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Epileptogenic Source Imaging Using Cross Frequency Coupled Signals from Scalp EEG

By Li Chunsheng, Daniel Jacobs, Trevor Hilton, Martin Del Campo, Yotin Chinvarun, Peter Carlen and Berj Bardakjian

Abstract

Objective: The epileptogenic zone (EZ) is a brain region containing the sources of seizure genesis. Removal of the EZ is associated with cessation of seizures after resective surgical procedures, as measured by Engel Class I score. This study describes a novel EEG (electroencephalography) source imaging (ESI) method which uses cross-frequency coupled potential signals (SCFC) derived from scalp EEG. Methods: Scalp EEG were recorded from ten patients (20 seizures) suffering from epilepsy. The S CFC were constructed from the phase and amplitude of the lower and higher frequency rhythms at electrographic seizure onset. ESI was then performed using the SCFC. Validation of the technique was facilitated by forward and inverse computer modeling of known cortical sources, and the correspondence of the ESI with EZ in resected regions of patients. Results: For ten seizures sampled at or above 500 Hz from four patients, all estimated sources lay within the resected region, emphasizing the clinical importance of higher sampling rates. The SCFC demonstrated significant advantages over the “raw” scalp EEG, indicating its robust noise performance. Modeling investigations indicated that a signal-to-noise ratio above 0.2 was sufficient to achieve successful localization regarding EMG artifacts. Conclusion: The association of the estimated sources to the EZ suggests that cross-frequency coupling is a feature of the brain's neural networks, not of artifactual activity. The SCFC can effectively extract brain signals from a noisy background. Significance: We propose this approach to enhance the placement of intracranial electrode for surgical intervention

Topics: Epilepsy, EEG source imaging (ESI), cross frequency coupling, modulation index (MI), artifactual immunity
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Year: 2016
DOI identifier: 10.1109/TBME.2016.2613936
OAI identifier: oai:localhost:1807/79789
Provided by: TSpace Repository
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