Dear FreeSurfer experts,

We have run a vertex-wise analysis regressing a continuous variable onto cortical thickness on the surface, and would like to verify that our contrast that uses Age and Sex as covariates was defined correctly, especially since there is probably more than one way to control for a binary variable like Sex.

On the website (https://surfer.nmr.mgh.harvard.edu/fswiki/DodsDoss) it suggests to make two regressors, one for Males, and one for Females, where for the former a 1 is indicative of the Male category, and a 1 on the latter is indicative of the Female category. However, using that FSGD file and running a DOSS contrast as [0 1 0 0 0], we get the error: matrix is ill-condition or badly scaled, condno=2.01889e+07.

We believe this may be due to the fact that Male and Female categories are autocorrelated and Freesurfer likes variables to be de-meaned. Running a FSGD file with only Age and our variable of interest via a DOSS contrast of [0 1 0] works without any errors.

We thus created an FSGD file where we have Sex as our third variable (in addition to our continuous variable of interest and one demeaned continuous covariate), coding 1s for Males and 0s for Females, and we used a DOSS contrast of [0 1 0 0]. This provided us with a map that makes sense with our expectations.

We would like to verify if this is doing what we believe it is doing; that is, looking at the relationship of our continuous variable or interest after accounting for age and sex.

Any thoughts would be greatly appreciated.

Thank you so much.

Best,

Fred