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%matplotlib inline

Morph volumetric source estimate

This example demonstrates how to morph an individual subject's :class:mne.VolSourceEstimate to a common reference space. We achieve this using :class:mne.SourceMorph. Pre-computed data will be morphed based on an affine transformation and a nonlinear registration method known as Symmetric Diffeomorphic Registration (SDR) by :footcite:AvantsEtAl2008.

Transformation is estimated from the subject's anatomical T1 weighted MRI (brain) to FreeSurfer's 'fsaverage' T1 weighted MRI (brain) <https://surfer.nmr.mgh.harvard.edu/fswiki/FsAverage>__.

Afterwards the transformation will be applied to the volumetric source estimate. The result will be plotted, showing the fsaverage T1 weighted anatomical MRI, overlaid with the morphed volumetric source estimate.



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# Author: Tommy Clausner <tommy.clausner@gmail.com>
#
# License: BSD (3-clause)
import os

import nibabel as nib
import mne
from mne.datasets import sample, fetch_fsaverage
from mne.minimum_norm import apply_inverse, read_inverse_operator
from nilearn.plotting import plot_glass_brain

print(__doc__)

Setup paths



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sample_dir_raw = sample.data_path()
sample_dir = os.path.join(sample_dir_raw, 'MEG', 'sample')
subjects_dir = os.path.join(sample_dir_raw, 'subjects')

fname_evoked = os.path.join(sample_dir, 'sample_audvis-ave.fif')
fname_inv = os.path.join(sample_dir, 'sample_audvis-meg-vol-7-meg-inv.fif')

fname_t1_fsaverage = os.path.join(subjects_dir, 'fsaverage', 'mri',
                                  'brain.mgz')
fetch_fsaverage(subjects_dir)  # ensure fsaverage src exists
fname_src_fsaverage = subjects_dir + '/fsaverage/bem/fsaverage-vol-5-src.fif'

Compute example data. For reference see sphx_glr_auto_examples_inverse_plot_compute_mne_inverse_volume.py

Load data:



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evoked = mne.read_evokeds(fname_evoked, condition=0, baseline=(None, 0))
inverse_operator = read_inverse_operator(fname_inv)

# Apply inverse operator
stc = apply_inverse(evoked, inverse_operator, 1.0 / 3.0 ** 2, "dSPM")

# To save time
stc.crop(0.09, 0.09)

Get a SourceMorph object for VolSourceEstimate

subject_from can typically be inferred from :class:src <mne.SourceSpaces>, and subject_to is set to 'fsaverage' by default. subjects_dir can be None when set in the environment. In that case SourceMorph can be initialized taking src as only argument. See :class:mne.SourceMorph for more details.

The default parameter setting for zooms will cause the reference volumes to be resliced before computing the transform. A value of '5' would cause the function to reslice to an isotropic voxel size of 5 mm. The higher this value the less accurate but faster the computation will be.

The recommended way to use this is to morph to a specific destination source space so that different subject_from morphs will go to the same space.` A standard usage for volumetric data reads:



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src_fs = mne.read_source_spaces(fname_src_fsaverage)
morph = mne.compute_source_morph(
    inverse_operator['src'], subject_from='sample', subjects_dir=subjects_dir,
    niter_affine=[10, 10, 5], niter_sdr=[10, 10, 5],  # just for speed
    src_to=src_fs, verbose=True)

Apply morph to VolSourceEstimate

The morph can be applied to the source estimate data, by giving it as the first argument to the :meth:morph.apply() <mne.SourceMorph.apply> method:



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stc_fsaverage = morph.apply(stc)

Convert morphed VolSourceEstimate into NIfTI

We can convert our morphed source estimate into a NIfTI volume using :meth:morph.apply(..., output='nifti1') <mne.SourceMorph.apply>.



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# Create mri-resolution volume of results
img_fsaverage = morph.apply(stc, mri_resolution=2, output='nifti1')

Plot results



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# Load fsaverage anatomical image
t1_fsaverage = nib.load(fname_t1_fsaverage)

# Plot glass brain (change to plot_anat to display an overlaid anatomical T1)
display = plot_glass_brain(t1_fsaverage,
                           title='subject results to fsaverage',
                           draw_cross=False,
                           annotate=True)

# Add functional data as overlay
display.add_overlay(img_fsaverage, alpha=0.75)

Reading and writing SourceMorph from and to disk

An instance of SourceMorph can be saved, by calling :meth:morph.save <mne.SourceMorph.save>.

This methods allows for specification of a filename under which the morph will be save in ".h5" format. If no file extension is provided, "-morph.h5" will be appended to the respective defined filename::

>>> morph.save('my-file-name')

Reading a saved source morph can be achieved by using :func:mne.read_source_morph::

>>> morph = mne.read_source_morph('my-file-name-morph.h5')

Once the environment is set up correctly, no information such as subject_from or subjects_dir must be provided, since it can be inferred from the data and used morph to 'fsaverage' by default, e.g.::

>>> morph.apply(stc)

References

.. footbibliography::