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Imperial College London > Talks@ee.imperial > Featured talks > Targeted Neuroplasticity: Natural and Artificial Shaping of Neural Correlations for Cognitive Neural Interfaces
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Targeted Neuroplasticity: Natural and Artificial Shaping of Neural Correlations for Cognitive Neural InterfacesAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Wiesia R Hsissen. Our ultimate understanding of the brain as a complex system is reflected in our ability to predict its dynamics in the normal state and eventually control these dynamics in the pathological state. Interest in interfacing with the brain at the neural ensemble level has been surging, primarily due to striking advances in technology intended to measure and manipulate neural dynamics with cell type specificity at exceedingly high temporal and spatial resolutions, and to characterize the interplay between the brain’s structure and function. In this talk, I will discuss our recent efforts to characterize the neural ensemble coding of tactile, working memory and motor control in awake behaving animals, and demonstrate how naturally evolving correlations in these ensembles subserve learning and memory formation. Complementing this framework is a systematic approach to artificially shape these correlations via electrical or optogenetic stimulation in order to accelerate learning to control a brain machine interface. I will conclude by summarizing our ongoing work aimed at facilitating this process through peripheral nerve stimulation to accelerate cognitive skill learning for basic and clinical neuroscience applications. BIO : Karim G. Oweiss received his Ph.D. degree (2002) in Electrical Engineering and Computer Science from the University of Michigan, Ann Arbor. From 2003-2014, he was with the faculty at the Department of Electrical and Computer Engineering, the Neuroscience and the Cognitive Science Programs at Michigan State University. In 2014, he joined the University of Florida where he is currently a pre-eminent professor of Electrical and Computer Engineering and Biomedical Engineering and a member at the McKnight Brain Institute. His research interests span the areas of neural integration and coordination in sensorimotor systems, and the engineering of clinically viable brain machine interfaces for restoring, replacing or augmenting damaged neurological functions, in which he has published over 160 peer-reviewed, full-length publications. Dr. Oweiss is a senior member of the IEEE and a member of the Society for Neuroscience. He serves on the technical committees of the IEEE Biomedical Circuits and Systems, the IEEE Life Sciences, and the IEEE Engineering in Medicine and Biology societies. He received the excellence in Neural Engineering award from the National Science Foundation in 2001. His lab has been supported for +15 years by the Neural Interfaces and the Repair and Plasticity Programs at the National Institute of Neurological Disorders and Stroke, as well as DARPA ’s Reliable Central-Nervous-System Interfaces and the Targeted Neuroplasticity Training Programs at the US Department of Defense. He is the editor and co-author of the book: Statistical Signal Processing for Neuroscience and Neurotechnology, published by Academic Press in 2010. This talk is part of the Featured talks series. This talk is included in these lists:
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