Task fMRI data analysis based on supervised stochastic coordinate coding

187In this paper, we propose a novel supervised sparse representation and dictionary learning framework, named supervised stochastic coordinate coding (SCC), for task fMRI data analysis, in which certain brain networks are learned with known information such as pre-defined temporal features and spatial network patterns, and at the same time other concurrent networks are learned automatically from data. The proposed method takes advantages of both hypothesis-driven methodology and data-driven methodology for fMRI analysis.