Lianrui Zuo

The paper evaluates the variability of GAMLSS-based brain charts using analytic and empirical methods, finding low coefficient of variation across most white matter features.

This paper introduces BrainVAE, a transformer-based variational autoencoder, to classify preclinical Alzheimer's disease using white matter BOLD signals and finds it outperforms other models when combining white and gray matter data.