CAREER: Multi-channel, Sub-microliter Implants for Selective Neuromodulation

Bioelectronic medicine can revolutionize how we practice medicine in offering effective non-opioid pain management, and providing compelling alternatives to other pharmaceuticals for conditions such as epilepsy, traumatic brain injury, high blood pressure, rheumatoid arthritis, sleep apnea, urinary incontinence, and treatment-resistant depression. Bioelectronic medicines are neurotechnology devices that read and modulate the electrical activity of the body’s nervous system to control, regulate, or restore function. Medical care that uses these devices to continuously monitor physiological biomarkers and autonomously deliver therapy will significantly reduce clinician burden, improve patient compliance, and reduce adverse drug reactions and abuse. However, current bioelectronic medicine devices are too large to target small nerves for effective therapy, deliver indiscriminate stimulation on large nerves resulting in significant off-target effects, and lack the sophistication for closed-loop, automated processing. This project will address these issues through key innovations in circuit design, system development, and closed-loop control. Project impact is extended through a multi-tiered education initiative to bolster the local semiconductor and neurotechnology workforce with collaboration from industry experts.This project will develop a wireless, miniaturized neurotechnology interface that selectively records and stimulates from specific fascicles within a larger nerve. The proposed work will make advances in three areas. First, the project will develop and validate a new stimulation technique that significantly reduces the volume of an implant and improves its safety and reliability regardless of electrode size. Second, the project will develop a new bi-directional wireless link that exceeds state-of-the-art efficiencies by co-design recording, stimulation, and wireless circuitry. Lastly, the project will use this new interface to evaluate machine learning optimization systems in a closed-loop experiment that targets specific nerve fascicles in the sciatic nerve of an animal model.This project is jointly funded by ECCS and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.