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This story is from the category Conferences
Date posted: 06/08/2007 Friday, August 17, 2007 Orlando, Florida, USA Brain-Machine Interfaces (BMI) communicate with the nervous system to provide lost sensory input, repair connectivity between brain structures, or translate intention of movement to treat the paralyzed, blind, and deaf. They require beyond state of the art electronics and data processing methods to effectively interact with the nervous system. Underlying these applications, we will discuss the computational challenges for understanding how individual neurons, neural circuits, and systems interact through spikes, LFPs, ECoGs, EEGs, and EMG to produce behaviour. This workshop will also study recent innovations including the use of data driven experimental paradigms in animals and humans to improve the fundamental concepts and computational modeling framework for explaining the physiological relationships in real neural and behavioral datasets. New quantitative tools to extract and represent control features from multivariate datasets will be introduced. - Control feature extraction from spikes, LFPs, ECoG, and EEG - Data compression and representation of neural activity - Optimisation of input-output models for mapping neural activity to behaviour - Computing with spikes - Strategies for dealing with nonstationarities in real BMI applications - Techniques to analyze the spatio-temporal processes that activate behaviour See the full Story via external site: nrg.mbi.ufl.edu Most recent stories in this category (Conferences): 03/03/2017: ICME 2017 - Large Scale 3D Human Activity Analysis |
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