Assistant Professor University of Maryland School of Medicine Baltimore, Maryland
Rationale: Over the last two decades it has become increasingly clear that focal epilepsy is a network disorder. Intracranial electroencephalography (icEEG) studies have defined common networks during seizure activity in temporal and extra-temporal epilepsy. What is unclear, however, is whether these networks are established only during seizures or persist interictally. In the current study we used seizure spread data to identify epileptic networks in interictal icEEG. Methods: In 11 patients with fronto-temporal epilepsy we identified electrode contacts involved in seizure onset and primary and secondary spread (seizure contact pairs). We defined control pairs as those where onset contact was involved but the second, equidistant from onset, was not involved in seizure spread. We compared connectivity between seizure contact pairs and matched control pairs and related this to seizure spread times and surgical outcome. Connectivity was calculated as the magnitude-squared-coherence from 4-30Hz estimated from five minutes of interictal icEEG data, sampled at 1024Hz, more than six hours from any seizures. Results: A total of 194 contact pairs (97 seizure and control) were evaluated. In all 11 patients with frontal and temporal (mesial and lateral) seizures, coherence was significantly higher in seizure contact pairs compared with control (0.1 vs. 0.07, p = 0.03). Similarly, patients with temporal (n = 5) and mesial temporal (n = 4) seizures had significantly higher coherence between seizure contact pairs and control (0.08 vs. 0.04, p = 0.007 and 0.09 vs. 0.04, p = 0.004, respectively), suggesting that seizure spread patterns follow underlying functional brain networks. To compare connectivity with outcome, we evaluated mean coherence across seizure electrodes in patients with good outcomes (Engel 1 and 2) (9 patients, 88 contact pairs) to those with poor outcomes (Engel 3 and 4) (3 patients, 18 contact pairs). Frontotemporal patients with good seizure outcomes had significantly higher coherence among seizure electrodes than patients with poor outcomes (0.1 vs. 0.02, p < 0.0001). The same was true for patients with temporal lobe seizure (0.1 vs. 0.002, p < 0.0001) suggesting that patients may have better surgical outcomes when highly connected epileptic networks are accurately identified. Conclusions: In this study, we showed higher interictal connectivity among electrode pairs identified in early seizure spread when compared to uninvolved contacts. These data suggest that an underlying functional epileptic network exists that is either hijacked or modified by seizures. Furthermore, highly connected epileptic networks, when identified on icEEG, may be significantly disrupted with epilepsy surgery and may lead to improved outcomes. Funding: Please list any funding that was received in support of this abstract.: NIH Grant Number: 1R01NS109062-01A1 Principal Investigator(s): Zaveri, Hitten and Eid, Tore Project Title: Network analysis for epilepsy surgery Click here to view image/table
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