This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning. We will make use of Matlab/Octave/Python demonstrations and exercises to gain a deeper understanding of concepts and methods introduced in the course. The course is primarily aimed at third- or fourth-year undergraduates and beginning graduate students, as well as professionals and distance learners interested in learning how the brain processes information.
These papers have not been peer-reviewed, but are circulated by their authors for comment and discussion. With the NBER's blessing, Making Sen$e is pleased to feature these summaries regularly on our page. The following summary was written by the NBER and doesn't necessarily reflect the views of Making Sen$e. Online coursework has been heralded as potentially transformative for higher education, but little is known about whether it increases the number of people pursuing education or simply substitutes for existing options. In "Can Online Delivery Increase Access to Education?"
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