That looks fine. If you are going to use the monte carlo sim, then you'll need an estimate of the FWHM. In mri_glmfit, we get that by running mris_fwhm on the residuals. So, assuming that your analysis has residuals, then you should save those out too.
On 05/24/2016 01:55 PM, Chung, Yoonho wrote:
Hi - If I would like to try to perform mass-univariate statistics at the vertex level (thickness, area, vol at each vertex) without using the mri_glmfit, is this order a sound step (in general) for mapping stats parameter of choice (p-val or t s or weights for example) to the surface?
- Use mris_preproc and surf2surf to get the data to common space and
smooth.
Load the data to matlab using fs_read_Y() or MRIread
Perform stats at each vertex using stats toolbox to apply modeling
approach of your choice (e.g., machine learning, linear mixed model etc.)
- Extract P-values (or other parameters) for each vertex for the
variable of primary interest
Use MRIwrite to create mgh file
Perform multiple comparison using freesurfer functions (e.g.,
FDR or monte carlo sim)
- view corrected maps using tksufer?
Any steps I should consider adding or avoid?
Thank you!
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