Colloquium Details
Faculty Search Colloquium: Algorithms for Understanding Motor Cortical Processing
and Neural Prosthetic Systems
| Author: | John P. Cunningham Stanford University |
|---|---|
| Date: | March 12, 2009 |
| Time: | 9:30 |
| Location: | 220 Deschutes |
| Host: | Sarah Douglas |
Abstract
Our seemingly effortless ability to make coordinated movements belies the sophisticated computational machinery at work in our nervous system. Much has been learned about motor cortical processing with classical systems neuroscience approaches. In recent years, the field has been dramatically expanding the complexity of its data acquisition technologies and experiments. This shift seeks to deliver a much deeper understanding of cortical processing and a much improved ability to control neural prosthetic devices (also called brain-machine interfaces). Paying this off, however, requires analytical and computational methods that can exploit this changing paradigm. I will discuss a few examples of our algorithmic developments for understanding cortical processing and for applied prosthesis work. I will focus particularly on our efforts to use machine learning technologies to extract population-level signatures of neural activity in the brain's motor system. I will discuss future directions of this work, particularly as it pertains to neural prosthetic systems, and I will also point to the broader implications this work should have for computer science, engineering, and neuroscience.
Biography
John P. Cunningham received the A.B. degree in computer science from Dartmouth College in 2002. He received the M.S. degree in electrical engineering in 2006 from Stanford University, where he is currently working toward the Ph.D. degree in electrical engineering. At Stanford, he is a member of the Neural Prosthetic Systems Laboratory, and he is the Michael Flynn Stanford Graduate Fellow. His research interests include machine learning techniques, their application to characterizing multi-channel neural data and to understanding cortical processing, and the development of decoding algorithms for neural prosthetic systems. www-npl.stanford.edu/~jcunnin