#### DISCLAIMER ####
Copyright (c) 2016, Simon Vandekar, UNIVERSITY OF PENNSYLVANIA
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#### DESCRIPTION ####
Coupling is a localized estimate of the spatial relationship between two cortical measures.
#### SETUP ####
These scripts will require your FREESURFER_HOME environment variable to
There are two options for setup:
1) Run the setup script which will require sudo to add files to the freesurfer
2) Perform all the steps in the setup script manually.
First cd to the folder where you downloaded the coupling scripts and run
/path/to/preferred/R/version/bin/R --slave --file=./setup.R
This script will try to download a required R package "optparse" and create a
folder in your freesurfer home directory called "R" where it will place the
code required to run coupling.
It will ask for sudo permissions when making $FREESURFER_HOME/R and copying the R
code into the directory, but not when installing the package.
It will make this version of R the default version used to estimate coupling.
There is a string in the top of the coupling script "###SHEBANG###" That gets replaced
by "/path/to/preferred/R/version/bin/Rscript", so that the script will run at the
Perform the steps above. You will need appropriate permissions for each step.
After running the setup script, add $FREESURFER_HOME/R to your path by adding
this line to your .bashrc:
The coupling_v*.R script also require that your SUBJECTS_DIR is set.
You will also need Rscript in your version of R e.g.
#### FILES ####
Files included in this package:
coupling_v*.R is a command line R program that estimates coupling for a given
list of subjects. type coupling_v1.R -h for help
kth_neighbors_v*.R is run by coupling_v*.R and estimates the first k sets of
nearest neighbors for each vertex for a particular template. This takes the
longest amount of time, but only needs to be run once. This can be modified
with the maxneigh argument in coupling_v*.R.
grid_submit.sh is an example on how to run coupling_v*.R on Sun Grid Engine.
Coupling automatically tries to detect SGE, or LSF array id variables. If it
cannot find either of them then it runs sequentially. grid_submit.sh waits for
the first job to run successfully before trying to run the full list of subjects.
The first subject run finds the kth nearest neightbors for the given template.
All other jobs will wait for the successful completion of the first subject
#### EXAMPLES ####
echo $SUBJECTS_DIR # $FREESURFER_HOME/subjects
cat my_subject_list.txt # bert
coupling_v1.R -s ./my_subject_list.txt
coupling_v1.R -s ./my_subject_list.txt -m "thickness,curv" # with curvature instead of sulcal depth
coupling_v1.R -s ./my_subject_list.txt -m "sulc,thickness" # reverse of default relationship
coupling_v1.R -s ./my_subject_list.txt -f 3 # less weighting than default
coupling_v1.R -s ./my_subject_list.txt -t fsaverage4 # coarser template. (gives smoother result due to weighting being in neighbor units)
coupling_v1.R -s ./my_subject_list.txt -t fsaverage6 # finer template (gives less smooth result).
coupling_v1.R -s ./my_subject_list.txt -o # overwrites files
coupling_v1.R -s ./my_subject_list.txt -n 15 # max number of neighborly separation with nonzero weight. Not really essential, 10 (default) works well in practice
#### OUTPUT ####
Neighbor information is stored here in an R rds file for this template.
If they don't already exists, labels are created for this template using mri_annotation2label in
In each subjects directory:
also intermediate files:
#### COMMENTS ####
can be analyzed as you would typically with other surfaces, e.g. using mri_glmfit or