FreeSurfer MRI reconstruction#

First steps#

After downloading and installing FreeSurfer, there are a few steps to set up the environment. First is to define an environment variable FREESURFER_HOME and then run the FreeSurfer setup script:

$ export FREESURFER_HOME=/path/to/FreeSurfer
$ source $FREESURFER_HOME/SetUpFreeSurfer.sh

Another important step is to tell FreeSurfer where to put the anatomical reconstructions of your research subjects. This is done with an environment variable called SUBJECTS_DIR, which will contain the individual subjects’ reconstructions in separate sub-folders.

$ export SUBJECTS_DIR=/path/to/your/subjects_dir

Again see the FreeSurfer installation guide for more info.

Anatomical reconstruction#

The first processing stage is the creation of various surface reconstructions. Usually a full FreeSurfer reconstruction is obtained by the following commands:

$ my_subject=sample
$ my_NIfTI=/path/to/NIfTI.nii.gz
$ recon-all -i $my_NIfTI -s $my_subject -all

where i stands for “input” and s for “subject”. Executing this will create the folder $SUBJECTS_DIR/sample and populate it with several subfolders (bem, label, mri, etc). See also the FreeSurfer wiki’s recommended reconstruction workflow for more detailed explanation.

FreeSurfer performs a hemispheric separation so most resulting files have separate left and right hemisphere versions, indicated by the prefix lh or rh. This hemispheric separation is preserved by MNE-Python (e.g., mne.SourceEstimate objects store spatial locations (vertices) for the two hemispheres separately; cf. The SourceEstimate data structure).

Below we show an example of the results of a FreeSurfer reconstruction for the left hemisphere of the Sample dataset subject, including an overlay of an anatomical parcellation (in this case, the parcellation from [1]).

import mne

sample_data_folder = mne.datasets.sample.data_path()
subjects_dir = sample_data_folder / 'subjects'
Brain = mne.viz.get_brain_class()
brain = Brain('sample', hemi='lh', surf='pial',
              subjects_dir=subjects_dir, size=(800, 600))
brain.add_annotation('aparc.a2009s', borders=False)

Use with MNE-Python#

For source localization analysis to work properly, it is important that the FreeSurfer reconstruction has completed beforehand. Furthermore, for many MNE-Python functions related to inverse imaging (such as mne.setup_source_space), SUBJECTS_DIR has to be defined globally (as an environment variable or through a call to mne.set_config), or specified separately in each function call by passing the keyword argument subjects_dir='/path/to/your/subjects_dir'.

See Setting up the source space to get an idea of how this works for one particular function, and How MNE uses FreeSurfer’s outputs for more details on how MNE-Python and FreeSurfer are integrated.

‘fsaverage’#

During installation, FreeSurfer copies a subject called 'fsaverage' to $FREESURFER_HOME/subjects/fsaverage. fsaverage is a template brain based on a combination of 40 MRI scans of real brains. The fsaverage subject folder contains all the files that a normal subject reconstruction would yield. See https://surfer.nmr.mgh.harvard.edu/fswiki/FsAverage for an overview, and https://surfer.nmr.mgh.harvard.edu/fswiki/Buckner40Notes for details about the subjects used to create fsaverage. A copy of fsaverage is also provided as part of the Sample dataset and is also distributed as a standalone dataset.

One of the most common uses of fsaverage is as a destination space for cortical morphing / source estimate transformations. In other words, it is common to morph each individual subject’s estimated brain activity onto the fsaverage brain, so that group-level statistical comparisons can be made.

References#

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