A novel approach for fMRI data analysis based on the combination of sparse approximation and affinity propagation clustering

In the task-related experiments, we can see that SAAPC is more accurate to detect the functional networks than basic APC, and it significantly reduces the time cost relative to basic APC. In addition, in the resting-state data experiments, the SAAPC method can successfully identify typical resting-state networks from the resting-state data set, while this performance is seldom reported by the classical cluster method and the basic APC method. This proposed clustering analysis method is expected to have wide applicability.