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[[FsFastTutorialV5.1|top]] | [[FsFastTutorialV5.1|previous]]| [[FsFastTutorialV5.1/FsFastDirStruct|next (Directory Structure)]] |
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| = FSFAST Tutorial Data Description = | = Surface-based Interhemispheric Registration = |
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| The functional data were collected as part of the Functional Biomedical Research Network (fBIRN, www.nbirn.net). | Those using this procedure should site the following paper: Greve, Douglas N., Lise Van der Haegen, Qing Cai, Steven Stufflebeam, Mert R. Sabuncu, Bruce Fischl, and Marc Bysbaert. "A surface-based analysis of language lateralization and cortical asymmetry." (2013). Journal of Cognitive Neuroscience 25.9 (2013): 1477-1492. |
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| * Working-memory paradigm with distractors * 18 subjects * Each subject has 1 run (except sess01 which has 4 runs) * Collected at MGH Bay 4 (3T Siemens) * FreeSurfer anatomical analyses |
== Installation == |
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| = Functional Paradigm = | Note: you only need to do this installation if you have version 5.1 or lower |
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| The paradigm was designed to study the effects of emotional stimuli on the ability to recall items stored in working memory. * Blocked design * Each block consisted of 3 phases 1. Encode (16 sec) - 8 stick figures to remember (no response) 1. Distractor (16 sec) - 8 distractor images (response whether there is a face in the image) a. Emotional - Distractors are emotionally disturbing a. Neutral - Distractors are emotionally neutral 1. Probe (16 sec) - 8 pairs of stick figures. Subject responds as to which of the pair was in the original Encode. * Between each block was a 16 sec scrambled image used as baseline. {{attachment:wmparadigm.jpg}} The above yields 5 conditions: 1. Encode 1. Emotional Distractor 1. Neutral Distractor 1. Probe following Emotional Distractor 1. Probe following Neutral Distractor The scrambled image will be modeled as a baseline, not as a condition. = Functional Data = * Original data: each subject had 8 runs * This data: each subject has 1 run (except for sess01 who has 4) * Each run lasts 142 time points * TR = 2 sec. * There is one run of rest data for 13 subjects * There is a B0 map for each subject = Anatomical Data = * FreeSurfer analysis has been run for all 18 subjects = Getting the Data (not necessary for the Boston FreeSurfer Course) = You can get the analyzed functional data (10G) from: |
Download these files |
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| wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fsfast-functional.tar.gz | ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/surfreg ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/xhemireg ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/mris_preproc ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/fsaverage_sym.tar.gz ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/mult-comp-cor.tar.gz ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/mri_convert.{linux,mac} ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/mri_vol2vol.{linux,mac} ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/mri_surf2surf.{linux,mac} |
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| You can get the structural data (5G) from: | Copy surfreg, xhemireg, mris_preproc into $FREESURFER_HOME/bin Copy mri_convert.{linux,mac} into $FREESURFER_HOME/bin/mri_convert Copy mri_vol2vol.{linux,mac} into $FREESURFER_HOME/bin/mri_vol2vol # Untar fsaverage_sym.tar.gz into your $SUBJECTS_DIR cd $SUBJECTS_DIR tar xvfz fsaverage_sym.tar.gz # Untar mult-comp-cor.tar.gz into $FREESURFER_HOME/average cd $FREESURFER_HOME/average tar xvfz mult-comp-cor.tar.gz # Copy mris_preproc into $FREESURFER_HOME/bin after making a backup To apply an existing atlas (eg, fsaverage_sym) to an anatomical analysis == Apply an existing atlas (fsaverage_sym) == # Reg to atlas (1-2 hours per subject) # Creates $subject/xhemi # Creates lh.fsaverage_sym.sphere.reg in $subject and $subject/xhemi |
