Computational Neuroscience for Interdisciplinary Scientists

Description: Lecture, two hours; laboratory, one hour. Requisites: course M101A or Psychology 115; Life Sciences 30A and 30B, or Mathematics 3A, 3B, and 3C, or 31A, 31B, and 32A; Life Sciences 40 or Psychology 100A or Statistics 10 or 13. Designed for students in both experimental and computational tracks to acquire significant breadth and depth in computational neuroscience. Highly interdisciplinary study in computational neuroscience. Integrates data-driven modeling, simulations, and analyses of neural dynamics to train students in hypothesis-driven approach to computational modeling. Students can immediately apply acquired knowledge and skills in research or industry settings. Concurrently scheduled with course C251. P/NP or letter grading.

Units: 4.0
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