BGGN 201. Methods in Computational Neuroscience (3 units)
Link to catalog page: https://catalog.ucsd.edu/courses/BIOL.html#bggn201
Description
Introduction to the computational methods most frequently used in neuroscience research. Aimed at first-year graduate students in neuroscience and related disciplines. Minimal quantitative background will be assumed. Topics include Poisson processes, Markov Chains, auto- and cross-correlation analysis, Fourier/Spectral analysis, principal components/linear algebra, signal detection theory, information theory, Bayes Theorem, hypothesis testing. Nongraduate students may enroll with consent of instructor.
Prerequisite courses
BGGN 201 has no prerequisite courses.
Successor courses
No courses have BGGN 201 as a prerequisite.