Connectomics

The MINDS lab conducts state-of-the-art research to help us better measure and understand human functional connectivity. The human brain is a complex network, consisting of functionally interconnected regions whose coordinated effort gives rise to different functions. Understanding what these regions are, how they interact, and how this interaction forms a wide range of behavior has long been an essential question for human neuroscience. The MINDS lab is addressing these questions with data generated by functional magnetic resonance imaging (fMRI) technology. However, fMRI data are not only massive in size but also spatially and temporally complex. The lab’s research aims at developing novel statistical and machine learning methods for functional connectivity to meet challenges arising with the “big” neuroscience data. To achieve that goal, some of the lab’s top research directions include connectome-based predictive modeling to study brain function and its link to behavior, high-dimensional connectome imputation, multi-modality manifold learning, and broader-level statistical inference to improve power and reliability.