Abstract

Mesial Temporal Lobe Epilepsy (MTLE) is the most common symptomatic focal epilepsy, with hippocampal sclerosis (HS) representing the most commonly occurring pathology linked to MTLE. In the past HS has been understood to represent a focal neuropathological alteration linked to the generation of seizures (i.e., the epileptic focus). However, the phenomenon that not all patients become seizure-free after surgical resection of the hippocampus has given rise to the concept that seizures and interictal epileptiform spikes and sharp waves (IES) captured by electroencephalography (EEG) in MTLE result from activity in a functionally connected epileptogenic network of brain regions. Large-scale network dynamics may thus be involved in the generation of IES and the temporal synchronisation of network structures may be an important factor in spike generation. Surgical outcome may be improved by broadening the focus from the identification of a single epileptogenic region to the characterisation of temporally synchronous epileptogenic networks associated with spikes. A common way to identify functional networks is to assess functional connectivity (FC) between spatially distinct brain regions. FC measures the degree of covariance between the activity in a specific brain region and other areas across the whole brain. The simultaneous acquisition of EEG and functional magnetic resonance imaging (fMRI) enables the identification of functional networks in which haemodynamic changes are time-locked to spikes. Nevertheless, whether this reflects the propagation of neural activity from a ‘focus’, or conversely the activation of a network linked to spike generation remains controversial. Delineation of functional connectivity patterns related to IES may be useful in shedding light on the mechanisms underlying their generation, and potentially of seizures in MTLE. Although the exact physiologic relationship between IES and seizures is not fully understood, there is a growing evidence to suggest that the neural network involved in generating IES is a reliable estimator of the network that generates seizures. My PhD aimed to explore the changes in brain network function that predispose the generation of IES using EEG-fMRI in patients with MTLE. I collected EEG-fMRI data from two groups of subjects: patients with MTLE and healthy controls. First, I examined MTLE patients to assess the presence of altered functional network connectivity identifiable immediately prior to the appearance of interictal spikes on EEG. A fundamental finding was the significant loss of bilateral hippocampal FC before the appearance of electrographic spikes. Second, I explored the changes in FC of different resting state networks during rest in patients compared to controls and changes in FC in relation to IES in MTLE patients. Specifically, I examined the FC of the default mode (DMN), salience (SN), and dorsal attentional (DAN) networks and found significant differences between patients and controls in all three networks during rest and prior to spikes. Third, I compared morphometric measures of the hippocampus and of anatomical nodes in the resting state networks between MTLE patients and controls and investigated their correlation with pre-spike FC patterns. I observed structural differences between MTLE patients and controls in the left hippocampus and in the major nodes of the DMN, SN, and DAN. Additionally, I found that these structural changes strongly correlated with pre-spike FC alterations. This project provides novel insights into the brain networks involved in the genesis of IES. Examining resting state networks in MTLE may improve identification of altered function within the epileptogenic network and lead to better understanding of neural functional organisation in patients with MTLE. Findings from this project may have important implications in future studies in the area of epilepsy surgery through the recognition of the brain networks crucial for the production of spikes and seizures.

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