Measuring, modeling, and manipulating the electrographic markers of disease in epilepsy
Date
2024
DOI
Authors
Version
OA Version
Citation
Abstract
Epilepsy, a complex neurological disorder marked by repetitive and spontaneous seizures, is one of the leading drivers of neurological morbidity worldwide. This thesis investigates epilepsy using scalp electroencephalography (EEG), magnetoencephalography (MEG), intracranial EEG, and behavioral tasks in children and adult populations. The thesis consists of four studies that aim to improve our understanding of the disorder and develop better treatment options.In a first study, we focused on predicting seizure risk. To do so, we analyzed interictal epileptiform discharge (IED) characteristics in 59 children with self-limited epilepsy with centrotemporal spikes (SeLECTS). We showed that specific features of the spike and slow wave complex of an IED – particularly average spike height, spike duration, slow wave rising slope, slow wave falling slope, and the most extreme values of slow wave rising slope – improve prediction of future seizure risk, beyond the expected resolution of SeLECTS with age. Moreover, longitudinal analysis showed the predictive value of spike height. These findings hold clinical significance for patient care and offer insights into the underlying neuronal mechanisms that influence seizure risk.
Next, we examined the thalamocortical sensory motor circuit, a crucial communication pathway affected in SeLECTS. To do so, we used the MEG to measure the median nerve stimulation conduction time from the wrist to the sematosensory cortex. We found that children with SeLECTs exhibited slower nerve conduction times compared to healthy controls, and that the ventral thalamic volume predicted conduction time. In addition, we found more pronounced slowing in children with resolve epilepsy, suggesting that thalamocortical circuit dysfunction might persist even after seizures cease.
In a third study, we explored the electrophysiological response of the thalamus in patients with drug refractory epilepsy to auditory sensory gating, a filtering mechanism for incoming stimuli. While we found SG in the thalamus and at the scalp, we found that thalamic SG - but not scalp-recorded SG - predicted performance on an attention task. Additionally, thalamic and scalp spindle rates - indicators of memory consolidation and cortical development - also predicted attention. These findings highlight the importance of the thalamic reticular nucleus and its role in sensory inhibition and in modulating thalamic sleep spindles, demonstrating the link between thalamic function, sensory processing, and cognitive performance.
The final study investigated the optimization of Closed-Loop Auditory Stimulation (CLAS) for epilepsy. CLAS delivers sound timed to the upstate of the slow oscillation (SO) during sleep, with the goal of enhancing the endogenous brain rhythms – SOs and sleep spindles – that support memory consolidation. We explored the optimal timing and detection parameters for CLAS to increase sleep spindles. We found that CLAS evokes SOs in both the thalamus and cortex. A higher success rate of evoked SOs occurred when the stimulation targeted the upstate of the endogenous SOs, with the impact on spindles depending on the targeted SO amplitude. CLAS during high amplitude SOs negatively impacted memory consolidation of a motor sequence task while CLAS targeting low amplitude SOs evoked a subsequent increase in spindle incidence and positively impacted memory consolidation. These findings indicate a new strategy to target CLAS for improved memory consolidation.
Conclusion: In this thesis, we identify new predictors of seizure risk and investigate the thalamocortical circuit dysfunction in SeLECTS. We also reveal the role of thalamus in sensory processing and attention in patient with refractory epilepsy and develop new approaches to optimize CLAS as a therapeutic avenue for cognitive symptoms in epilepsy.
Description
2024
License
Attribution-NonCommercial-NoDerivatives 4.0 International