Targeting Epileptogenesis: A Conceptual Black Hole or Light at the End of the Tunnel?

Abstract

Objective: The current study aims to investigate functional brain network representations during the early period of epileptogenesis. Methods: Eighteen rats with the intrahippocampal kainate model of mesial temporal lobe epilepsy were used for this experiment. Functional magnetic resonance imaging (fMRI) measurements were made 1 week after status epilepticus, followed by 2-4-month electrophysiological and video monitoring. Animals were identified as having (1) developed epilepsy (E+, n = 9) or (2) not developed epilepsy (EÀ, n = 6). Nine additional animals served as controls. Graph theory analysis was performed on the fMRI data to quantify the functional brain networks in all animals prior to the development of epilepsy. Spectrum clustering with the network features was performed to estimate their predictability in epileptogenesis. Results: Our data indicated that E+ animals showed an overall increase in functional connectivity strength compared to EÀ and control animals. Global network features and small-worldness of EÀrats were similar to controls, whereas E+ rats demonstrated increased small-worldness, including increased reorganization degree, clustering coefficient, and global efficiency, with reduced shortest path length. A notable classification of the combined brain network parameters was found in E+ and EÀanimals. For the local network parameters, the EÀrats showed increased hubs in sensorimotor cortex, and decreased hubness in hippocampus. The E+ rats showed a complete loss of hippocampal hubs, and the appearance of new hubs in the prefrontal cortex. We also observed that lesion severity was not related to epileptogenesis. Significance: Our data provide a view of the reorganization of topographical functional brain networks in the early period of epileptogenesis and how it can significantly predict the development of epilepsy. The differences from EÀanimals offer a potential means for applying noninvasive neuroimaging tools for the early prediction of epilepsy.

A Call to Change Course for Established Epilepsy

“…Blood vessel malformations in the brain, stroke, brain tumors, and several genetic syndromes can also result in TLE. Since a small subset of patients with these known causative factors go on to develop TLE, targeting the “latent-period” 2 with a preventative or disease-modifying therapy would require the ability to accurately predict the most high-risk patients for TLE. However, such predictive biomarkers for TLE have not yet been established.…”