Connectivity and Centrality Characteristics of the Epileptogenic Focus Using Directed Network Analysis.

Connectivity and Centrality Characteristics of the Epileptogenic Focus Using Directed Network Analysis.

IEEE Trans Neural Syst Rehabil Eng. 2018 Dec 11;:

Authors: Adkinson JA, Karumuri B, Hutson TN, Liu R, Alamoudi O, Vlachos I, Iasemidis L

Abstract
Accurate epileptogenic focus localization is required prior to surgical resection of brain tissue for treatment of patients with antiepileptic drug resistant (intractable) epilepsy. This clinical need is only partially fulfilled through a subjective, and at times inconclusive, evaluation of the recorded electroence-phalogram (EEG) at seizures' onset (the so-called gold standard for focus localization in epilepsy). We herein present a novel method of multivariate analysis of the EEG that appears to be very promising for an objective and robust localization of the epileptogenic focus at seizures' onset. Using the measure of Generalized Partial Directed Coherence (GPDC), combined with surrogate data analysis, we first estimated from multichannel intracranial EEG the statistically significant causal interactions between brain regions at the onset of 92 clinical seizures from 9 patients with temporal lobe intractable epilepsy. From the networks that were formed based on the thus derived interactions, a set of centrality metrics was estimated per network node (brain site). Brain sites located anatomically within the epileptogenic focus were shown to be associated with greater inward centrality values than non-focal brain regions at high frequencies (.. band), and particular inward centrality metrics accurately localized the focus in all 9 patients. In addition to focus localization from seizure (ictal) onset, the developed novel framework for analysis of EEG could be employed to identify the changes of the focal network over time, peri-ictally and interictally, and thus shed light onto the dynamics of ictogenesis, which could then have a significant impact on automated prediction and closed-loop control of seizures by neuromodulation.

PMID: 30561346 [PubMed - as supplied by publisher]

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