Mapping and mining interictal pathological gamma (30-100 Hz) oscillations with clinical intracranial EEG in patients with epilepsy

• Type of Material: Article
• Authors: Otis Smart, Emory University; Douglas Maus, State University of New York; Eric Marsh, Children's Hospital of Philadelphia; Dennis Dlugos, Children's Hospital of Philadelphia; Brian Litt, University of Pennsylvania; Kim J Meador, Emory University
• Language: English
• Date: 2012-06-15
• Publisher: Elsevier
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2011 Elsevier Ltd. All rights reserved.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.eswa.2012.01.071
• Title of Journal or Parent Work: Expert Systems with Applications
• ISSN: 0957-4174
• Volume: 39
• Issue: 8
• Start Page: 7355
• End Page: 7370
• Grant/Funding Information: This research was supported by funds from the National Institute of General Medical Sciences (IRACDA 5K12 GM000680-07) and the United Negro College Fund Special Programs Corporation (NASA Harriett G. Jenkins Pre-doctoral Fellowship Program) awarded to Dr. Smart and the National Institute of Neurological Disorders and Stroke (1R01NS048598-01A2), the Dana Foundation, the Epilepsy Research Foundation, and the Citizens United for Research in Epilepsy awarded to Dr. Litt.
• Keywords: Pathological gamma oscillation; Data-mining; REFRACTORY EPILEPSY; INTRACEREBRAL EEG; Operations Research & Management Science; BRAIN; ELECTRICAL-STIMULATION; ENTORHINAL CORTEX; HIPPOCAMPUS; Computer Science, Artificial Intelligence; SURGERY; Computer Science; TEMPORAL-LOBE EPILEPSY; Science & Technology; HIGH-FREQUENCY OSCILLATIONS; Epileptic network; Engineering; Mapping; Interictal epileptic discharge; FOCAL SEIZURES; Technology; Detection; Engineering, Electrical & Electronic
• Research Categories: Biology, Neuroscience; Engineering, Biomedical; Health Sciences, Pathology

Abstract

Localizing an epileptic network is essential for guiding neurosurgery and antiepileptic medical devices as well as elucidating mechanisms that may explain seizure-generation and epilepsy. There is increasing evidence that pathological oscillations may be specific to diseased networks in patients with epilepsy and that these oscillations may be a key biomarker for generating and indentifying epileptic networks. We present a semi-automated method that detects, maps, and mines pathological gamma (30-100 Hz) oscillations (PGOs) in human epileptic brain to possibly localize epileptic networks. We apply the method to standard clinical iEEG ( < 100 Hz) with interictal PGOs and seizures from six patients with medically refractory epilepsy. We demonstrate that electrodes with consistent PGO discharges do not always coincide with clinically determined seizure onset zone (SOZ) electrodes but at times PGO-dense electrodes include secondary seizure-areas (SS) or even areas without seizures (NS). In 4/5 patients with epilepsy surgery, we observe poor (Engel Class 4) postsurgical outcomes and identify more PGO-activity in SS or NS than in SOZ. Additional studies are needed to further clarify the role of PGOs in epileptic brain.