Sparse representation of whole-brain fMRI signals for identification of functional networks

Overview of the computational pipeline of identifying functional brain networks via sparse representation of whole-brain fMRI signals. (a) An example of the learned sparse dictionary of 400 functional components (indexed by the horizontal axis). The vertical axis stands for the occurrence frequency of each component in over 40,000 fMRI BOLD signals in a whole brain. The three dictionary components highlighted by yellow, blue and red circles correspond to different functional networks. They are: (b) task related component in which the response well follows the external block-based task paradigm, (c) anti-task related component in which the response well follows the inverse of external block-based task paradigm, and (d) DMN component. In each component (b-d), the corresponding signals (colored curves) accompanied with the task stimulus (white curve) are shown in the top panels. Their spatial distributions are also back-projected onto the volumetric images in the lower panel. Each voxel is color-coded by the reference weight used in the sparse representation.139