Wednesday, February 5, 2025
2/5/2025
Scientific abstract Epilepsy is a chronic and debilitating disease, leading to refractory seizures in up to 40% of patients. A better understanding of the neural mechanisms that cause recurrent seizures could lead to improved diagnostic markers and new neuroprotective therapies. My recent research suggests that abnormal slow-wave activity (SWA) patterns during sleep may constitute a promising diagnostic marker to locate the seizure onset zone (SOZ). In a high-density electroencephalogram (hdEEG) study of fifteen focal epilepsy patients, I found increases in sleep SWA that were maximal in the SOZ and were correlated with seizure and interictal spike frequency. Building on a wealth of studies validating sleep SWA as a marker of synaptic strength, my results suggest that seizures and spikes induce synaptic potentiation in the human brain. To further validate sleep SWA as a diagnostic marker for the SOZ, I aim to make use of the higher spatio-temporal resolution of direct intracranial EEG (iEEG) recordings. In Aim 1, I will analyze continuous iEEG recordings in patients with focal epilepsy to quantify sleep SWA in the SOZ, in the seizure propagation network (SPN, areas secondarily recruited in the ictal rhythm), and in the periphery (areas not involved in the ictal rhythm). I hypothesize that 1) in the SOZ, SWA will increase maximally; 2) in the periphery, sleep SWA will have lower values; and 3) the SPN will show intermediate patterns. In Aim 2, I will also analyze single-unit (SU) recordings to identify the neuronal contributors to sleep SWA during sleep and their alterations across seizure territories. I will use existing long-term microelectrode recordings from epileptic patients to quantify SU firing rates and multi-unit activity (MUA) synchrony during sleep (two markers of synaptic strength) in the SOZ, the SPN, and the periphery. To shed light on the relationship between increased sleep SWA and ictal firing rates, I will use the SU recordings to separate the SPN into areas of high vs. low ictal firing rates (the ictal core vs. ictal penumbra, respectively). I hypothesize that 1) in the SOZ, SU firing rates and MUA synchrony will increase maximally; 2) in the periphery, SU firing rates and MUA synchrony will show lower values; and 3) the SPN will show intermediate patterns, but with more normal values overall in the ictal penumbra compared to the ictal core. If this project is successful, it will provide mechanistic evidence for a link between chronic hyperexcitability in the epileptic network and synaptic potentiation due to seizures, which can be sensitively detected using intracranial sleep EEG. It will also allow researchers and clinicians to develop new diagnostic tools to localize the SOZ, paving the way for new therapeutic interventions targeting sleep to decrease seizure frequency in patients with epilepsy.
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