This course will provide a broad introduction to basic mathematical and computational tools for a quantitative analysis of neural systems. Integrated lectures, MATLAB sessions, and homework sets will introduce techniques and help us learn to apply them. We will cover a range of topics, including neural encoding and decoding, population codes, filtering, correlation, convolution, spike-triggered averaging (reverse correlation), deconvolution, and dimensionality reduction, clustering, and spike-sorting through principal components analysis, as well as some probability and Bayesian
M 408N is the first-semester calculus course of the three course calculus sequence. It is directed at students in the natural sciences, and is restricted to College of Natural Science Students. The emphasis in this course is on problem solving, not on the presentation of theoretical considerations. While the course includes some discussion of theoretical notions, these are supporting rather than primary.
The syllabus for M 408N includes most of the basic topics in the theory of differential calculus of functions of a real variable: algebraic, trigonometric,