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This page will outline how to split a full FreeSurfer aparc annotation into multiple seeds To use a portion of the full Freesurfer parcellation ("split parcellation"), follow the [[FsFastFunctionalConnectivityWalkthrough |additional steps here]] - and resume with step 5 on this page...
This page will outline how to split a full FreeSurfer aparc annotation into multiple seeds to use a portion of the full Freesurfer parcellation ("split parcellation") as your seed region.
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echo "isthmuscingulate 3" > seed.isthmuscingulate.3.txt *STEP 2: use [[mris_divide_parcellation]]. This command will generate a new parcellation including your split ROI, as well as all original parcellations outside your chosen region.
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 mris_divide_parcellation $recondir $hemi aparc.annot $txt ${hemi}.${splitN}split set splitN = 3 #this is the number of divisions to make
echo "isthmuscingulate 3" > seed.isthmuscingulate.3.txt #
set splitstem = <hemi>.isthmuscingulate.3.split #name for divided surface annotation
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 mris_divide_parcellation <recondir> <hemi> aparc.annot seed.isthmuscingulate.3.txt ${hemi}.${splitN}split
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*STEP 4: Use fcseed-config to record the parameters you wish to pass to your connectivity analysis. *STEP 3: use [[mri_annotation2label]] to create labels from the new annotation. This will create a label for each parcellation (including labels for regions outside of your desired seed region). The labels will be deposited in the subject's recondir/label directory.
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Sample command:
fcseed-config -segid 1010 -fcname mean.L_Posteriorcingulate.dat -fsd bold -mean -cfg mean.L_Posteriorcingulate.config
          mri_annotation2label --subject <recondir> \
                               --hemi <hemi> \
                               --labelbase <hemi>.isthmuscingulate.3 \
                               --annotation 3split \
                               --surface pial
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This example will use the FreeSurfer cortical segmentation for the left posterior cingulate (segID: 1010). For seed regions, we recommend generating the mean signal timecourse by using "-mean" To remove the excess labels, I've used this method:
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@ splitN2 = $splitN + 1 #this number will be helpful when removing excess labels
set rmextra = `find $SUBJECTS_DIR/<recondir>/label -maxdepth 1 -type f | \
                                        grep <hemi>.isthmuscingulate.3 | \
                                                              sort -nr | \
                                                   sed -n ${splitN2},500p`
                                                 #this command lists all files in the label dir, greps for our label name,
                                                 #sorts numerically in reverse, then grabs all labels after the first 3
echo " REMOVING excess labels "
rm -v $rmextra
set lbls = `find $ldir -maxdepth 1 -type f | grep <hemi>.isthmuscingulate.3 | sort -nr` #grabs our seed labels
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*STEP 4: check that you've grabbed the correct seed labels by loading them in [[tksurfer]]

*STEP 5: Use [[mri_label2vol]] on each of the split seed labels to obtain a segmentation volume for each.
         
               mri_label2vol --label <label> \
                             --temp $SUBJECTS_DIR/<recondir>/mri/brainmask.nii.gz \
                             --proj frac 0 1 .1 \
                             --subject <recondir> --hemi <hemi> \
                             --regheader $SUBJECTS_DIR/<recondir>/mri/brainmask.nii.gz \
                             --o <outsegname>

*STEP 6: Use fcseed-config to record the parameters you wish to pass to your connectivity analysis.

Sample command for running the mean time course and using the first (1) of the 3 seed split:

  set type = mean # For seed regions, we recommend generating the mean signal timecourse by using "-mean"
  set segname = <hemi>.isthmuscingulate.split3.1
  fcseed-sess -s <subject> \
               -segid 1 \
               -o ${type}.${segname}.dat \
               -seg <outsegname> \
               -fsd bold \
               -${type} \
               -cfg {type}.${segname}.config

Note: this is a companion page to the FsFastFunctionalConnectivityWalkthrough page.

This page will outline how to split a full FreeSurfer aparc annotation into multiple seeds to use a portion of the full Freesurfer parcellation ("split parcellation") as your seed region.

*STEP 1: create a text file with the name of the full parcellation of interest and the number of seeds. Possible structures can be found here: $FREESURFER_HOME/average/colortable_desikan_killiany.txt

  • NOTE: The method I've show below divides the parcellation, orthogonally along its long axis.
    • There is also a method of using mris_divide_parcellation that specifies a unit of area for each seed.

*STEP 2: use mris_divide_parcellation. This command will generate a new parcellation including your split ROI, as well as all original parcellations outside your chosen region.

set splitN = 3 #this is the number of divisions to make echo "isthmuscingulate 3" > seed.isthmuscingulate.3.txt # set splitstem = <hemi>.isthmuscingulate.3.split #name for divided surface annotation

  • mris_divide_parcellation <recondir> <hemi> aparc.annot seed.isthmuscingulate.3.txt ${hemi}.${splitN}split

*STEP 3: use mri_annotation2label to create labels from the new annotation. This will create a label for each parcellation (including labels for regions outside of your desired seed region). The labels will be deposited in the subject's recondir/label directory.

  • mri_annotation2label --subject <recondir> \

    • --hemi <hemi> \ --labelbase <hemi>.isthmuscingulate.3 \ --annotation 3split \ --surface pial

To remove the excess labels, I've used this method:

@ splitN2 = $splitN + 1 #this number will be helpful when removing excess labels set rmextra = `find $SUBJECTS_DIR/<recondir>/label -maxdepth 1 -type f | \

  • grep <hemi>.isthmuscingulate.3 | \

    • sort -nr | \
    • sed -n ${splitN2},500p`
    • #this command lists all files in the label dir, greps for our label name, #sorts numerically in reverse, then grabs all labels after the first 3

echo " REMOVING excess labels " rm -v $rmextra set lbls = find $ldir -maxdepth 1 -type f | grep <hemi>.isthmuscingulate.3 | sort -nr #grabs our seed labels

*STEP 4: check that you've grabbed the correct seed labels by loading them in tksurfer

*STEP 5: Use mri_label2vol on each of the split seed labels to obtain a segmentation volume for each.

  • mri_label2vol --label <label> \

    • --temp $SUBJECTS_DIR/<recondir>/mri/brainmask.nii.gz \ --proj frac 0 1 .1 \ --subject <recondir> --hemi <hemi> \ --regheader $SUBJECTS_DIR/<recondir>/mri/brainmask.nii.gz \ --o <outsegname>

*STEP 6: Use fcseed-config to record the parameters you wish to pass to your connectivity analysis.

Sample command for running the mean time course and using the first (1) of the 3 seed split:

  • set type = mean # For seed regions, we recommend generating the mean signal timecourse by using "-mean"

    set segname = <hemi>.isthmuscingulate.split3.1 fcseed-sess -s <subject> \

    • -segid 1 \ -o ${type}.${segname}.dat \

      -seg <outsegname> \ -fsd bold \ -${type} \ -cfg {type}.${segname}.config

Now resume with step 5 on this page...

FsFastFunctionalConnectivityWalkthroughSplittingSeeds (last edited 2011-10-20 11:18:37 by TylerTriggs)