A semiparametric PCA approach to fMRI data analysis

Functional Magnetic Resonance (fMRI) data is most often analyzed using linear regression type methods that consider each voxel separately or by using exploratory methods such as Principal Component Analysis (PCA) or Independent Component Analysis (ICA). In this paper we introduce a model, which we call XnPCA, that combines regression with PCA. Unlike the… (More)