Retinotopic Mapping

MRI
Retinotopy
Procedure to apply the probabilistic retinotopic mapping using the Benson Atlas
Author

MG

Published

May 5, 2025

Retinotopic mapping is used to individually identify subregions in the visual cortex (i.e V1, V2, V3 and sometimes higher areas as well). This is then used to better understand how visual information is processed in the brain by different regions.

Normally, this is achieved by implementing dedicated “retinotopy-runs” in the experimental design. However, this is not always possible.

The Benson2014 atlas allows to get a retinotopic mapping even without dedicated “retinotopy-runs” by using structural features and probabilistic maps.

The script

The script to run the probabilistic retinotopic mapping can be found on the server: /shared/website/occatlas.sh

Alternatively, you can copy/paste the code (after adapting it for your data! See below):

#!/usr/bin/env bash

# This script demonstrates how to run Benson's neuropythy atlas on neurodesk
# and map early visual areas onto the subject's functional volume space
# NZ 2025.03.21

# define variables and make dirs
ml freesurfer/7.4.1 # tested with fs 7.4.1
sid=999
niidir=/home/jovyan/completion/4_conditions_main/bids
export SUBJECTS_DIR=$niidir/derivatives/fmriprep/sourcedata/freesurfer
export SINGULARITYENV_SUBJECTS_DIR=$SUBJECTS_DIR # this is container-specific definition of SUBJECTS_DIR
export APPTAINERENV_SUBJECTS_DIR=$SUBJECTS_DIR   # this is container-specific definition of SUBJECTS_DIR
mkdir -p /home/jovyan/completion/4_conditions_main/bids/neuropythy_tmp
show=yes # show images: yes or no
do_volumetric=no # run volumetric (surf2vol) part: yes or no

# run benson's occipital atlas docker as singularity container
tmpdir=/home/jovyan/completion/4_conditions_main/bids/neuropythy_tmp
singularity run -B $SUBJECTS_DIR:/subjects \
  -B $tmpdir:/data docker://nben/neuropythy \
  atlas --verbose sub-$sid

if [ "$show" = "yes" ]; then
  # take a look at the data
  freeview \
    -f $SUBJECTS_DIR/sub-$sid/surf/lh.inflated:overlay=$SUBJECTS_DIR/sub-$sid/surf/lh.benson14_varea.mgz:overlay_color=colorwheel \
    -f $SUBJECTS_DIR/sub-$sid/surf/rh.inflated:overlay=$SUBJECTS_DIR/sub-$sid/surf/rh.benson14_varea.mgz:overlay_color=colorwheel
fi

# run volumetric projection if enabled
if [ "$do_volumetric" = "yes" ]; then

  # surf2vol
  mkdir -p $niidir/derivatives/rois/sub-$sid

  # loop over hemis
  for hemi in lh rh; do

    # convert to t1 space first
    mri_surf2vol \
      --surfval $SUBJECTS_DIR/sub-$sid/surf/$hemi.benson14_varea.mgz \
      --temp $SUBJECTS_DIR/sub-$sid/mri/orig.mgz \
      --identity sub-$sid \
      --o $niidir/derivatives/rois/sub-$sid/$hemi.sub-${sid}_benson14_varea_space-T1.nii.gz \
      --fill-projfrac -0.5 1.5 0.05 \
      --subject "sub-$sid" \
      --hemi $hemi

    if [ "$show" = "yes" ]; then
      freeview \
        $SUBJECTS_DIR/sub-$sid/mri/orig.mgz \
        $niidir/derivatives/rois/sub-$sid/$hemi.sub-${sid}_benson14_varea_space-T1.nii.gz:colormap=LUT
    fi

    # now convert from T1 to BOLD space
    mri_vol2vol \
      --mov $niidir/derivatives/rois/sub-$sid/$hemi.sub-${sid}_benson14_varea_space-T1.nii.gz \
      --targ $niidir/derivatives/fmriprep/sub-$sid/ses-1/func/*task-loc*space-T1w_boldref.nii.gz \
      --o $niidir/derivatives/rois/sub-$sid/$hemi.sub-${sid}_benson14_varea_space-bold.nii.gz \
      --regheader \
      --nearest

    if [ "$show" = "yes" ]; then
      freeview \
        $niidir/derivatives/fmriprep/sub-$sid/ses-1/func/*task-loc*space-T1w_boldref.nii.gz \
        $niidir/derivatives/rois/sub-$sid/$hemi.sub-${sid}_benson14_varea_space-bold.nii.gz:colormap=LUT
    fi

    # binarize the labels
    mri_binarize \
      --i $niidir/derivatives/rois/sub-$sid/$hemi.sub-${sid}_benson14_varea_space-bold.nii.gz \
      --match 1 2 3 --o "$niidir/derivatives/rois/sub-$sid/$hemi.sub-${sid}_evc_space-bold.nii.gz"

  done

  # unite hemispheres and binarize again
  mri_concat \
    --i $niidir/derivatives/rois/sub-$sid/lh.sub-${sid}_evc_space-bold.nii.gz \
    --i $niidir/derivatives/rois/sub-$sid/rh.sub-${sid}_evc_space-bold.nii.gz \
    --sum \
    --o $niidir/derivatives/rois/sub-$sid/sub-${sid}_evc_space-bold.nii.gz

fi

# the rest should probably be done in python, thresholding values on the fly

Necessary adaptiation steps

  1. Change the variable sid to match the subject you want to process (only the number is necessary! In the script it will be implemented as sub-sid)

  2. Change the variable niidir to match the path to your BIDS-directory

  3. Optional (you can look at the output later anyway): Change the variable show to see the intermediate steps (\(\to\) show=yes vs. show=no)

  4. Indicate if you use volumentric (do_volumetric=yes) oder surface data (do_volumentric=no) in your later analysis

  5. Save your changes

  6. Run the script \(\to\) open a terminal and execute:

  1. bash /Path/to/occatlas.sh
  2. change the working directory to where the script is using cd /Path/to/directory/with/script and then bash ./occatlas.sh
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