Julien Cohen‐Adad

The paper identifies an interferon-responsive oligodendroglial state in aging white matter using killifish models, linking it to potential neurodegenerative disease mechanisms.

This study characterizes the human uncinate fasciculus using multimodal approaches, finding no group differences in histology but identifying differentially expressed genes and age-related changes.

The paper develops and validates a novel sf-CARS system with AxonDeepSeg to analyze UF ultrastructure in human postmortem brain tissue, finding mean axon diameter and myelin thickness.

This study benchmarks four cervical spinal cord RF coils at 7 T MRI across multiple centers, identifying performance differences and proposing a standardized evaluation protocol.

The paper introduces EPISeg, a deep learning model for automated spinal cord segmentation on gradient-echo EPI data, showing improved performance over existing methods.

This study shows body size parameters significantly correlate with brain and spinal cord MRI metrics and should be included in neuroimaging studies.

The paper uses multimodal imaging to assess spinal cord oxygenation and vascular changes in a PD mouse model, finding reduced oxygen saturation but no vascular impairment or atrophy.

This study evaluates the impact of distortion correction and cardiac triggering on spinal cord diffusion MRI quality, finding that distortion correction has limited effectiveness and cardiac triggering can be omitted without significant quality loss.

This paper evaluates AxonDeepSeg's performance in automated axon histomorphometry on light micrographs of rat peripheral nerves, finding it robust and faster than manual analysis.

The study finds reduced axon caliber in the associative striatum of Sapap3-KO mice, affecting signal conduction but not the sensorimotor striatum.

The paper introduces an R1-weighted connectome to complement traditional connectomes by incorporating myelin-sensitive MRI data, revealing differences in modular organization and functional gradients.

This study meta-analyzes MRI biomarkers of myelin to compare their correlation with histology, finding MT and relaxometry-based measures have the highest correlations.

This paper introduces a unified signal readout approach for multi-parametric spinal cord MRI, combined with MP-PCA denoising, improving the quality and consistency of microstructural metrics.

This study maps axon morphometry in the human spinal cord using a deep learning framework, revealing structural differences and symmetry, and provides a public template for MRI studies.