Differences between revisions 7 and 8
Deletions are marked like this. Additions are marked like this.
Line 33: Line 33:
||-seg segid <-segid segid2 ...> ||use FreeSurfer segmentation as seed || desc || ||-seg segid <-segid segid2 ...> ||use FreeSurfer segmentation as seed || use FreeSurfer Segmentation IDs for common ROIs (found in $FREESURFER_HOME/FreesurferColorLUT.txt)||




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!


fcseed-sess -segid <SegID#> -fillthresh 0.5 -s bert -mean


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)


all white matter as seed (erroded by 3 voxels)

Useful to use as nuisance regressor time-course


ventricles & Cerebrospinal fluid as seed

Useful to use as nuisance regressor time-course



output mask for segmentation-based. Good for checking



delete and overwrite any existing files


use mean

compute spatial mean seed region time-course for seed region


use pca

compute principal component analysis for seed instead of spatial mean. seed.dat file will contain one component time-course per row



as created by funcroi-confg


print version


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.



time course data from seed region


fcseed-sess run log


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.


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


  • 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.



See Also

othercommand1, othercommand2


FreeSurfer, FsFast

Methods Description




Reporting Bugs

Report bugs to < analysis-bugs@nmr.mgh.harvard.edu >



fcseed-sess (last edited 2011-01-13 17:31:04 by TylerTriggs)