Sorry, not sure what you are trying to do. From your equation it looks like you are not doing a voxel-wise analysis but instead using maps to try to predict cognition? If so, this is a multivariate analysis whereas mri_glmfit does voxel-wise analysis. We don't really have any tools to do multivariate analysis.

On 3/3/2020 7:05 PM, Adam Martersteck wrote:

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Hi FreeSurfer team,

I have a question about running mri_glmfit with 2 different surface modalities as the independent variable and a single value per participant as the dependent variable. I'm trying to examine the unique and shared contribution of the 2 surfaces to predict a cognitive measure. E.g. Cognition ~ ?h.thickness + ?h.PET

I tried mri_glmfit with the "--table" option, giving it a column of scores per participant (in the aseg2stats table format), and then using "--pvr lh.thickness-stack.fsaverage.mgh" and a second "--pvr lh.PET-stack.fsaverage.mgh", using contrasts matrices as [0 0 1], [0 1 0], and [0 1 1].

_When I run mri_glmfit it returns:_ ERROR: mri_reshape: number of elements cannot change   nv1 = 163842, nv1 = 1

It continues to run, but all surface maps are full of zeroes. Any suggestions? Is there a better way to do this?

Thanks, Adam

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