Joint representation of connectome-scale structural and functional profiles for identification of consistent cortical landmarks in human brains

There have been significant interests in the representation of structural or functional profiles for establishment of structural/functional correspondences across individuals and populations in the brain mapping field. For example, from the structural perspective, previous studies have identified hundreds of consistent cortical landmarks across human individuals and populations, each of which possess consistent DTI-derived fiber connection patterns. From the functional perspective, a large collection of well-characterized functional brain networks based on sparse coding of whole-brain fMRI signals have been identified. However, due to the considerable variability of structural and functional architectures in human brains, it is challenging for the earlier studies to jointly represent the connectome-scale profiles to establish a common cortical architecture which can comprehensively encode both brain structure and function. In order to address this challenge, in this paper, we proposed an effective computational framework to jointly represent the structural and functional profiles for identification of a set of consistent and common cortical landmarks with both structural and functional correspondences across different human brains based on multimodal DTI and fMRI data. Experiments on the Human Connectome Project (HCP) data demonstrated the promise of our framework.