Ni Shu

The paper develops population-specific white matter charts for Chinese and Western populations, showing differences in maturation timing and improved prediction accuracy when using population-matched models.

The paper identifies genetic variants associated with brain white matter connectome efficiency and intelligence, showing shared SNPs and improved prediction when combining polygenetic scores with connectome data.

This study examines individual variability in human brain structural connectivity, finding higher variability in limbic regions and lower in sensorimotor areas, and proposes a model to predict cognition and generate individual brain maps.

This study examines how structural and functional brain connectivity develop and relates to cognitive functions and gene expression in humans.

DCP automates diffusion tensor imaging processing on Windows to construct brain structure networks, offering a GUI and integration of existing tools.

This study examines how age affects overlapping functional modular organization in the human brain using resting-state fMRI data from a healthy cohort, finding age-related decreases in overlapping modularity and increases in overlapping nodes.

The paper uses diffusion tensor imaging and machine learning to predict cognitive decline rates in elderly individuals based on white matter network properties.

This study examines structural network maturation in preterm and term-born neonates using diffusion MRI, finding faster increases in hub and rich-club connectivity during the third trimester.