Jiayu Zhou was awarded an NSF grant as a co-PI

Wen Li (PI), Associate Professor of Electrical and Computer Engineering,  Jiayu Zhou (Co-PI), Assistant Professor of Computer Science and Engineering, and  researchers from North Carolina State University and Georgia Tech have been award an NSF grant:

 

Title: 

Collaborative Research: NCS-FO: Intelligent Closed-Loop Neural Interface System for Studying Mechanisms of Somatosensory Feedback in Control of Functional and Stable Locomotion

 

Abstract:

Sensory feedback from moving legs is critical for functional and dynamically stable locomotion. Although it is clear that motion-related sensory feedback influences inter-leg coordination and selection of gaits (walking, trotting, galloping, etc.), it is not known which sensory modalities (e.g., muscle length- or force-related signals) and sources of feedback (e.g., hip or knee muscles) mediate these locomotor changes. Therefore, this project aims to understand how sensory neurons providing information about the length of hip muscles regulate interlimb coordination and gait selection. This goal will be accomplished by selectively and reversibly stimulating these sensory neurons in an intelligent, closed-loop, and well-controlled manner. This project will lead to the development of new neural implant tools and associated computational algorithms for an in-vivo manipulation of motion-related sensory signals in a large animal model, the cat. The new findings of this project and the developed methods will substantially enhance our understanding of the mechanisms of sensory locomotor control and contribute to developing novel therapeutic interventions. The proposed multidisciplinary research approaches will also significantly expand the utility and capabilities of the rapidly growing field of optogenetics, enabling transformative research and providing unprecedented new experimental tools for neuroscience. The most noticeable long-term benefits of this work to society will be an improvement in the quality of life for a sizable population of people affected by a wide range of movement deficits, from limb loss to sensory neuropathy. These individuals will benefit from the development of revolutionary neural interfaces between the nervous and engineering systems controlled by machine learning algorithms.