This course is designed to cover the basic principles and computational methods required for quantitative analysis of the two most common functional imaging techniques: functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). These imaging techniques are widely used in many different disciplines such as psychiatry, neurology, neurosurgery, radiology, psychology, etc. The course begins with a short introduction to the acquisitional aspect of each technique, but mostly focuses on quantification and computational processes used for functional imaging data analysis. In addition, an overview of human brain anatomy and physiology, as well as necessary statistical and digital signal processing methods, is provided.
There are two textbook for this course:
- Functional Magnetic Resonance Imaging by Scott Huttel, et. al. third edition
- Positron Emission Tomography: Basic Sciences by Dale Bailey, et. al.
Bi-weekly homework is assigned to familiarize students with existing concepts in functional imaging techniques, and lab sessions allow students use and practice with the existing open source software packages (such as SPM, FSL, or etc). Preliminary coding skill in Matlab (or Python) is required. A final project draws upon the cumulative course material.
Upon completion of the course, students will have gained the preliminary skill set necessary to conduct independent analysis of fMRI and PET imaging data.