Huili Sun

This study uses connectome-based predictive modeling to predict chronological age from structural and functional brain connectivity across different lifespan stages and finds that both modalities contribute complementary age-related information.

This study uses network control theory and developmental MRI to show how brain structural maturation supports cognitive development, finding decreasing control energy for most cognitive tasks and varying optimal efficiency ages across cognitive functions.

The paper uses network control theory to show fetal brain controllability follows a U-shaped trajectory during pregnancy, co-developing with synaptic functions and synchronizing with maternal controllability changes.

The paper examines functional connectivity in the social perception pathway in neonates and links it to social attention at 4 months, finding stronger connectivity in the right pathway associated with better social functioning.

The paper shows that overlooked brain connectivity features can yield different neurobiological interpretations with similar prediction accuracy in neuroimaging studies.

The paper uses white-matter controllability at birth to predict social engagement and language outcomes in toddlers.

This study predicts brain age and deviations from normative trajectories in neonatal connectomes using structural and functional data from infants.

The paper evaluates the statistical power of external validation in brain-phenotype predictions and finds that sample size impacts power and effect size inflation.

CAROT remaps connectomes between atlases without raw data, enabling reuse of processed data across different atlases.