nowadays, a network perspective is considered to be essential to the understanding of the development, progression, and management of epilepsy.