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Integrating FreeSurfer and FSL FEAT

Integrating FreeSurfer and FSL FEAT. Outline. Registering FEAT  FreeSurfer Anatomical Automatic (FLIRT) Manual (tkregister2) Surface-based Group fMRI Analysis Individual Analysis Viewing FEAT output on Anatomical Sampling FEAT output on the surface

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Integrating FreeSurfer and FSL FEAT

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  1. Integrating FreeSurfer and FSL FEAT

  2. Outline • Registering FEAT  FreeSurfer Anatomical • Automatic (FLIRT) • Manual (tkregister2) • Surface-based Group fMRI Analysis • Individual Analysis • Viewing FEAT output on Anatomical • Sampling FEAT output on the surface • Mapping FreeSurfer Segmentations to FEAT

  3. Registration Template Functional FreeSurfer Anatomical (orig) Note: Registering the template functional volume to the anatomical volume is sufficient to register the template to the surface.

  4. FreeSurfer Registration • Your Data/Software • fMRI (FSL, etc) • EEG/MEG • DTI • … • FreeSurfer • Subject-Specific • Volumes • Surfaces • Thickness • ROIs Registration • Registration Matrix • Affine 4x4 • As many as 12 DOF (usually 6) • Text file

  5. Automatic Registration First: analyze your data with FEAT reg-feat2anat –featdir fbert1.feat –subject bert Uses BBR to perform 6DOF registration: fbert1.feat/example_func.nii.gz $SUBJECTS_DIR/bert/mri/brainmask.mgz Creates FreeSurfer registration matrix: fbert1.feat/reg/freesurfer/anat2exf.register.dat Also creates: fbert1.feat/reg/freesurfer/anat2std.register.dat This matrix maps standard space to anatomical space and can be used when combining data within subject across data sets reg-feat2anat --help

  6. Manual Registration • reg-feat2anat –feat fbert.feat --manual • Visually inspect registration • Manually edit registration (6 DOF) • Cf Manual Talairach registration tkregister2 --help

  7. Tips • Rigid = 6 DOF = No stretching • Use CSF to get a sense of where the folds are • Avoid using B0 distortion regions • Avoid using ventricles • Warning about “edge” of the brain • Same Subject, Left-Right Flips

  8. Sampling on the Surface Pial White/Gray • White/Gray • Pial • Half Way • Average Projection Fraction --projfrac 0.5

  9. Sampling on the Surface

  10. Surface-based fMRI Group Analysis

  11. Surface-based fMRI Group Analysis R1 R2 R3 S1 S2 S3 } Functional COPEs fsaverage Subject 1 Can be compared Voxel-for-voxel Subject 2 Subject 3 mris_preproc … reg-feat2anat recon-all

  12. Surface-based fMRI Group Analysis (One Run) • Single Run • Analyze with FEAT, No smoothing • COPEs are in native functional space Subject1 run1.feat stats cope1.nii

  13. Surface-based fMRI Group Analysis (One Run) • run reg-feat2anat Subject1 run1.feat reg stats freesurfer cope1.nii reg-feat2anat anat2exf.register.dat – anatomical–example_func registration

  14. Surface-based Group fMRI Analysis (One Run) mris_preproc --out lh.cope1.nii.gz --target fsaverage --hemi lh --iv bert.feat/stats/cope1.nii.gz bert.feat/reg/freesurfer/anat2exf.register.dat --iv greg.feat/stats/cope1.nii.gz greg.feat/reg/freesurfer/anat2exf.register.dat --iv sally.feat/stats/cope1.nii.gz sally.feat/reg/freesurfer/anat2exf.register.dat --iv pat.feat/stats/cope1.nii.gz pat.feat/reg/freesurfer/anat2exf.register.dat Volumes Registrations • lh.cope1.mgh – stack of subjects • Can map any functional data, eg, zstat, fzstat, cope, pe, etc • fsaverage – defines common space (spherical surface) • Group analysis same as with a thickness study: • surface smoothing, mri_glmfit, mri_glmfi-sim

  15. Surface-based fMRI Group Analysis (>1 Run) • Multiple Runs • Analyze each run with FEAT, No smoothing • COPEs are in native functional space Subject1 run1.feat run2.feat stats stats cope1.nii cope1.nii

  16. Surface-based fMRI Group Analysis (>1 Run) • Merge runs with GFEAT with Fixed Effects • GFEAT results are in MNI152 Standard Space Subject1 MNI152 run1.feat run2.feat xrun.gfeat cope1.feat stats stats mean_func.nii stats cope1.nii cope1.nii cope1.nii

  17. Surface-based fMRI Group Analysis (>1 Run) • run reg-feat2anat on one run • anat2std.register.dat – same across all runs Subject1 MNI152 run1.feat run2.feat xrun.gfeat cope1.feat stats reg mean_func.nii stats cope1.nii freesurfer cope1.nii reg-feat2anat anat2exf.register.dat – anatomical–example_func registration anat2std.register.dat -- anatomical–standard MNI152 space registration

  18. Surface-based fMRI Group Analysis (>1 Run) Verify the registration tkregister2 –mov xrun.gfeat/cope1/mean_func.nii.gz --reg run1.feat/reg/freesurfer/anat2std.register.dat --surf Subject1 MNI152 run1.feat run2.feat xrun.gfeat cope1.feat stats reg mean_func.nii stats cope1.nii freesurfer cope1.nii reg-feat2anat anat2exf.register.dat – anatomical–example_func registration anat2std.register.dat -- anatomical–standard MNI152 space registration

