Kimberly R. Pechman

This study identifies genetic loci and pathways associated with limbic white matter microstructure in aging and Alzheimer's Disease using multi-cohort diffusion MRI and bulk RNA-seq data.

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.

MidRISH harmonizes diffusion imaging data by projecting sites to a mid-space, reducing reference bias compared to LinearRISH.

The paper examines how sex, race, and APOE-ε4 allele status affect white matter microstructure across multiple aging and Alzheimer's disease cohorts.

The paper develops a variational autoencoder to harmonize multi-site diffusion MRI connectomes by isolating site-invariant features and preserving age-related modularity correlations.

This paper uses deep learning to predict brain age from MRI data and finds it correlates with cognitive impairment and decline.

This study analyzes diffusion MRI data from 1184 participants to quantify age-related changes in white matter microstructure and macrostructure, finding that macrostructural features show more heterogeneous age-related decline.

The paper investigates how free-water metrics in medial temporal lobe white matter tracts relate to cognitive decline, finding they add unique predictive value beyond hippocampal volume.