The goal of this course is to introduce you to basic computational techniques for analyzing, modeling, and understanding the behavior of cells and circuits in the brain. 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 exercises to gain a deeper understanding of concepts and methods introduced in the course. No prior background in neuroscience is required but familiarity with basic concepts in linear algebra, calculus, and probability theory would be useful.
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