Time Series Data in MNI Space: Difference between revisions

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     fi
     fi
  done
  done
=Working with ROIs=
The above code extracts mean time series for all voxels in each labeled region in the aseg.mgz file. However, it is possible to use a masked subcortical segmentation file, which you can [[Working_with_Subcortical_ROIs_(Freesurfer) | create]].

Revision as of 14:53, 20 September 2020

Thanks to Cary for sorting this out. It appears that the process for obtaining mean time series from the mni305 volumes generated by preproc-sess is very similar to that for time series in surface space

After the data have been detrended, mri_segstats can be called on the detrended volume to extract the average waveform within each of the labeled segments.

#Assume ${sub} contains the subject ID
#Assume ${r} contains the run number
#Assume ${FILEPAT} contains the name of the detrended volume: 
FILEPAT=fmcpr.siemens.sm7.mni305.2mm.mgh
mri_segstats --seg /usr/local/freesurfer/5.3.0/subjects/fsaverage/mri.2mm/aseg.mgz --i ${sub}/bold/${r}/${FILEPAT} \
--ctab /usr/local/freesurfer/5.3.0/FreeSurferColorLUT.txt \
--sum ${sub}/bold/${r}/sum_subcort.txt \
--avgwf ${sub}_${r}.${FILEPAT}.wav.txt

This will generate a *.wav.txt file in the current working directory with t=timepoints rows and s=43 columns (1 per segment).

The following is a script which will automate the process for just the MNI space files. The commands below have been incorporated into the more general gettimecourses.sh scripts, so the code below is appropriate for when surface space data have already been extracted and you wish to go back and get the subcortical data.

getmnitimecourses.sh

#!/bin/bash
USAGE="Usage: getmnitimecourses.sh filepattern sub1 ... subN"

if [ "$#" == "0" ]; then
        echo "$USAGE"
        exit 1
fi

#first two parameters are is the annot files and filepatterns for the \
#.nii.gz time series to be detrended, up to the hemisphere indicator
#e.g., fmcpr.sm6.self.?h.nii.gz would use fmcpr.sm6.self as the filepattern
filepat="$1"
shift

#subjects
subs=( "$@" );
#hemispheres
hemis=( lh rh )

for sub in "${subs[@]}"; do
source_dir=${SUBJECTS_DIR}/${sub}/bold

    if [ ! -d ${source_dir} ]; then
        #The subject_id does not exist
        echo "${source_dir} does not exist!"
    else
	cd ${source_dir}
	readarray -t runs < runs
	for hemi in "${hemis[@]}"; do
		for r in "${runs[@]}"; do
			if [ -n "${r}" ]; then
			mri_segstats \
        		--seg /usr/local/freesurfer/5.3.0/subjects/fsaverage/mri.2mm/aseg.mgz \
        		--i ${source_dir}/${r}/${filepat} \
        		--sum ${sub}_${hemi}_${annot}_${r}.${filepat}.sum.txt \
			--ctab /usr/local/freesurfer/5.3.0/FreeSurferColorLUT.txt \
       			--avgwf ${sub}_${hemi}_${annot}_${r}.${filepat}.wav.txt
			fi
		done
	done
    fi
done

Working with ROIs

The above code extracts mean time series for all voxels in each labeled region in the aseg.mgz file. However, it is possible to use a masked subcortical segmentation file, which you can create.