15-490 Special Topic: Computational Neuroscience

Units: 9.0 Department: Computer Science Prerequisites: 15-113 and (18-202 or 21-241) Related URLs: http://www.csd.cs.cmu.edu An introduction to computational neuroscience, i.e. the application of computational and mathematical concepts and techniques to the study of the brain. Students will learn the fundamentals of signals and systems, pattern analysis, probability theory and information theories and apply these techniques to study how the real nervous systems compute, communicate and learn at many levels, from synapses to neurons, from neuronal populations to systems. Topics include basic anatomy and physiology of neurons and the mammalian nervous systems, biophysics of single neurons, excitable membranes and cable equation, encoding and decoding of information in single neurons and neuronal ensembles, neural adaptation and learning, signal detection and reconstruction, distributed and hierarchical computations. Concrete examples will be drawn from visual and motor systems and studied from both biological and computational perspectives. Students will do a number of Matlab programming and mathematical exercises to consolidate their learning, participate in the analysis of real neuronal data. No prior background in biology is assumed.

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Spring 2005 times

No sections available for semester Spring 2005.