Right. FSFAST uses "three spaces": lh (surface), rh (surface), and subcortical (volume). To prevent voxels from being counted twice, we mask cortical voxels out of the volume-based analysis.

On 2/5/16 11:29 AM, Rodriguez-Thompson, Anais wrote:

Hi FreeSurfer experts,

I'm writing to follow up on an email I sent on Monday.

I'm working in 5.3 and switching over to running my 1st level analysis in fsaverage. I noticed that when visualizing the volume output from the mni305 analysis in tkmedit, there is only activation in subcortical regions and none in cortical regions.

I read in the FreeSurfer release notes for 5.1 that fsfast "now masks the volume-based analysis to include only subcortical areas."

I just wanted to confirm that we are not seeing cortical activation in the volume due to it being masked out.

Again, my commands are:

...

Pre-processing: preproc-sess -s GDDA001 -surface fsaverage lhrh -mni305 -fwhm 5 -per-run -d $SUBJECTS_DIR -fsd bold -so siemens Mkanalysis: mkanalysis-sess -analysis SIRP_LoadRegression_Stable5.3_012616_sm5_mni305 -mni305 2 -fwhm 5 -paradigm slopepar -event-related -fsd bold -runlistfile runlistfile -tpef tpef_1.5mm.txt -timewindow 20 -TER 2 -nconditions 9 -gammafit 2.25 1.25 -refeventdur 2 -per-run -TR 2 -stc siemens -force

Thanks, Anais

On Feb 1, 2016, at 12:40 PM, Rodriguez-Thompson, Anais <ARODRIGUEZ-THOMPSON@mgh.harvard.edu mailto:ARODRIGUEZ-THOMPSON@mgh.harvard.edu> wrote:

...

Hi FreeSurfer experts,

I'm in the process of switching over our first-level analyses from being run in native space to being run in fsaverage/mni305 space. Looking at the first-levels on an individual subject level, the volume analyses look fairly different (cortical signal especially is lost in the mni305 analysis). I've attached a couple of slides with images comparing the two volume analyses.

My commands for the mni305 analysis are...

Pre-processing: preproc-sess -s GDDA001 -surface fsaverage lhrh -mni305 -fwhm 5 -per-run -d $SUBJECTS_DIR -fsd bold -so siemens Mkanalysis: mkanalysis-sess -analysis SIRP_LoadRegression_Stable5.3_012616_sm5_mni305 -mni305 2 -fwhm 5 -paradigm slopepar -event-related -fsd bold -runlistfile runlistfile -tpef tpef_1.5mm.txt -timewindow 20 -TER 2 -nconditions 9 -gammafit 2.25 1.25 -refeventdur 2 -per-run -TR 2 -stc siemens -force Mkcontrast: mkcontrast-sess -analysis SIRP_LoadRegression_Stable5.3_012616_sm5_mni305 -contrast 2vFix -a 2 -c 0

My commands for the native space analysis are...

Preprocessing: preproc-sess -s GDDA001 -fwhm 5 -per-run -d $SUBJECTS_DIR -fsd bold Mkanalysis: mkanalysis-sess -analysis SIRP_LoadRegression_Stable5_050514 -TR 2 -paradigm slopepar -event-related -runlistfile runlistfile -tpef tpef_1.5mm.txt -native -fwhm 5 -timewindow 20 -TER 2 -nconditions 9 -gammafit 2.25 1.25 -refeventdur 2 Mkcontrast: mkcontrast-sess -analysis SIRP_LoadRegression_Stable5_050514 -contrast 2vFix -a 2 -c 0

I have a couple of questions regarding the differences between the two analyses. First, why is so much of the signal robustness from the native space volume analysis lost in the mni305 analysis? Second, why are the voxel sizes so different between the two analyses (with the native space analysis having a much larger voxel size)?

Thanks, Anais <Volume_analysis_discrepancies.pdf> _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu mailto:Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

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