Introduction to Neural Computation
MIT OpenCourseWare's introduction to quantitative neuroscience covers mathematical descriptions of neurons, how neurons respond to sensory stimuli, and simple neuronal networks, along with statistical inference and decision making. The course builds the quantitative toolkit needed for data analysis in neuroscience, including correlation, convolution, spectral analysis, and principal components analysis, plus the underlying mathematics of differential equations and linear algebra. Materials include lecture notes, problem sets, and MIT's standard OCW course structure, free to access with no certificate attached. It suits students with some math background who want to understand brain function through models rather than description alone, bridging computational methods and experimental neuroscience.