Statistical Methods for Neuroimaging

Catalog description

This course is intended for students interested in both statistical methodology, and the process of developing this methodology, for the field of neuroimaging. This will include quantitative techniques that allow for inference and prediction from ultra-high dimensional and complex images. In this course, basics of imaging neuroscience and preprocessing will be covered to provide students with requisite knowledge to develop the next generation of statistical approaches for imaging studies. High-performance computational neuroscience tools and approaches for voxel- and region-level analyses will be studied. The multiple testing problem will be discussed, and the state-of-the art in the area will be examined. Finally, the course will end with a detailed study of multivariate pattern analysis, which aims to harness patterns in images to identify disease effects and provide sensitive and specific biomarkers. The student will be evaluated based on 3 homework assignments and a final in-class presentation. Prerequisite: If course requirement not met, permission of instructor required.