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Events for May 12, 2014
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"Real-Time Brain-Machine Interface Architectures: Algorithmic Development and Experimental Implementation"
Mon, May 12, 2014 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Maryam Shanechi, Assistant Professor/Cornell University
Talk Title: "Real-Time Brain-Machine Interface Architectures: Algorithmic Development and Experimental Implementation"
Abstract: A brain-machine-interface (BMI) is a system that interacts with the brain either to allow the brain to control an external device or to control the brain's state. In this talk, I present my work on developing both these types of BMIs, specifically motor BMIs for restoring movement in paralyzed patients and a new BMI for control of the brain state under anesthesia. Motor BMI research has largely focused on the problem of restoring the original motor function by using standard signal processing techniques. However, devising novel algorithmic solutions that are tailored to the neural system can significantly improve the performance of these BMIs. Moreover, while building high-performance BMIs with the goal of matching the original motor function is indeed valuable, a compelling goal is that of designing BMIs that can enhance original motor function. Here, I first develop a novel BMI paradigm for restoration of natural motor function that incorporates an optimal feedback-control model of the brain and directly processes the spiking activity using point process modeling. I show that this paradigm significantly outperforms the state-of-the-art. I then introduce a BMI architecture aimed at enhancing original motor function that decodes all the elements of a sequential motor plan concurrently prior to movement. I demonstrate the successful implementation of both these designs in rhesus monkeys. I also present a motor BMI for control of the native limb that decodes neural activity from an alert subject to generate arm movements in a second temporarily paralyzed subject by stimulating its spinal cord. In addition to motor BMIs, I construct a new BMI that controls the state of the brain under anesthesia. This is done by designing stochastic controllers that infer the brain's anesthetic state from non-invasive observations of neural activity and control the real-time rate of drug administration to achieve a target brain state. I show the reliable performance of this BMI in rodent experiments.
Biography: Maryam M. Shanechi is an assistant professor in the School of Electrical and Computer Engineering at Cornell University. Her research focuses on using the principles of information and control theories and statistical signal processing to develop effective algorithmic solutions to basic and clinical neuroscience problems. Her work combines methodology development with in vivo implementation and testing. She received the B.A.Sc. degree with honors in Engineering Science from the University of Toronto in 2004 and the S.M. and Ph.D. degrees in Electrical Engineering and Computer Science (EECS) from the Massachusetts Institute of Technology (MIT) in 2006 and 2011, respectively. She has held postdoctoral fellowships at Harvard Medical School and in the EECS department at the University of California, Berkeley.
Host: Dr. Sandeep Gupta
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Progress towards monitoring of ambient particulate matter using satellite and aircraft remote sensing
Mon, May 12, 2014 @ 02:30 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: David J. Diner , JPL - California Institute of Technology
Talk Title: Progress towards monitoring of ambient particulate matter using satellite and aircraft remote sensing
Abstract: Exposure to ambient particulate matter (PM) has been consistently linked to adverse health effects including cardiovascular and respiratory diseases, heart attacks, low birth weight, and premature death. According to the 2010 Global Burden of Disease Study, ambient (outdoor) PM causes over 3 million premature deaths in a single year. Although surface stations are currently used to monitor PM concentrations, their sparse distribution can lead to errors in establishing accurate exposure levels, and they are unable to provide the level of spatial detail needed to link different aerosol species to given health effects. By using passive remote sensing (that is, inference of particle properties by observing backscattered sunlight from a high-altitude platform), significant progress has been made in recent years to differentiate particle types using a combination of Multispectral, multiangular, and polarimetric observations. Establishment of regression relationships between column aerosol loading and the concentration of near-surface particulates measured by surface monitors makes it possible to use the coverage provided by satellite and airborne instruments to map PM with contiguous spatial coverage.
At JPL, we have been developing observational technologies to map aerosol abundance and type by remote sensing. The Multi-angle Imaging SpectroRadiometer instrument has been flying on NASA's Terra spacecraft since 1999, and has demonstrated the value of supplementing multispectral measurements with observations at different view angles to separate scattering by aerosols from reflection by the underlying surface, enhance the visibility of thin aerosols, distinguish spherical and nonspherical particles, and track the injection heights of discrete aerosol plumes. More recently, we have been flying the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) instrument on NASA's high-altitude ER-2 aircraft. Interaction of sunlight with the atmosphere polarizes the light, providing an additional tool for diagnosing the size distribution and optical properties of airborne particles. In this talk I will discuss how an integrated approach in which remote sensing data, additional particle type constraints provided by chemical transport models, and in situ particle monitors has the potential to provide a cost-effective global PM monitoring system to benefit the health of future generations.
Biography: David J. Diner is a Senior Research Scientist at the Jet Propulsion Laboratory, California Institute of Technology and Principal Investigator of the satellite Multi-angle Imaging SpectroRadiometer (MISR) and Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) instruments. He is also Supervisor of the Aerosol and Cloud Science Group at JPL. Dr. Diner received the B.S. degree in Physics from the State University of New York at Stony Brook, and the M.S and Ph.D. degrees in Planetary Science from Caltech. He has been involved in numerous NASA planetary and Earth remote-sensing investigations, and is the recipient of both the NASA Outstanding Leadership and Exceptional Achievement medals.
Host: Bhaskar Krishnamachari
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Shane Goodoff
