Hello, 
I'm starting an image-based meta-analysis with SDM on surface-based morphometry (SBM) data. Specifically I'm investigating the Freesurfer local gyrification index (lGI) and mean curvature index (MCI) in patients with schizophrenia (SZ) compared to controls. 

- As you mentioned in 2 recently published meta-analyses of SBM data (Gharehgazlou et al., 2020 and Li et al., 2019), I created with freesurfer/fsl a new grey matter mask excluding subcortical voxels. The resulting mask seems thinner than the one displayed in Li et al., 2019... could you help us to understand this difference?

All the authors I contacted analysed gyrification for each hemisphere and provided me with separate freesurfer z-maps/t-maps for the left and right hemispheres.
- I guess I should merge the left and right statistical maps to include them in the analysis ? If yes, do you know if the fslmaths -add function is an appropriate way to do so?

- These are surface statistical maps so I guess I should convert them to volumes (because the only grey-matter template I can select with SDM is the VBM gray-matter template)?
If yes, do you know if the procedure I used to create the new mask (using the freesurfer mri_surf2vol function and performing an affine-transfomration from Freesurfer space to MNI with the appropriate matrix) correct here?

Thank you so much, 
Layla