mne-python coregistration

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Coregistration in mne-python Subjects with MRI

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Page 1: MNE-Python Coregistration

Coregistration in mne-pythonSubjects with MRI

Page 2: MNE-Python Coregistration

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

Page 3: MNE-Python Coregistration

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

Page 4: MNE-Python Coregistration

Input Files• Specify the directory containing MRI-

subjects (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.

Page 5: MNE-Python Coregistration

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.

Page 6: MNE-Python Coregistration

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

Page 7: MNE-Python Coregistration

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)

Page 8: MNE-Python Coregistration

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

Page 9: MNE-Python Coregistration

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