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Neuroscience Homepage  > Course Listings > Nsc 5202

About the Course

This course will introduce the concepts of computational and theoretical neuroscience. It will cover (1) general principles of theoretical neuroscience, including distributed representations and information theory, (2) methods for single-cell modeling, including compartmental and integrate-and-fire models, (3) learning rules, including supervised, unsupervised, and reinforcement learning models, and (4) specific systems models, taken from the current theoretical neuroscience literature. Class time will be divided between lecture and discussion. Readings each week will be taken from the current scientific literature. The class is designed for graduate students and for advanced undergraduates.



This course fulfills the electives Category B (Neural Systems and Behavior) for undergraduate neuroscience major. For more information on the degree see the Neuroscience Major Requirements.


Photo Above

Photo, above, by Dr. A. David Redish, depicts average waveforms from six cells simultaneously recorded from a striatal tetrode.


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Graduate Program in Neuroscience


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