This toolbox accompanies two research papers that utilize spatial profiles (gradients) to map subcortical brain structures using MRI data.
Mapping Microstructural Gradients of the Human Striatum in Normal Aging and Parkinson’s Disease Drori, Berman, and Mezer. Science Advances, 2022
This code automatically computes the principal axes of the striatum (caudate and putamen) and possibly other subcortical structures (e.g., substantia nigra) in MRI images. It uses singular value decomposition (SVD) on ROI voxel coordinates at the individual subject level.
It then calculates spatial functions of MRI intensities (or qMRI values) along these axes, both at the individual and group levels.
It outputs summary results of the image value spatial profiles and the axes information, as well as subject-specific NIfTI files of the resulting axis-based segmentations
Visualization tools are provided for:
- ROI axes
- MRI-derived spatial functions
Example usage: Run the script mrGrad_run.m
Spatial profiles provide sensitive MRI measures of the midbrain micro- and macrostructure Berman, Drori, and Mezer. NeuroImage, 2022
A separate script for applying this method to the midbrain is available in the MidBrainProfiles directory.
Example data for each analysis is included in their respective directories.
mrGrad is a fully self-contained MATLAB-based toolbox.
Required:
Recommended:
boundedline-pkg: A MATLAB toolbox for plotting bounded lines (useful for visualization)