Coregistration in mne-pythonSubjects without MRI

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 MNE-Python; please report unexpected behavior to the mne-analysis mailing list

Overview

Select Raw File

Set MRI Fiducials

Select MRI Scale the MRI

Save the Result

Find Head Shape to MRI Co- registration

Control the 3D View

3D View

Input Files• Specify the directory containing MRI-

subjects (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.

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.

Coregistration• Use “Fit LPA/RPA” to find an

initial approximate alignment

Coregistration• Head shape and MRI are

initially aligned at the nasion. Adjust the nasion alignment to properly align the forehead

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)

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

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

Saving• Finally hit the save button to save the

scaled MRI as well as the head-MRI transformation in a *-trans.fif file