Simultaneous modeling of the spatio-temporal variation patterns of brain functional network from 4D fMRI data has been an important yet challenging problem for the field of cognitive neuroscience and medical image analysis.
In recent years, analyzing task-based fMRI (tfMRI) data has become an essential tool for understanding brain function and networks.
Part model-based methods have been successfully applied to object detection and scene classification and have achieved state-of-the-art results.
It is believed that eye movements in free-viewing of natural scenes are directed by both bottom-up visual saliency and top-down visual factors.
Our strategy is to formulate the individual ROI optimization as a group variance minimization problem, in which group-wise functional and structural connectivity patterns, and anatomic profiles are defined as optimization constraints.