Da Zhi

This study shows that individualized parcellation of the human prefrontal cortex reveals sharp functional boundaries not visible in group atlases, suggesting a mosaic of fine-grained subdivisions within large-scale gradients.

The paper models the genetic architecture of cortical expansion using GWAS data and links it to neuropsychiatric disorders.

This paper introduces mRBM-HBP, a Bayesian framework that integrates resting-state and task fMRI to improve cortical parcellation accuracy and individual specificity.

This paper introduces a hierarchical Bayesian framework that fuses task-based and resting-state neuro-imaging datasets to create a population-based atlas of the human cerebellum, achieving better individual parcellations with limited data.

This paper presents a hierarchical functional atlas of the human cerebellum integrating multiple datasets, improving individual precision mapping and enabling analysis at different levels of granularity.

The paper introduces DCBC to evaluate brain parcellations by comparing their ability to predict functional boundaries in fMRI data, finding that anatomical parcellations underperform while resting-state and task-based parcellations perform better.