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Neural adaptations to a brain-machine interface

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Abstract:
The advent of multi-electrode recordings and brain-machine interfaces (BMIs) has provided a powerful tool for the development of neuroprosthetic systems for people with sensory and motor disabilities. BMIs are powerful tools that use brain-derived signals to control artificial devices such as computer cursors and robots. By recording the electrical activity of hundreds of neurons from multiple cortical areas in subjects performing motor tasks we can study the spatio-temporal patterns of neural activity and quantify the neurophysiological changes occurring in cortical networks, both in manual and brain control modes of operation. In this talk I will present exciting results from our lab showing that the brain can consolidate prosthetic motor skill in a way that resembles that of natural motor learning. Using stable recording from ensembles of units from primary motor cortex in two macaque monkeys we demonstrate that proficient neuroprosthetic control reversibly reshapes cortical networks through local effects. This will be followed by an outline on the emerging directions the field is taking towards the development of neuroprosthetic devices for the impaired.

Type of Seminar:
IfA Seminar
Speaker:
Prof. Jose Carmena
Department of Electrical Engineering & Computer Sciences , Helen Wills Neuroscience Institute , University of California, Berkeley
Date/Time:
Nov 09, 2010   10.15
Location:

ETH, Gloriastrasse 35, ETZ E8
Contact Person:

John Lygeros
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Biographical Sketch:
Jose M. Carmena received the B.S. and M.S. degrees in electrical engineering from the Polytechnic University of Valencia (Spain) in 1995 and the University of Valencia (Spain) in 1997. Following those he received the M.S. degree in artificial intelligence and the Ph.D. degree in robotics both from the University of Edinburgh (Scotland, UK) in 1998 and 2002 respectively. From 2002 to 2005 he was a Postdoctoral Fellow at the Department of Neurobiology and the Center for Neuroengineering at Duke University (Durham, NC). In the summer of 2005 he was appointed Assistant Professor in the Department of Electrical Engineering and Computer Sciences, the Program in Cognitive Science, and the Helen Wills Neuroscience Institute at the University of California, Berkeley. He is senior member of the IEEE (RA, SMC and EMB societies), Society for Neuroscience, and the Neural Control of Movement Society. He has been the recipient of the Aspen Brain Forum Prize in Neurotechnology (2010), the National Science Foundation CAREER Award (2010), the Sloan Research Fellowship (2009), the Okawa Foundation Research Grant Award (2007), the UC Berkeley Hellman Faculty Award (2007), and the Christopher Reeve Paralysis Foundation Postdoctoral Fellowship (2003). His research interests span across systems neuroscience (neural basis of sensorimotor learning and control; neural ensemble computation) and neural engineering (brain-machine interfaces; neuroprosthetics; biomimetic robotics).