Commonality analysis for neuroimaging. Code supporting Wu et al, "Cerebral blood flow predicts multiple demand network activity and fluid intelligence across the lifespan".
This voxel-wise GLM-like approach uses MATLAB's fitlm to save nii image of coefficients and p-values for each variable and residuals. This could be useful in instances with voxel-specific covariates. For example, in Tsvetanov et al 2020, we estimated variance explained and residuals in RSFA maps (across subjects) after controlling for regionally-speciffic effects of ASL maps, T1w maps in addition to other systemic effects.
We extended this voxel-wise approach to commonality analysis in Wu et al 2022.
Dependencies can be accessed at my external repo from the subfolders 'spm12' and 'palm'.
The use of other external code in .../code/external/ of this package.