Jacques‐Donald Tournier

This study examines how thalamocortical innervation timing and spatial distribution influence cortical network formation during gestation, finding that hubs emerge from spatiotemporal constraints rather than preferential targeting.

TRAMFIX evaluates the reproducibility of fixel-based analysis across multiple MRI scanners and finds high reliability for whole-brain and tract-level metrics, with some variability at the fixel level.

This study uses in vivo tractography to examine neonatal white matter pathways related to hypothalamic and reward functions, linking early-life factors to later neurodevelopmental and obesity outcomes.

This study links ASD common genetic variants to regional brain volume differences in newborns, finding positive associations with frontal and fronto-temporal volumes and negative associations with parietal and parieto-occipital volumes.

The paper examines microstructural changes in fetal brain compartments before cortical folding begins, finding that anisotropy decreases in subplate and cortical plate regions prior to sulcal pit formation.

This study uses diffusion MRI to track thalamocortical pathway maturation in human fetal brains, identifying key neurobiological changes in the second to third trimester.

The paper identifies a stable structural connectome fingerprint in preterm neonates that can distinguish individuals more effectively than functional connectomes.

This paper uses machine learning to predict neonatal brain age and clinical risk from structural connectomes, finding thalamocortical connections are key predictors of developmental outcomes.

dStripe corrects slice artefacts in diffusion MRI using a constrained neural network to reduce interslice inconsistencies without biasing data.

This study examines how preterm birth affects cortical development in infants at term-equivalent age using MRI, finding altered microstructure and morphology with individual variability.

This paper develops a multi-channel 4D atlas of neonatal brain development combining structural and diffusion MRI data, showing microstructural differences between term and preterm infants.

The paper optimizes multi-shell diffusion MRI acquisition parameters using a data-driven approach, resulting in a specific protocol for neonatal imaging.

This paper introduces a method for fetal diffusion MRI reconstruction with intensity correction, enabling detailed analysis of brain connectivity and microstructure in-utero.

MRtrix3 provides an open-source C++11 and Python software framework, command-line suite, and OpenGL 3.3 viewer for fast multi-dimensional medical image processing and diffusion MRI analysis.

This paper develops a machine learning framework to identify sparse grey matter biomarkers in Schizophrenia and their biological substrates using structural MRI data.

The paper examines how brain network properties at birth predict language skills and shows that syntactic abilities are affected by preterm birth.

The paper introduces a fully automated pipeline for neonatal cortical surface reconstruction from MRI, achieving high accuracy in 85% of cases.