fMRI Bootcamp
A nine-part MIT OpenCourseWare video series on how to think about functional MRI data rather than just how to run the software. It opens with the basics of anatomical and functional MRI and the shape of the fMRI signal over time, then moves through univariate and multivariate analysis, multivoxel pattern analysis, classification, representational similarity, corrections for multiple comparisons, and hyperalignment. Lectures come from Rebecca Saxe's lab at MIT and focus on the logic behind each analysis step, the questions a researcher should ask before running a model, and the tradeoffs between methods. The series links out to lab resources and pairs with Poldrack, Mumford, and Nichols' Handbook of Functional MRI Data Analysis for readers who want the underlying math. No assignments or certificate, just the recorded lectures and supporting materials, aimed at students already comfortable with basic neuroscience and statistics.