Betweenness centrality of intracranial electroencephalography networks and surgical epilepsy outcome

Objective: We sought to determine whether the presence or surgical removal of certain nodes in a connectivity network constructed from intracranial electroencephalography recordings determines postoperative seizure freedom in surgical epilepsy patients. Methods: We analyzed connectivity networks constructed from peri-ictal intracranial electroencephalography of surgical epilepsy patients before a tailored resection. Thirty-six patients and 123 seizures were analyzed. Their Engel class postsurgical seizure outcome was determined at least one year after surgery. Betweenness centrality, a measure of a node's importance as a hub in the network, was used to compare nodes. Results: The presence of larger quantities of high-betweenness nodes in interictal and postictal networks was associated with failure to achieve seizure freedom from the surgery (p < 0.001), as was resection of high-betweenness nodes in three successive frequency groups in mid-seizure networks (p < 0.001). Conclusions: Betweenness centrality is a biomarker for postsurgical seizure outcomes. The presence of high-betweenness nodes in interictal and postictal networks can predict patient outcome independent of resection. Additionally, since their resection is associated with worse seizure outcomes, the midseizure network high-betweenness centrality nodes may represent hubs in self-regulatory networks that inhibit or help terminate seizures. Significance: This is the first study to identify network nodes that are possibly protective in epilepsy. (C) 2018 Published by Elsevier B.V. on behalf of International Federation of Clinical Neurophysiology.