This document provides instructions for coregistering MRI data to MEG data in MNE-Python without a subject's individual MRI. It describes selecting a template brain MRI, setting fiducials, initially aligning the head shape to the MRI, scaling the MRI for proper fit, fine-tuning the alignment manually, and saving the transformed MRI and head-MRI coregistration parameters.

1. Coregistration in mne-python
Subjects without MRI

2. General Notes
•
The GUI uses the traits library
which supports different
backends but seems to work
best with QT4 currently. To
make QT4 the default:
• In Canopy: change
Preferences/Python/PyLab
backend
• In a terminal: $ export
ETS_TOOLKIT=“qt4”
•
The coregistration GUI is a
recent addition to MNEPython; please report
unexpected behavior to the
mne-analysis mailing list

3. Overview
Select MRI
Scale the MRI
3D View
Set MRI
Fiducials
Find Head Shape
to MRI Coregistration
Select Raw File
Control the
3D View
Save the Result

4. Input Files
•
Specify the directory containing MRIsubjects (subjects_dir)
•
Select the Raw file for which to do the
coregistration
•
Select the template brain to use. The
default template that comes with
freesurfer and MNE is fsaverage. The
fsaverage files can be copied into the
subjects directory with the “Copy
FsAverage to Subject Folder” button (the
button does not work if a subject named
“fsaverage” already exists).
•
Fsaverage comes with fiducials which
should be automatically loaded, in which
case you can skip the next slide.

5. Fiducials
•
Select the fiducial you want to
modify, and then click on the
head model to specify the
position. Fiducials are
displayed as small colored
spheres.
•
When all the fiducials are
specified, save the positions
so they can be loaded in the
future.
•
Lock the fiducials to proceed
to the coregistration.

6. Coregistration
•
Use “Fit LPA/RPA” to find an
initial approximate alignment

7. Coregistration
•
Head shape and MRI are
initially aligned at the nasion.
Adjust the nasion alignment to
properly align the forehead

8. Coregistration
•
In case the head shape
contains outlier points, head
shape points can be omitted
based on their distance from
the MRI head surface (for the
sample data, 10 mm is a good
distance)

9. Scaling
•
Select the desired number of
scaling parameters (scaling
with the same factor along all
axes or scaling with a separate
factor for the X, Y and Z axes)
•
Use the automatic fitting
functions as well as manual
adjustment to find a proper
MRI scaling factor

10. Coregistration
•
Once a proper scaling factor is found,
use the fitting function that don’t scale
the MRI as well as manual adjustment to
fine tune the coregistration

11. Saving
•
Finally hit the save button to save the
scaled MRI as well as the head-MRI
transformation in a *-trans.fif file