Personalized Deep Brain Stimulation for Epilepsy

Mayo Clinic Rochester, Rochester MN

Investigators

Abstract

PROJECT SUMMARY/ABSTRACT Epilepsy impacts 1% of the US population with a third experiencing drug-resistant epilepsy. FDA-approved treatments like anterior nucleus of the thalamus deep brain stimulation, and thalamic responsive neurostimulation show great promise, however, rarely achieve seizure freedom. Thalamic neuromodulation is limited by a generic approach to electrode targeting and stimulation parameter selection, which does not account for highly variable patient specific seizure network (SN) structure and excitability. Our hypothesis is that optimal thalamic neuromodulation requires a highly personalized approach, with SN-specific electrode targeting, and short-latency biomarkers for efficient data-driven optimization of stimulation parameters. The objectives of this research are to 1) delineate and measure precise causal connections within brain networks (effective connectivity) using single pulses of stimulation delivered through stereotactic intracranial EEG (sEEG) leads, and 2) characterize thalamic neuromodulation induced changes in network excitability using short-latency electrophysiology biomarkers. Here, we will employ clinical intracranial stereotactic EEG (sEEG) that includes a thalamus electrode, and single pulse and repetitive high frequent stimulation to map, characterize, and modulate brain networks. We aim to 1) map thalamocortical effective connectivity using single pulse electrical stimulation during sEEG (3-4 thalamus stimulation sites, and approx. 200 recording locations per individual); 2) characterize the temporal structure of thalamocortical evoked potentials in non-seizure and seizure networks using a data- driven computational machine-learning approach (identify specific features that distinguish normal from seizure networks); and 3) characterize thalamic high frequency stimulation induced changes on network excitability, and the timescales of effects. This work aims to develop a highly personalized approach to thalamic neuromodulation, with seizure network specific electrode targeting and data-driven stimulation parameter optimization. Lastly, we will use an ethics framework to gather and integrate patient perspectives on precision neuromodulation to ensure that efforts align with patient priorities. My career development objectives are to gain expertise in: 1) multimodal brain network mapping, integrating electrophysiology and imaging techniques (SA1), and 2) advanced signal processing and machine- learning methods for data-driven feature classification (e.g. distinguish normal from seizure networks (SA2); quantify stimulation induced changes in excitability (SA3)). I will develop independent expertise with flexible neuromodulation systems (g.tec, NeuraLynx, Cadence) (SA1, 3). Further, I will pursue comprehensive training in translational research, clinical trial conduct, and grant writing, equipping me for the shift to an independent research career. This career development award is pivotal for my progression towards independent RO1 funding and provides the foundation for clinical trials in personalized thalamic neuromodulation for epilepsy.