Freesurfer Linear Mixed Effects Model


I am trying to run some longitudinally processed Freesurfer data through the linear mixed effects model (LinearMixedEffectsModels - Free Surfer Wiki). I have followed the univariate tutorial on the website using my own data to create the design matrix, which takes the following form:

Col1 = intercept (all 1’s)
Col2 = time (days from baseline)
Col3 = exposure (1=high exposure, 0=low exposure)
Col4 = time*exposure interaction
Col5 = covariate
Col6 = covariate
Col7 = covariate
Col8 = covariate
Col9 = estimated intracranial volume/mean cortical thickness (covariate)

What I am interested in is any differences in cortical thickness/volume over time between the high and low exposure groups for particular ROIs. I am also interested in seeing if these other covariates (cols 5-9) play a role in the relationship.

I am relatively new to imaging, so I do not have much experience working with design and contrast matrices. The Freesurfer tutorial does a poor job at explaining how to construct the contrast matrix. What would a contrast matrix look like to test the above hypothesis?

Thanks in advance!