Fig. 1.

Illustration of the framework of supervised stochastic coordinate coding (SCC) for task fMRI data modeling. (a) FMRI signals in the brain mask are extracted and organized into a signal matrix S. (b) S is decomposed into a dictionary matrix D and a sparse code matrix A by the supervised SCC. D_C: Fixed dictionary atoms. D_R: learned dictionary atoms for constrained spatial patterns. D_l: Automatically learned dictionary atoms. A_C: learned spatial maps corresponding to D_C. A_R: Restricted spatial maps while learning. A_l: Automatically learned concurrent networks. (c) Each row of A can be mapped back to brain volume as a spatial network.