## Note: This page was created with the CommandTemplate ## ## If you're modifying this page please take a look at the ## latest version of CommandTemplate to ensure that you're ## using the latest version of the CommandTemplate ## ## See HelpOnCommandTemplate for description of formatting '''Index''' <> = Name = [[fcseed-sess]] Computes seeds (regressors) that can be used for functional connectivity analysis or for use as nuisance regressors. NOTE: this program is still experimental. Use at your own risk! = Synopsis = fcseed-sess -segid -fillthresh 0.5 -s bert -mean = Arguments = == Required Flagged Arguments == ||-sf sessidfile || supply text file with list of subjects || ||-df srchdirfile || search in this dir for subjects || ||-s sessid || single subject processing || ||-d srchdir || search in this dir for single subject || ||-fsd fsdir name || dir name for location of bold data & analyses within subjectdir || == Optional Flagged Arguments == ||-seg segid <-segid segid2 ...> ||use FreeSurfer segmentation as seed || use FreeSurfer Segmentation IDs for common ROIs (found in $FREESURFER_HOME/FreesurferColorLUT.txt)|| ||-wm || all white matter as seed (erroded by 3 voxels) ||Useful to use as nuisance regressor time-course || ||-vcsf|| ventricles & Cerebrospinal fluid as seed || Useful to use as nuisance regressor time-course || ||-m || maskfile || output mask for segmentation-based. Good for checking || ||-overwrite ||overwrite || delete and overwrite any existing files|| ||-mean || use mean || compute spatial mean seed region time-course for seed region || ||-pca || use pca || compute principal component analysis for seed instead of spatial mean. seedregion.dat file will contain one component time-course per row|| ||-roi || roiconfig || as created by funcroi-confg || ||-version|| print version || ||-help || print help text|| using -roi flag: ROI-based Seed Regions The ROI-based seed region is the result of a functional ROI analysis (see funcroi-config). Note that the functional ROI may have a different FSD than the functional connectivity analysis. This can be helpful when creating an ROI from a task but applying it to rest data. = Outputs = ||seedregion.dat || time course data from seed region || ||seedregion.log || fcseed-sess run log || = Description = Computes seeds (regressors) that can be used for functional connectivity analysis or for use as nuisance regressors. Seed regions can be defined in two ways: (1) as an anatomical region in a segmentation such as aparc+aseg, or (2) as an ROI created with funcroi-config. The seed regions are always subject-specific. The output is a text file in the same directory as the raw data. This file will be named based on the -o flag. For segmentation-based, the segmentation must exist in $SUBJECTS_DIR/$subject/mri. By default the segmentation is aparc+aseg. This can be changed with -seg (eg, -seg aparc+aseg would be the same as the default). You must specify a segmentation index with -segid. Eg, if you are using aparc+aseg, then 17 would be left hippocampus (this is defined in $FREEESURFER_HOME/FreeSurferColorLUT.txt). You can specify any number of segmentations; they will be combined into one seed region (eg, (-segid 17 -segid 53 would produce one seed region from both hippocampi). The segmentation will be converted from the 1mm anatomical space into the native functional space. For this, you can specify a fill threshold. This governs how much an anatomical segmentation must fill a functional voxel must be in order for it to be considered part of the seed region. This is a number between 0 (the smallest part of a voxel) to 1 (all of the voxel). To avoid quatifification artifacts, it is recommended that this not be set above .8. Default is .5. There are two default segmentations: (1) white matter (-wm) and (2) ventricular CSF (-vcsf). The white matter option first creates a mask of the WM in the anatomical space by finding the voxels in the aparc+aseg.mgz with indices 2 and 41. It then erodes the mask by 3 voxels. It then converts the mask to native functional space with fillthresh=0.5 The CSF segmentation uses segmentation indices 4 5 14 43 44 31 and 63 with fillthresh=.75. Both use a PCA output. These are good to use as nuisance regressors for functional connectivity analysis. = Examples = == Example 1 == Create a seed waveform by spatially averaging the entire left hemisphere hippocampus: fcseed-sess -o lh.hippo.dat -segid 17 -s session -fsd rest This will create files called lh.hippo.dat in session/rest/RRR where RRR is the run directory. == Example 2 == Create white matter and ventricular CSF nuisance regressors fcseed-sess -o wm.dat -wm -s session -fsd rest fcseed-sess -o vcsf.dat -vcsf -s session -fsd rest == Analysis Example == First, create an analysis folder and setup file using mkanalysis-sess i.e.: mkanalysis-sess -a fc-lh.hippo.rhemi -notask -taskreg lh.hippo.dat 1 -nuisreg wm.dat 3 -nuisreg vcsf.dat 3 -surface fsaverage rh -fwhm 5 -fsd rest -TR 2 This analysis is called "fc-lh.hippo.rhemi". It uses the single waveform found in lh.hippo.dat as the "task regressor". It also adds 3 PCA waveforms from both the white matter and the CSF as nuisance regressors. Note that a contrast does not need to be made because one is automatically created with an -taskreg. This data can be analyzed with selxavg3-sess and isxconcat-sess just as if it were any task-based analysis. = Bugs = None = See Also = [[othercommand1]], [[othercommand2]] = Links = FreeSurfer, FsFast = Methods Description = {{{ description description }}} = References = [[References/Lastname##|References/Lastname###]] = Reporting Bugs = Report bugs to < analysis-bugs@nmr.mgh.harvard.edu > = Author/s = JaneSmith