Hi,

I understand how to use randomise, cluster and fsl_glm to perform a mass-univariate regression of a vertex-varying response variable against a global predictor, followed by, e.g., cluster-extend based thresholding to identify a FEWR-significant cluster. I believe the canonical example of this kind of analysis would be correlation of cortical thickness with age.

Is it possible in FSL to have a predictor that varies across vertices, and do a correlation analysis of, e.g. cortical thickness against cortical curvature? I presume that this would necessitate specifying a vertex-dependent design matrix in the GLM.

Thanks,

Eckhard