Victor Nozais

This study benchmarks predictive models for long-term stroke outcomes using a global consortium, revealing mechanistic diversity and key predictors across motor, cognitive, and emotional domains.

The paper characterizes lifespan changes in white matter microstructure, macrostructure, and associated cortical morphology using large datasets, finding unique developmental and aging trajectories across brain pathways.

The paper develops a method to map white and grey matter contributions to resting-state networks and finds that 89% of white matter is shared across multiple networks.

This study uses track-weighted dynamic functional connectivity to identify white matter components associated with functional connectivity dynamics and cognitive performance.

The paper introduces Functionnectome, a method that maps functional white matter circuits using fMRI and anatomy, revealing their contribution to motor, working memory, and language functions.

The paper introduces the MRi-Share database, a multi-modal brain MRI dataset of 1,870 young adults, and presents preliminary findings on age and sex associations with brain phenotypes.

This paper develops a deep learning algorithm for 3D segmentation of perivascular spaces in MRI data, achieving high accuracy and demonstrating interoperability across scanners.

The paper develops a deep learning classifier to assign independent components from resting-state fMRI to predefined resting-state networks, achieving 92% accuracy and creating an RSN atlas.