  19. Surface-based fMRI Group Analysis (>1 Run) mris_preproc --out lh.cope1.mgh --target fsaverage --hemi lh --iv bert.gfeat/cope1.feat/stats/cope1.nii.gz bert.feat/reg/freesurfer/anat2std.register.dat --iv greg.gfeat/cope1.feat/stats/cope1.nii.gz greg.feat/reg/freesurfer/anat2std.register.dat --iv sally.feat/cope1.feat/stats/cope1.nii.gz sally.feat/reg/freesurfer/anat2std.register.dat --iv pat.feat/cope1.feat/stats/cope1.nii.gz pat.feat/reg/freesurfer/anat2std.register.dat Volumes Registrations • lh.cope1.mgh – stack of subjects • Can map any functional data, eg, zstat, fzstat, cope, pe, etc • fsaverage – defines common space (spherical surface) • Group analysis same as with a thickness study: • surface smoothing, mri_glmfit, mri_glmfi-sim

  20. Surface-based fMRI Group Analysis Left Hemi Right Hemi fBIRN Group n=18, working memory, distractor-vs-fix

  21. Individual Subject Integration

  22. Viewing Functional Activation on the Volume tkmedit bert orig.mgz -aux brain.mgz -overlay ./fbert1.feat/stats/zstat1.nii.gz -overlay-reg ./fbert1.feat/reg/freesurfer/anat2exf.register.dat -fthresh 2.3 –fmax 4.3 -seg aparc+aseg.mgz Visual, Auditory, Motor Thresholds depend on the nature of the data, Eg, for zstat image, 2.3 means z > 2.3 Can be changed with View->Configure->FunctionalOverlay Can display any functional data, eg, zstat, fzstat, cope, pe, etc

  23. Volume Viewing • Red/Yellow + • Blue/Cyan - • Seg Opacity • ROI Average • ROI Count

  24. Viewing FEAT Stats on the Surface tksurfer bert rh inflated -overlay ./fbert1.feat/stats/zstat1.nii.gz -overlay-reg ./fbert1.feat/reg/freesurfer/anat2exf.register.dat -fthresh 2.3 -fmid 3.3 -fslope 1 Visual, Auditory, Motor Can display any functional data, eg, zstat, fzstat, cope, pe, etc

  25. Surface Viewing • Red/Yellow +,Blue/Cyan - • Parcellation Outline • ROI Average • ROI Count

  26. Mapping Automatic Segmentations aseg.mgz aparc+aseg.mgz lh.aparc.annot $FREESURFER_HOME/FreeSurferColorsLUT.txt Maps numerical index to ROI name, eg Left-Hippocamus = 17

  27. Mapping Automatic Segmentations aseg2feat --feat fbert.feat –aseg aparc+aseg In the functional FOV, creates: fbert1.feat/reg/freesurfer/aseg+aparc.nii.gz Create Text Summary Table (nvox, mean cope, std cope, etc) mri_segstats --seg fbert1.feat/reg/freesurfer/aparc+aseg.nii.gz --nonempty --ctab-default --in fbert.feat/stats/cope1.nii.gz --sum fbert1.sum.txt Can summarize any functional data, eg, zstat, fzstat, cope, pe, etc

  28. Make and View ROI Make a binary mask of the left putamen: Note: 12 = Left Putamen, see $FREESURFER_HOME/FreeSurferColorsLUT.txt fslmaths ./fbert1.feat/reg/freesurfer/aparc+aseg.nii.gz -thr 12 -uthr 12 ./fbert1.feat/reg/freesurfer/lh.putamen.nii.gz tkmedit bert orig.mgz -aux brain.mgz -overlay ./fbert1.feat/reg/freesurfer/lh.putamen.nii.gz -overlay-reg ./fbert1.feat/reg/freesurfer/anat2exf.register.dat -fthresh 0.5 -seg aparc+aseg.mgz

  29. Practical Data • Sensory-motor study • Blocked Design (15sec OFF, 15 sec ON) • One subject – “bert” • Two runs (TR=3, 85 time points) • FEAT has been run on both runs (FWHM=5) • Combined with GFEAT • FFx • One-Sample Group Mean (OSGM) • Actually, all analysis steps already performed!

  30. Practical • Automatic registration (<5 min) • Manual registration • View FEAT results on subject’s anatomy (aparc+aseg) • View FEAT results with tksurfer • Map aparc+aseg to Functional Space • Verify GFEAT registration • View GFEAT results in volume and on surface • “Higher-Level” analysis with mri_glmfit • Cross-Run • Fixed-Effects (FFX), One-Sample Group Mean (osgm)

  31. End of Presentation

  32. Sampling on the Surface: Projection Fraction -0.1 0.0 (white) +0.1 +0.3 +0.5 +0.7 +0.9 +1.0 (pial) +1.1

  33. Step 1: Register Anatomical with Surface Atlas (fsaverage) Native Anatomical Surface Space Surface-based Registration fsaverage Space S recon-all Anatomical Surface in fsaverage Space

  34. Step 2: Register fMRI with Anatomical Native Anatomical Space Native Functional Space Rigid Registration R reg-feat2anat bbregister fMRI in Anatomical Space

  35. Step 3: Combine Steps 1 and 2: mris_preproc Native Anatomical Space Native Functional Space fsaverage Space S R recon-all reg-feat2anat bbregister fMRI in fsaverage Space

  36. Within-Subject, Cross-Run Analysis • Analyze each run with FEAT (dataX.feat) • Combine runs with GFEAT (standard space) • mean_func.nii.gz – avg of example_func in std space • Register each run (not .gfeat) with reg-feat2anat. • dataX.feat/reg/freesurfer/anat2std.register.dat • All runs (X) should be very close Verify the registration tkregister2 –mov data.gfeat/mean_func.nii.gz --reg anat2std.register.dat --surf Use anat2std.register.dat the way you would anat2exf.register.dat

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