Sophia Vinci‐Booher

The paper generates lifespan normative charts for cervical spinal cord morphometry using MRI data, revealing non-linear changes and sex differences across ages 0-100.

This study tracks brain development and learning in first graders, finding that white matter changes predict math learning but not reading.

This study characterizes white matter asymmetry across the lifespan using a large dataset, revealing dynamic changes in asymmetry patterns with age.

The paper develops normative reference charts for white matter microstructure and macrostructure across the lifespan using diffusion MRI data from 50 studies.

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.

The paper uses diffusion tractography and machine learning to show that specific white matter tracts predict individual differences in sensorimotor learning outcomes.

This study examines how hippocampal subfield microstructure develops and relates to two types of inference tasks in humans.

This paper introduces a 1D-CNN denoising method for DWI data that improves image quality and microstructural measurements by learning from low-noise datasets.

The paper examines the development of the posterior vertical pathway (PVP) white matter tracts and finds they are more adult-like than dorsal stream tracts but less than ventral stream tracts, and are linked to perceptual task performance in children.