Thanks Doug, though I'm still a bit confused:
I'd like to see the smoothed results on the individuals, not just the
group - so it seems isxconcat-sess wouldn't be appropriate.
Are you suggesting running mri_surf2surf directly on the contrast
sig.nii files? Is smoothing a significance map the equivalent of
smoothing the data, then recreating the significance in the sphere
space? This didn't seem true to me, which is why I tried to recreate
the significance maps as below.
Thanks,
-S
Doug Greve wrote:
Hi Scott, you should skip steps 2-6 (that is the old stream). Instead,
run isxconcat-sess after #1, then smooth on the surface either in
isxconcat-sess or with mri_surf2surf before running mri_glmfit.
doug
Scott Gorlin wrote:
Hi,
I'd like some clarification on the recommended procedure for
smoothing functional data across the cortical surface in FS-FAST.
I've managed to get it working using the following procedure:
1) analyze my data using selxavg3-sess in the native space, without
smoothing
2) resample the averages into the spherical space using func2sph-sess
3) smooth these averages using sphsmooth-sess (which required several
edits to work with .nii files)
4) recreate the contrasts in the smoothed sph space with stxgrinder-sess
5) paint the analysis onto the surface with paint-sess (which also
required edits for .niis)
6) view with surf-sess (which I had to edit to read the subject
properly)
Surely there's a simpler way to accomplish this? I'm particularly
confused because the online documentation says that selxavg3 replaces
stxgrinder, but it seems stxgrinder has to be called to make
contrasts in non-native space (and uses different code to produce the
contrasts than selxavg). Plus, the revision date for stxgrinder is
more recent!
Then, it seems odd that isxconcat will reproject the data for a group
analysis if it's already sampled on the surface via func2sph.
Thanks,
Scott
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