Matlab Tool: Functional Regression Analysis of DTI tract Statistics

Diffusion tensor imaging (DTI) provides important information on the structure of white matter fiber bundles as well as detailed tissue properties along these fiber bundles in vivo. A functional regression framework, called FRATS and implemented by Matlab, was presented for the analysis of multiple diffusion properties along fiber bundle as functions in an infinite dimensional space and their association with a set of covariates of interest, such as age, diagnostic status and gender, in real applications. The functional regression framework consists of four integrated components: (1) the local polynomial kernel method for smoothing multiple diffusion properties along individual fiber bundles, (2) a functional linear model for characterizing the association between fiber bundle diffusion properties and a set of covariates, (3) a global test statistic for testing hypotheses of interest, and (4) a resampling method for approximating the p-value of the global test statistic. The resulting analysis pipeline can be used for understanding normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles.