This document provides instructions for coregistering MRI data with MEG data in MNE-Python. It describes selecting the MRI and raw data files, setting fiducial points on the MRI, initially aligning the MRI and head shape, fine-tuning the alignment through translation and automatic fitting, and saving the final transformation between the head shape and MRI. The coregistration process allows the MRI to be used for visualization and modeling of MEG data.

1. Coregistration in mne-python
Subjects with 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
•
If it is not automatically selected, select
the MRI subject
•
If a fiducials file is found in the MRI
directory it is automatically loaded and
you can skip the next slide. If not, load a
file manually, or specify the fiducials as
described on 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
•
Since the MRI stems from the
same subject and thus has the
right size, make sure scaling is
off (“No scaling”)
•
Use LPA and RPA for an initial
approximate alignment

7. 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)

8. Coregistration
•
The head shape and MRI are
initially aligned using the
Nasion; in order to modify the
initial alignment use the
translation parameters
•
Then use the automatic fitting
functions and manual
parameter adjustment to find
a satisfactory coregistration

9. Saving
•
Finally hit the save button to save the
head-MRI transformation in a *-trans.fif
file
•
When creating the forward solution,
specify this file as the mri argument