Examining the relationship between brain function and structure on voxel-by-voxel-basis

In neuroimaging studies, several imaging modalities are commonly used together, but the images are often analyzed separately for different modalities. To address this, I present two massively univariate statistical methods to analyze functional and structural brain imaging data together on voxel-by-voxel basis. In the first example, a permutation-based nonparametric method is used on imaging data from Alzheimer´s disease patients. In the second example, a multi-modal cross-correlation analysis is performed in a dyslexia study. Finally I outline voxel-based network analysis as a potential future direction in analyzing multi-modal brain imaging data.