Pattern recognition of functional brain networks

Abstract

Functional brain network analysis has been a powerful tool for measuring brain function in normal and pathologic states based on resting state fMRI (rsfMRI) data. Recent advances in pattern recognition and sparse modeling have enabled us to characterize subject-specific functional brain networks and derive clinically useful biomarkers. In this paper, we briefly introduce our recent work in the development of functional brain network analytic techniques, including functional brain network modeling, pattern recognition of functional brain networks, as well as modeling heterogeneous patterns of functional connectivity. Finally, we discuss some current challenges that have received and are likely to receive more attention in the near future.