CAREER: Towards High-Channel-Count Invasive and High-Resolution Non-Invasive Electrical Neural Interfaces

William Marsh Rice University, Houston TX

Investigators

Abstract

Neural interfaces serve as a powerful tool in neuroscience research to better understand the brain and are increasingly intended for clinical applications. For example, emerging brain-machine interfaces built on the large-scale neural recording can decipher brain activities; the decoded information can then be used to control neural prosthetics to restore lost sensory or motor functions for paralyzed patients. On the neural stimulation side, deep brain stimulation has proven to be highly effective in treating certain brain disorders by injecting a pulsed current with a pre-defined pattern. Although these results are highly encouraging, to fully unlock the potential of neural interfaces for future widespread and standard-of-care human clinical use, new device capabilities need to be developed with significantly improved hardware performance. For invasive neural interfaces, the biggest challenge now is to increase the number of simultaneous recording channels to enable control of more sophisticated prosthetics with higher degrees of freedom. For non-invasive neural interfaces, an emerging need is to develop new stimulation techniques that can replace today’s invasive deep brain stimulations to ensure long-term safety in brain disorder treatment. This project aims to address the above two pressing needs by developing a high-channel-count implanted neural interface and a non-invasive high-focality deep brain stimulation system. Through its coherent educational and outreach plan, this project will also train the next-generation workforce in hardware engineering by engaging graduate, undergraduate, and high-school students in STEM. There are two research thrusts in this project. The first thrust will develop a fully packaged implanted neural interface with higher channel counts of more than ten times of the state of the art. Additionally, the hardware will enable full spectrum coverage to record both local field potentials and action potentials with programmable stimulation capability. The complete hardware module will include a low-power application-specific integrated circuit (ASIC) that can record, stimulate, digitize, and stream out high-throughput neural signals, a flexible intracortical neural probe that will be flip-chip packaged with the ASIC, and a high-speed digital backend that relays the data from the ASIC to a computer for real-time data processing. The second thrust will develop a non-invasive deep brain stimulation system based on temporally interfering EM waves. The research tasks include multi-physics modeling, stimulation hardware implementation, and validation using phantom and animal model. Overall, this research will have the opportunity to impact the key designs in future brain-machine interfaces, neural prostheses, and the treatment of brain disorders. 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.