Alexandria C Marino1, Genevieve J Yang1, Evgeniya Tyrtova2, Kun Wu3, Hitten P Zaveri4, Pue Farooque4, Dennis D Spencer3, S Kathleen Bandt5. 1. Department of Neuroscience, Yale University, PO Box 208001, New Haven, CT 06520-8001, USA; Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510, USA. 2. Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510, USA. 3. Department of Neurosurgery, Yale University, P.O. Box 208082, New Haven, CT 06520-8082, USA. 4. Department of Neurology, Yale University, PO Box 208018, New Haven, CT 06520-8018, USA. 5. Department of Neurosurgery, Yale University, P.O. Box 208082, New Haven, CT 06520-8082, USA; Department of Neurosurgery, Northwestern University, 676 N. Saint Clair, Suite 2210, Chicago, IL 60611, USA. Electronic address: katie.bandt@northwestern.edu.
Abstract
OBJECTIVE: Localization related epilepsy (LRE) is increasingly accepted as a network disorder. To better understand the network specific characteristics of LRE, we defined individual epilepsy networks and compared them across patients. METHODS: The epilepsy network was defined in the slow cortical potential frequency band in 10 patients using intracranial EEG data obtained during interictal periods. Cortical regions were included in the epilepsy network if their connectivity pattern was similar to the connectivity pattern of the seizure onset electrode contact. Patients were subdivided into frontal, temporal, and posterior quadrant cohorts according to the anatomic location of seizure onset. Jaccard similarity was calculated within each cohort to assess for similarity of the epilepsy network between patients within each cohort. RESULTS: All patients exhibited an epilepsy network in the slow cortical potential frequency band. The topographic distribution of this correlated network activity was found to be unique at the single subject level. CONCLUSIONS: The epilepsy network was unique at the single patient level, even between patients with similar seizure onset locations. SIGNIFICANCE: We demonstrated that the epilepsy network is patient-specific. This is in keeping with our current understanding of brain networks and identifies the patient-specific epilepsy network as a possible biomarker in LRE.
OBJECTIVE: Localization related epilepsy (LRE) is increasingly accepted as a network disorder. To better understand the network specific characteristics of LRE, we defined individual epilepsy networks and compared them across patients. METHODS: The epilepsy network was defined in the slow cortical potential frequency band in 10 patients using intracranial EEG data obtained during interictal periods. Cortical regions were included in the epilepsy network if their connectivity pattern was similar to the connectivity pattern of the seizure onset electrode contact. Patients were subdivided into frontal, temporal, and posterior quadrant cohorts according to the anatomic location of seizure onset. Jaccard similarity was calculated within each cohort to assess for similarity of the epilepsy network between patients within each cohort. RESULTS: All patients exhibited an epilepsy network in the slow cortical potential frequency band. The topographic distribution of this correlated network activity was found to be unique at the single subject level. CONCLUSIONS: The epilepsy network was unique at the single patient level, even between patients with similar seizure onset locations. SIGNIFICANCE: We demonstrated that the epilepsy network is patient-specific. This is in keeping with our current understanding of brain networks and identifies the patient-specific epilepsy network as a possible biomarker in LRE.