For whatever reason this e-mail didn’t make it to me.  Another thing to check 
is whether there is a difference between fslsmoothest and wb_command 
-volume-estimate-fwhm.  It certainly may be that in 2D on the surface the data 
appears smoother than in 3D in the volume, as the surface is oriented in the 
same direction as the areas are.
Peace,

Matt.

From: 
<[email protected]<mailto:[email protected]>>
 on behalf of Timothy Coalson <[email protected]<mailto:[email protected]>>
Date: Monday, June 5, 2017 at 7:45 PM
To: "Ely, Benjamin" <[email protected]<mailto:[email protected]>>
Cc: "[email protected]<mailto:[email protected]>" 
<[email protected]<mailto:[email protected]>>
Subject: Re: [HCP-Users] smoothness of grayordinate data

I thought someone else might answer this, but I'll give it a shot.

For the volume part of the data, there is some smoothing that happens (2mm 
FWHM), originally as part of making the subcortical ROIs of each subject 
conform to the cifti space.  The recent versions of the pipelines use a 
different method now, but it still is set to do similar smoothing by default, 
to reduce differences from the released HCP data.  This smoothing occurs 
separately within each subcortical parcel, and the effects of having an ROI 
edge near a voxel may result in an amplification of the smoothing kernel.

For surface data, I know of two things that are going on.  First, when data is 
mapped from volume to surface, it uses a weighted average between several 
voxels, depending on how the ribbon intersects them, which results in a 
reduction of noise.  Second, the surface data was smoothed by the same distance 
as the subcortical data (2mm FWHM).

The surface FWHM calculation is also fairly naive, in that it assumes all 
vertices have the same spacing, which might cause a bias in it.  We don't use 
this measure much, if at all, so we haven't come up with a method that takes 
this into account.

It may also be the case that the non-noise part of the smoothed fMRI signal has 
less within-neighborhood variation in it than a similarly smoothed pure noise 
image would have, which would also cause the FWHM estimation to be larger than 
the combination of "smoothness" amounts would suggest.

Tim


On Wed, May 31, 2017 at 11:34 PM, Ely, Benjamin 
<[email protected]<mailto:[email protected]>> wrote:
Hi everyone,

I noticed recently that the smoothness of the minimally-preprocessed 
grayordinate-space HCP data is surprisingly high, especially at 3T. For subject 
100610, as an example, wb_command -cifti-estimate-fwhm reports:

rfMRI_REST1_LR_Atlas_MSMAll_hp2000_clean.dtseries.nii
CORTEX_LEFT FWHM: 18.3385
CORTEX_RIGHT FWHM: 16.5479
Voxels FWHM: 7.3608, 7.1032, 6.95473

By contrast, fsl smoothest gives the smoothness of the corresponding volumetric 
fMRI file as:

rfMRI_REST1_LR_hp2000_clean.nii.gz
FWHMx = 1.98571 mm, FWHMy = 1.84018 mm, FWHMz = 1.99221 mm

That seems like a huge jump in smoothness, especially for the subcortical data, 
which is represented in essentially the same voxel space.

The difference is smaller for the 7T data, but still pronounced:

rfMRI_REST1_7T_PA_Atlas_1.6mm_MSMAll_hp2000_clean.dtseries.nii
CORTEX_LEFT FWHM: 7.04818
CORTEX_RIGHT FWHM: 6.99358
Voxels FWHM: 4.63357, 4.54396, 4.23441

rfMRI_REST1_7T_PA_hp2000_clean.nii.gz
FWHMx = 1.7863 mm, FWHMy = 1.74615 mm, FWHMz = 1.66513 mm

Do these results seem correct and if so, why are the grayordinate-space data 
(including the subcortical voxels) so much smoother?

Many thanks,
-Ely

Example of full workbench command, from subject directory:
wb_command -cifti-estimate-fwhm \
MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR_Atlas_MSMAll_hp2000_clean.dtseries.nii
 \
-merged-volume -column 1 \
-surface CORTEX_LEFT 
MNINonLinear/fsaverage_LR32k/100610.L.midthickness_MSMAll.32k_fs_LR.surf.gii \
-surface CORTEX_RIGHT 
MNINonLinear/fsaverage_LR32k/100610.R.midthickness_MSMAll.32k_fs_LR.surf.gii

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