Graduation Date

Spring 5-4-2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Programs

Interdisciplinary Graduate Program in Biomedical Sciences

First Advisor

Dr. Stephen V. Gliske

Abstract

Epilepsy is a neurological disease leading to recurrent and unpredictable seizures. Patients can be diagnosed as focal onset, where the seizure focus resides in one hemisphere; generalized onset, where seizure foci reside in both hemispheres; or unknown onset. Anti-seizure medications are the first line of treatment, and those whose seizures cannot be controlled with medication are diagnosed with drug-resistant epilepsy (DRE). For patients diagnosed with focal onset epilepsy to achieve seizure freedom, surgical resection of the epileptogenic zone (EZ), the region of the brain that is both necessary and sufficient for initiating seizures, is required. The EZ is a theoretical region, so clinical teams often use the seizure onset zone (SOZ) as a surrogate. Before surgical resection, clinical teams will identify brain regions that must be spared to preserve normal cognitive function and brain regions that must be resected to provide therapeutic value. As current clinical methods rely on subjective evaluation, objective measures could improve clinical evaluation and post-surgical outcomes. Using magnetoencephalography (MEG) and intracranial electroencephalography (iEEG), this work attempts to fill this critical knowledge gap by objectively identifying brain areas relevant to surgical intervention. In Chapter 1, we post-process a distributed source localization method to identify the location and boundary of the brain region that activates in response to a somatosensory task performed during MEG recordings. This region is compared to an anatomical atlas and current clinical methods. Our method has high concordance with an anatomical atlas and does not differ from current clinical approaches. In Chapter 2, we perform time-varying effective connectivity analysis on ictal iEEG recordings to identify electrode contacts that may reside in the SOZ. The weighted out-degree is calculated from 10 seconds before to five seconds after the determined electrographic onset. Channels with normalized weighted out-degrees greater than 0.5 are identified as candidate SOZ channels. We find our algorithm provides useful information for the localization of SOZ channels. These findings highlight using computational methods to extract additional information during pre-surgical evaluation. Further validation of these methods could lead to improved outcomes for patients undergoing surgical intervention in the treatment of focal epilepsy.

Comments

2024 Copyright, the authors

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