Hi, so I'm still trying to work my way through surface-based analysis for the first time, and I'm now running into an error using SurfSmooth:
Notice SUMA_estimate_FWHM_1dif (SUMA_GeomComp.c:6564):
Distribution of data is possibly random noise (p=0.154304)
Expect fwhm to be no different from 0
FWHM values up to 0.56(segments) or 0.48(mm)
are likely meaningless (at p=0.01) on this mesh.
-- Error SUMA_Chung_Smooth_07_toFWHM_dset (SUMA_GeomComp.c:5743):
Failed to get mean fwhm
-- Error SurfSmooth (SUMA_SurfSmooth.c:2116):
Failed to blur master data dset
What I'm trying to do, in words, is to recreate a standard volume-based group analysis, but now on the surface. Since I'm totally new to surfaces, below I list exactly my processing stream, with completely specified commands that I've modeled from examples in SUMA documents, help files, or Message Board postings. I would be very grateful if you could tell me not only where I've gone wrong with the surface smoothing, but any other errors or inefficiencies you might see (eg, do I have to do everything twice, once for each hemisphere, or can I combine them at some point?)
For every subject:
####Use FreeSurfer to create surface (using all default settings)
(not shown)
####Make spec file
@SUMA_Make_Spec_FS -sid MYSUBJ1
####Align the surface to my aligned anatomical
@SUMA_AlignToExperiment -exp_anat MPRAGEanat_Nudged+orig -surf_anat surf/SUMA/MYSUBJ1_SurfVol+orig
####Process (tshifted and volreged) EPI data by hemisphere
For each hemi in lh rh
####Create standard mesh
MapIcosahedron -spec MYSUBJ1_${hemi}.spec -ld 141
####Map the brain mask (made by 3dAutomask on EPI data) to that mesh
3dVol2Surf -spec std.MYSUBJ1_${hemi}.spec -surf_A std.${hemi}.smoothwm.asc \
-surf_B std.${hemi}.pial.asc -sv MYSUBJ1_SurfVol_Alnd_Exp+orig \
-grid_parent mask+orig \
-map_func ave -f_steps 10 -f_index nodes -out_niml v2s_std.${hemi}.mask.niml.dset
####Process EPI data by hemisphere and run
For each run X
####Map the EPI run timeseries to the standard mesh
3dVol2Surf -spec std.MYSUBJ1_${hemi}.spec -surf_A std.${hemi}.smoothwm.asc \
-surf_B std.${hemi}.pial.asc -sv MYSUBJ1_SurfVol_Alnd_Exp+orig \
-grid_parent EPI_RUNX+orig \
-map_func ave -f_steps 10 -f_index nodes -out_niml v2s_std.${hemi}.EPI_RUNX.niml.dset
####Smooth the surface time series
SurfSmooth \
-met HEAT_07 \
-spec std.MYSUBJ1_${hemi}.spec \
-surf_A std.${hemi}.smoothwm.asc \
-surf_B std.${hemi}.pial.asc \
-input v2s_std.${hemi}.EPI_RUNX.niml.dset \
-blurmaster v2s_std.${hemi}.EPI_RUNX.niml.dset \
-detpoly_master 3 \
-output v2s_std.${hemi}.EPI_RUNX.BL.niml.dset \
-target_fwhm 4 \
-bmall \
-cmask "-a v2s_std.${hemi}.EPI_RUNX.niml.dset -expr bool(a)"
####Normalize
3dTstat -prefix v2s_std.${hemi}.EPI_RUNX_MEAN.BL.niml.dset v2s_std.${hemi}.EPI_RUNX.BL.niml.dset
3dcalc -fscale -a v2s_std.EPI_RUNX.BL.niml.dset -b v2s_std.${hemi}.EPI_RUNX_MEAN.BL.niml.dset -expr 'step(b)*min(200,a/b*100)' -prefix v2s_std.${hemi}.Norm_EPI_RUNX.BL.niml.dset`
End
####Concatenate runs
3dTcat -prefix v2s_std.${hemi}.Norm_EPI_allruns.BL.niml.dset v2s_std.${hemi}.Norm_EPI_RUNX.BL.niml.dset v2s_std.${hemi}.Norm_EPI_RUNY.BL.niml.dset v2s_std.${hemi}.Norm_EPI_RUNZ.BL.niml.dset ...
####Run 3dDeconvolve (no polort because detrending took place in smoothing???)
3dDeconvolve -basis_normall 1 -input v2s_std.${hemi}.Norm_EPI_allruns.BL.niml.dset -mask v2s_std.${hemi}.mask.niml.dset -concat startpoints.1D -num_stimts 26 \
[-stims....blah blah blah] \
-tout -bucket deconallruns_stdsurf_${hemi}
End
(Repeat for all subjects)
####This is when I would normally bucket out beta weights, run anovas across subjects, and compute a cluster size threshold, but I haven't gotten there yet for surfaces
Thanks,
Chris
