Engineering Targeted Electrical Treatments for Neurological and Non-Neurological Disorders

Electrical neuromodulation is a powerful alternative to pharmaceuticals that treats disease by electrically targeting select parts of the central or peripheral nervous systems. This neurotechnology has transformed clinical management of diseases in which pharmaceuticals alone are less effective, such as chronic pain and late-stage Parkinson’s disease. Recent electrical neuromodulation work shows promise for enhancing neurorehabilitation options and for improving management of disease in at-risk populations such as hypertension or diabetes. However, despite this transformative potential, average efficacy rates of established neuromodulation therapies remain at approximately 60% due to imprecise energy delivery, therapy-limiting side effects, and a poor understanding of therapeutic mechanisms. Precision tools—computational modeling, novel neuromodulation strategies, and data-driven approaches—are poised to increase the therapeutic response rates substantially by addressing each of these challenges through personalization of therapies and improved control over energy delivery. In this talk, I demonstrate how the combined use of computational and in vivo experimental methods in neuromodulation can advance our ability to develop these precision tools in the central and peripheral nervous system. In the central nervous system, I show how model-based optimization algorithm frameworks can improve the efficacy and efficiency of deep brain stimulation therapy for treating brain disorders. In the peripheral nervous system, I show how the discovery of novel types of kilohertz-frequency signals can inactivate neural activity efficiently and with minimal undesired activation. The presented work illustrates the power of combining computational models and in vivo approach. This dual strategy has broad applicability to innovate precision neuromodulation technologies for treatment of neurological and non-neurological disorders.