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| wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fsfast-tutorial.subjects.tar.gz | foreach subject (subjectlist) surfreg --s $subject --t fsaverage_sym --lh surfreg --s $subject --t fsaverage_sym --lh --xhemi end |
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= Organizing the Tutorial (not necessary for the Boston FreeSurfer Course) = cd to a place on your network where you have enough space to unpack the tutorial data. |
# Create a stack of subjects |
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| cd /place/with/space }}} Untar the data {{{ tar xvfz fsfast-tutorial.tar.gz tar xvfz fsfast-tutorial.subjects.tar.gz |
mris_preproc --target fsaverage_sym --hemi lh --xhemi --paired-diff \ --srcsurfreg fsaverage_sym.sphere.reg \ --meas thickness \ --out lh.lh-rh.thickness.sm00.mgh \ --s subj1 --s subj2 ... |
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| You will need to set the TUTORIAL_DATA environment variable. In tcsh or csh |
# Smooth. This example smooths by 10mm on the surface. This is only an example and your data might be better off being smoothed more or less. There is no way to determine what the optimal smoothing level is. |
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| setenv TUTORIAL_DATA /place/with/space | mris_fwhm --s fsaverage_sym --hemi lh --cortex --smooth-only --fwhm 10\ --i lh.lh-rh.thickness.sm00.mgh --o lh.lh-rh.thickness.sm10.mgh |
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| You will also need to link the FreeSurfer anatomical subjeccts (data in fsfast-tutorial.subjects) into your $SUBJECTS_DIR. You should set the FSFAST output format to be compressed NIFTI (nii.gz): |
# Analyze |
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| setenv FSF_OUTPUT_FORMAT nii.gz | mri_glmfit --y lh.lh-rh.thickness.sm10.mgh --glmdir glm.lh.lh-rh.thickness.sm10 \ --osgm --surf fsaverage_sym lh |
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| [[FsFastTutorialV5.1|top]] | [[FsFastTutorialV5.1|previous]]| [[FsFastTutorialV5.1/FsFastDirStruct|next (Directory Structure)]] | # View {{{ tksurfer fsaverage_sym lh inflated -aparc -overlay glm.lh.lh-rh.thickness.sm10/osgm/sig.mgh }}} # Correct for multiple comparisons {{{ mri_glmfit-sim --glmdir glm.lh.lh-rh.thickness.sm10 \ --cwpvalthresh .5 --cache 2 abs }}} == Build Your Own Atlas == # Create xhemi subject (don't reg, a few minutes to finish) {{{ foreach subject (subjectlist) xhemireg --s $subject end }}} # Reg to existing sym atlas # Note: if you want test how symmetrical the atlas is use --lhrh # (but it takes twice as long) {{{ foreach subject (subjectlist) surfreg --s $subject --t fsaverage_sym --lh surfreg --s $subject --t fsaverage_sym --xhemi --lh end }}} # Make first iteration (<5min) {{{ make_average_subject --out myatlas.i1 \ --surf-reg fsaverage_sym.sphere.reg \ --subjects subjectlist \ --xhemi \ --no-vol --template-only }}} # Reg to first iteration # Note: if you want test the symmetry, use --lhrh {{{ foreach subject (subjectlist) surfreg --s $subject --t myatlas.i1 --lh surfreg --s $subject --t myatlas.i1 --xhemi --lh end }}} # Make second iteration (<5min) {{{ make_average_subject --out myatlas.i2 \ --surf-reg myatlas.i1.sphere.reg \ --subjects subjectlist \ --xhemi \ --no-vol --template-only }}} # Reg to second iteration. Note: if you want test the symmetry, use --lhrh {{{ foreach subject (subjectlist) surfreg --s $subject --t myatlas.i2 --lh surfreg --s $subject --t myatlas.i2 --xhemi --lh end }}} # Make final iteration (1-2 hours) {{{ make_average_subject --out myatlas.i3 \ --surf-reg myatlas.i2.sphere.reg \ --subjects subjectlist \ --xhemi --hemi lh }}} |
Contents
1. Surface-based Interhemispheric Registration
Those using this procedure should site the following paper: Greve, Douglas N., Lise Van der Haegen, Qing Cai, Steven Stufflebeam, Mert R. Sabuncu, Bruce Fischl, and Marc Bysbaert. "A surface-based analysis of language lateralization and cortical asymmetry." (2013). Journal of Cognitive Neuroscience 25.9 (2013): 1477-1492.
