Oualid M. Benkarim

The paper shares a multimodal 7T MRI dataset of ten healthy individuals, providing structural and functional brain data across multiple imaging modalities and parcellation scales.

This study identifies subregional structure-function coupling in the human amygdala using histology and MRI, revealing two axes of microstructural variation linked to functional networks.

This study finds reduced cortex-wide connectivity distance in ASD, indicating shorter average connection length and increased short-range connectivity, particularly in transmodal brain systems.

HippoMaps provides a toolbox and data warehouse for mapping and analyzing hippocampal data across multiple modalities and scales.

This study uses multimodal imaging and connectivity modeling to show that polysynaptic mechanisms are implicated in autism spectrum disorder, with reduced structure-function coupling in transmodal networks.

The paper shares a multimodal MRI dataset for studying multiscale brain organization, including connectomes and gradients from multiple imaging modalities.

Micapipe is an open pipeline for processing multimodal MRI data, generating structural and functional connectomes, geodesic distances, and microstructural profiles across multiple brain parcellations and surface spaces.

This paper predicts brain function from the structural connectome using a Riemannian approach based on diffusion maps and random walks, showing performance plateaus around the third walk.

This study identifies a structure-function substrate of cognitive imbalances in autism using multi-site neuroimaging data and dimensional analysis.

BrainStat provides a toolbox for statistical analysis and feature association in neuroimaging data, integrating multiple modalities and templates to enhance cross-modal research.

This study identifies shared and distinct structural brain differences in children with autism and anxiety, using neuroimaging data from 82 participants.

This study examines structural and functional brain network development in adolescents, finding that structural wiring changes correlate with functional differentiation.

The paper introduces the ENIGMA Toolbox, a Python/Matlab ecosystem for integrating multisite neuroimaging datasets across disorders and contextualizing findings at multiple scales.

This study quantifies how population diversity affects brain-imaging prediction accuracy and pattern stability using two clinical cohorts.

The paper combines connectome analysis and computational models to show autism has altered subcortico-cortical interactions linked to microcircuit and macroscale network anomalies.

This study identifies higher functional network idiosyncrasy in ASD compared to TD, linked to ASD risk genes and symptom severity.

The paper identifies three structural connectivity gradients in the human temporal lobe and links them to microstructural features and macroscale functional measures.

The paper develops a continuous surface model of the mesiotemporal lobe's iso-to-allocortex transition and links it to functional dynamics and cognitive systems.

BrainSpace provides a toolbox for analyzing macroscale gradients in neuroimaging and connectomics data, enabling gradient identification, alignment, visualization, and association studies.

The paper identifies myeloarchitecture gradients in the human insula that correlate with its functional connectivity and diverse roles.