Hi Shengwei,

I'm not sure if I understand. The images we model in randomise are all scalars. Do you mean something that is constant across space and/or constant across multiple subjects? If yes, randomise can still be used. FWE results are valid, and if all voxels across space are identical, it will give the same result as the uncorrected (and both are fine then).

The spatial statistics (cluster extent, cluster mass and TFCE) are, however, only meaningful for actual imaging data. If these quantities that you define as scalars aren't truly imaging data (i.e., not voxelwise), and were stored as NIFTI just for some convenience, these statistics aren't meaningful.

Not sure if it helps. Maybe if you give more details.

All the best,

Anderson



On 31 July 2014 17:14, Shengwei Zhang <[log in to unmask]> wrote:
Hi FSL experts,

I have a question about the input for randomise. I'm interested in modelling a scalar quantity as a function of voxel-dependent EV plus other EVs, and using randomise for the analyses.

Can I just fill that scalar quantity in the brain mask for each participant and use it as input for randomise? Will it affect the way that randomise is supposed to work to correct FWE or TFCE?

Any help is appreciated.

Shengwei