Marc Joliot

The paper investigates SC-FC coupling in healthy adults to identify markers distinguishing typical, atypical, and non-lateralised language lateralisation profiles.

The paper examines how resting-state network connectivity relates to cognition and affect, finding that cognitive patterns reflect a segregated network architecture while affective patterns show less consistent signatures.

The paper investigates resting-state connectivity patterns in adolescents with trait anxiety, finding reduced connectivity in networks related to self-referential processing and rumination.

The paper creates a reference atlas of functional brain networks for typically developing adolescents using resting-state fMRI data and identifies age-related changes and sex effects.

The paper uses imaging genetics to analyze functional connectivity in language networks, identifying genetic loci linked to language abilities, dyslexia, and handedness.

The paper constructs a lateralized brain atlas for visuospatial attention, identifying key networks and hubs, and provides insights for future research on hemispheric specialization.

The paper introduces a deep learning tool, SHIVA-WMH, for detecting white matter hyperintensities across different WMH severities and demonstrates its superior performance compared to existing methods.

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 paper investigates how drowsiness affects functional connectivity in resting-state fMRI and finds that correction methods can reduce its impact, but no single method is optimal.

The paper examines brain activity during perception of prehistoric engravings versus natural patterns, finding differences in expert and non-expert participants.

The paper associates left-handedness with structural brain asymmetries in specific cortical regions using data from 31,864 individuals and identifies genetic links to these asymmetries.

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 identifies 21 genetic loci associated with brain asymmetry using UK Biobank data and links them to microtubule-related genes and psychiatric traits.

The paper analyzes brain asymmetry in three population datasets, finding associations with handedness, cognitive functions, and a genetic correlation with Autism Spectrum Disorder.

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.

The paper shows that individuals with atypical rightward language lateralization use a different brain organization compared to typical leftward lateralized individuals, characterized by strong interhemispheric connectivity and larger corpus callosum volume.

The paper constructs a brain functional atlas for late adulthood, showing spatial differences from younger adult atlases and providing a publicly available resource.

The paper identifies genes correlated with the sentence-processing network in the human cortex using gene expression, fMRI, and neuroimaging meta-analysis.

The paper uses fMRI to show that early human engravings activate brain regions similar to those for objects and written words, suggesting they had a representational purpose.

The paper identifies common multimodal brain networks for listening, production, and reading word-lists using fMRI in right-handers, revealing hemispheric specialization and connectivity patterns.

The paper creates an atlas of 32 sentence-related brain areas using task-induced activation and resting-state connectivity analysis in healthy right-handers.

The paper constructs a population-based atlas of the human pyramidal tract using diffusion MRI and a new tractography algorithm, showing improved resolution of cortico-lateral projections.