Imaging Network Alterations in Patients With Genetic Generalized Epilepsy and Their Healthy Siblings Using Magneto- and Electroencephalography
by Christina Stier
Date of Examination:2022-03-17
Date of issue:2022-04-05
Advisor:Prof. Dr. Niels K. Focke
Referee:Prof. Dr. Niels K. Focke
Referee:Prof. Dr. Alexander Gail
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EnglishGenetic generalized epilepsy (GGE) is a common epilepsy syndrome and represents the largest group of epilepsies suspected to have a complex genetic etiology. Specific time windows for age of onset and various seizure types that rapidly engage bilateral networks of the brain characterize GGE. Another hallmark of GGE is the occurrence of brief, transient synchronized discharges in the 2-3 Hz range, as observed in the electroencephalogram. To date, there is no clear understanding of how large-scale brain networks behave in the absence of seizures or discharges, that is, during the interictal state in GGE. It is also unclear how this functional state relates to the genetic etiology of the disease. This dissertation presents three studies that address the interictal state in GGE and its functional underpinnings to support diagnostic and therapeutic innovations using electrophysiological imaging phenotypes: In study I, patients with GGE and healthy individuals were measured during the resting-state using magnetoencephalography (MEG). Network power and phase-based connectivity were estimated following a whole-brain approach and surface-based source analyses. An endophenotype approach was adopted, in which also the healthy siblings of the patients were studied to evaluate whether derived network alterations are genetically influenced. In study II, recordings from high-density electroencephalography (HD-EEG) of the same study cohort were analyzed with similar methods as in the first study and statistically combined with the MEG results and structural measures to broaden the understanding of the functional imaging phenotype in GGE. In study III, how power and connectivity vary across the lifespan was examined using a large-scale dataset from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) to advance knowledge of the biological meaning of these markers concerning normative lifespan trajectory and disease development. Overall, this dissertation sheds new light on the interictal state and the causes and consequences of network alterations in GGE by revealing increased connectivity and power and evidence for a genetic contribution. The examinations of the study cohort using both techniques, HD-EEG and MEG, in a broad frequency spectrum adds significantly to the understanding of GGE to date and helps in comparing these findings with those of previous clinical studies. The work in this dissertation further promotes multimodal imaging in GGE that incorporates brain structural features in addition to electrophysiological markers. It also proposes to investigate behavioral and genetic correlates of power and phase-based connectivity across the lifespan and to investigate deviations from the norm that may lead to pathology in GGE. Eventually, this dissertation provides suggestions into how electrophysiological data might be linked to the genetic nature of GGE.
Keywords: MEG; EEG; MRI; resting-state; functional connectivity; imaging endophenotypes; network analysis; epilepsy; lifespan; cortical thickness