NSF-Research Training Group
Project: Quantification of brain connectivity from neuroimaging time series data
Mentors: Owen Carmichael (Neuroscience) and Hans-Georg Müller (Statistics)
Resting state functional magnetic resonance imaging (rs-fMRI) data consists of time series of brain activity measured at hundreds of thousands of locations in the brain of a living animal. Functional connectivity describes the degree of similarity between random functions observed as fMRI BOLD signals at distinct brain locations. This project will explore the development and comparison of statistical methods for quantifying the similarity of such random functions and will include studying and presenting relevant literature. Participating students will learn the fundamentals of time series similarity quantification and implement various measures of functional similarity. These measures will be applied and compared for real rs-fMRI data sets of young healthy people, old healthy people, and old people with brain diseases including Alzheimer's disease. Pre-requisites include successful completion of Statistics 131A and 141 and experience in programming with R or Matlab. Working knowledge of C is a plus but is not required.