Yuanzhe Liu

PaSTA provides a fast and reliable method to assess the statistical significance of spatial associations between brain maps, improving false positive control and power in heterogeneous data.

The paper introduces a deep learning model to generate individual connectomes from personal attributes and shows it can accurately replicate empirical connectomes from the UK Biobank.

This paper introduces a generative model of the connectome that simulates dynamic axon growth, producing brain-like network structures and revealing how axonal guidance principles shape macroscopic connectomes.