Mingyang Li

This study uses in utero MRI and computational models to show that radial glial fibers influence fetal cortical folding through biomechanical modulation.

This paper introduces STREAM, a deep learning framework for analyzing task-fMRI data, revealing directional information flow and reconfiguration in brain networks during visual processing.

This study maps gene expression patterns to cortical folding features in fetal brains, identifying molecular mechanisms and linking them to autism risk genes.

This study identifies distinct neural and molecular correlates of fluid and crystallized intelligence in adolescents using neuroimaging and transcriptomic data from the ABCD cohort.

This study identifies key MRI acquisition factors affecting fetal brain morphology and shows that ComBat-GAM harmonization effectively reduces site effects while preserving developmental patterns.

The paper creates multi-resolution parcellations of the neonatal cerebral cortex using multi-modal MRI data, showing stability and reproducibility across features.

This study shows that postnatal experience selectively shapes structural and functional development of the visual cortex in human neonates, but not cortical myelination or overall functional circuits.