Andrew Kalnin

The paper evaluates factors affecting brain-age prediction models using structural neuroimaging data from 35,683 individuals, finding optimal model performance with no site harmonization, age-binning, and a sample size of over 1,600.

The paper benchmarks and optimizes a normative modeling framework for brain morphometry across the lifespan using MFPR, showing excellent accuracy and stability.

The paper examines age-related variations in cortical thickness across different life stages using gene expression data from a large neuroimaging dataset.

The paper analyzes sex differences in brain structure variability across the lifespan using a large dataset, finding greater male variability in subcortical volumes, cortical surface area, and thickness in most regions.

This study analyzes subcortical volume changes across the lifespan using MRI data from 18,605 individuals, finding age-related declines in some structures and increases in others.