Jean M. Vettel

This study evaluates six compressed sensing diffusion spectrum imaging (CS-DSI) schemes, finding they provide accurate and reliable white matter structure measures with up to 80% reduced scan time compared to full DSI.

The paper assesses reproducibility and variability in multi-modal, longitudinal brain networks across different modalities and tasks, finding structural networks more reliable than functional ones for individual identification.

QSIPrep is a software platform for preprocessing diffusion MRI data that supports multiple sampling schemes and ensures reproducibility through standardized workflows and quality measures.

The paper examines how brain connectivity and social network structure influence response inhibition in adolescents, finding that social brain systems compensate for weaker response inhibition systems and that social context strengthens this relationship.

The paper uses TMS-EEG and dynamic community detection to analyze how brain network reconfigurations differ in alpha and beta frequency bands following stimulation.

The paper creates a population-averaged atlas of the human structural connectome using diffusion MRI data, revealing network topology features like small-worldness and hub structures.

This paper applies community detection algorithms to brain graphs derived from neuroimaging data to uncover patterns of coordinated neural activity and their implications for brain function.

The paper uses diffusion MRI to analyze white matter architecture and shows it can predict social, health, and cognitive attributes across individuals.

The paper investigates how social exclusion affects brain connectivity in adolescents and links these changes to the density of their friendship networks.