With the explosion of neuroimaging, differences between male and female brains have been
exhaustively analyzed. Here we synthesize three decades of human MRI and postmortem …

With the advances of data-driven machine learning research, a wide variety of prediction
problems have been tackled. It has become critical to explore how machine learning and …

Mapping the connectome of the human brain using structural or functional connectivity has
become one of the most pervasive paradigms for neuroimaging analysis. Recently, Graph …

Human brains are commonly modeled as networks of Regions of Interest (ROIs) and their
connections for the understanding of brain functions and mental disorders. Recently …

Recent work has begun to relate individual differences in brain functional organization to
human behaviors and cognition, but the best brain state to reveal such relationships remains …

Establishing brain-behavior associations that map brain organization to phenotypic
measures and generalize to novel individuals remains a challenge in neuroimaging …

Graph representations are often used to model structured data at an individual or population
level and have numerous applications in pattern recognition problems. In the field of …

The macro-connectome elucidates the pathways through which brain regions are
structurally connected or functionally coupled to perform a specific cognitive task. It …

Participant motion during functional magnetic resonance image (fMRI) acquisition produces
spurious signal fluctuations that can confound measures of functional connectivity. Without …

While neuroimaging studies typically collapse data from many subjects, brain functional
organization varies between individuals, and characterizing this variability is crucial for …