1.1. Installation
Note: you only need to do this installation if you have version 5.1 or lower
Download these files
ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/surfreg
ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/xhemireg
ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/mris_preproc
ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/fsaverage_sym.tar.gz
ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/mult-comp-cor.tar.gz
ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/mri_convert.{linux,mac}
ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/mri_vol2vol.{linux,mac}
ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/5.1.0/xhemi/mri_surf2surf.{linux,mac}Copy surfreg, xhemireg, mris_preproc into $FREESURFER_HOME/bin Copy mri_convert.{linux,mac} into $FREESURFER_HOME/bin/mri_convert Copy mri_vol2vol.{linux,mac} into $FREESURFER_HOME/bin/mri_vol2vol
# Untar fsaverage_sym.tar.gz into your $SUBJECTS_DIR cd $SUBJECTS_DIR tar xvfz fsaverage_sym.tar.gz
# Untar mult-comp-cor.tar.gz into $FREESURFER_HOME/average cd $FREESURFER_HOME/average tar xvfz mult-comp-cor.tar.gz
# Copy mris_preproc into $FREESURFER_HOME/bin after making a backup To apply an existing atlas (eg, fsaverage_sym) to an anatomical analysis
1.2. Apply an existing atlas (fsaverage_sym)
# Reg to atlas (1-2 hours per subject) # Creates $subject/xhemi # Creates lh.fsaverage_sym.sphere.reg in $subject and $subject/xhemi
foreach subject (subjectlist) surfreg --s $subject --t fsaverage_sym --lh surfreg --s $subject --t fsaverage_sym --lh --xhemi end
# Create a stack of subjects
mris_preproc --target fsaverage_sym --hemi lh --xhemi --paired-diff \ --srcsurfreg fsaverage_sym.sphere.reg \ --meas thickness \ --out lh.lh-rh.thickness.sm00.mgh \ --s subj1 --s subj2 ...
# Smooth. This example smooths by 10mm on the surface. This is only an example and your data might be better off being smoothed more or less. There is no way to determine what the optimal smoothing level is.
mris_fwhm --s fsaverage_sym --hemi lh --cortex --smooth-only --fwhm 10\ --i lh.lh-rh.thickness.sm00.mgh --o lh.lh-rh.thickness.sm10.mgh
# Analyze
mri_glmfit --y lh.lh-rh.thickness.sm10.mgh --glmdir glm.lh.lh-rh.thickness.sm10 \ --osgm --surf fsaverage_sym lh
# View
tksurfer fsaverage_sym lh inflated -aparc -overlay glm.lh.lh-rh.thickness.sm10/osgm/sig.mgh
# Correct for multiple comparisons
mri_glmfit-sim --glmdir glm.lh.lh-rh.thickness.sm10 \ --cwpvalthresh .5 --cache 2 abs
1.3. Build Your Own Atlas
# Create xhemi subject (don't reg, a few minutes to finish)
foreach subject (subjectlist) xhemireg --s $subject end
# Reg to existing sym atlas # Note: if you want test how symmetrical the atlas is use --lhrh # (but it takes twice as long)
foreach subject (subjectlist) surfreg --s $subject --t fsaverage_sym --lh surfreg --s $subject --t fsaverage_sym --xhemi --lh end
# Make first iteration (<5min)
make_average_subject --out myatlas.i1 \ --surf-reg fsaverage_sym.sphere.reg \ --subjects subjectlist \ --xhemi \ --no-vol --template-only
# Reg to first iteration # Note: if you want test the symmetry, use --lhrh
foreach subject (subjectlist) surfreg --s $subject --t myatlas.i1 --lh surfreg --s $subject --t myatlas.i1 --xhemi --lh end
# Make second iteration (<5min)
make_average_subject --out myatlas.i2 \ --surf-reg myatlas.i1.sphere.reg \ --subjects subjectlist \ --xhemi \ --no-vol --template-only
# Reg to second iteration. Note: if you want test the symmetry, use --lhrh
foreach subject (subjectlist) surfreg --s $subject --t myatlas.i2 --lh surfreg --s $subject --t myatlas.i2 --xhemi --lh end
# Make final iteration (1-2 hours)
make_average_subject --out myatlas.i3 \ --surf-reg myatlas.i2.sphere.reg \ --subjects subjectlist \ --xhemi --hemi lh
