compute_source_morph(src, subject_from=None, subject_to='fsaverage', subjects_dir=None, zooms='auto', niter_affine=(100, 100, 10), niter_sdr=(5, 5, 3), spacing=5, smooth=None, warn=True, xhemi=False, sparse=False, src_to=None, verbose=False)¶
Create a SourceMorph from one subject to another.
- srcinstance of
SourceSpaces| instance of
The SourceSpaces of subject_from (can be a SourceEstimate if only using a surface source space).
Name of the original subject as named in the SUBJECTS_DIR. If None (default), then
src['subject_his_id]'will be used.
Name of the subject to which to morph as named in the SUBJECTS_DIR. Default is
'fsaverage'. If None,
src_to['subject_his_id']will be used.
Changed in version 0.20: Support for subject_to=None.
The path to the freesurfer subjects reconstructions. It corresponds to Freesurfer environment variable SUBJECTS_DIR.
The voxel size of volume for each spatial dimension in mm. If spacing is None, MRIs won’t be resliced, and both volumes must have the same number of spatial dimensions. Can also be
src_to is Noneand the zooms from
Changed in version 0.20: Support for ‘auto’ mode.
Number of levels (
len(niter_affine)) and number of iterations per level - for each successive stage of iterative refinement - to perform the affine transform. Default is niter_affine=(100, 100, 10).
Number of levels (
len(niter_sdr)) and number of iterations per level - for each successive stage of iterative refinement - to perform the Symmetric Diffeomorphic Registration (sdr) transform. Default is niter_sdr=(5, 5, 3).
The resolution of the icosahedral mesh (typically 5). If None, all vertices will be used (potentially filling the surface). If a list, then values will be morphed to the set of vertices specified in in
spacing. This will be ignored if
Changed in version 0.21: src_to, if provided, takes precedence.
Number of iterations for the smoothing of the surface data. If None, smooth is automatically defined to fill the surface with non-zero values. Can also be
'nearest'to use the nearest vertices on the surface (requires SciPy >= 1.3).
Changed in version 0.20: Added support for ‘nearest’.
If True, warn if not all vertices were used. The default is warn=True.
Morph across hemisphere. Currently only implemented for
subject_to == subject_from. See notes below. The default is xhemi=False.
Morph as a sparse source estimate. Works only with (Vector) SourceEstimate. If True the only parameters used are subject_to and subject_from, and spacing has to be None. Default is sparse=False.
- src_toinstance of
The destination source space.
For surface-based morphing, this is the preferred over
spacingfor providing the vertices.
For volumetric morphing, this should be passed so that 1) the resultingmorph volume is properly constrained to the brain volume, and 2) STCs from multiple subjects morphed to the same destination subject/source space have the vertices.
For mixed (surface + volume) morphing, this is required.
New in version 0.20.
- srcinstance of
This function can be used to morph data between hemispheres by setting
xhemi=True. The full cross-hemisphere morph matrix maps left to right and right to left. A matrix for cross-mapping only one hemisphere can be constructed by specifying the appropriate vertices, for example, to map the right hemisphere to the left:
vertices_from=[, vert_rh], vertices_to=[vert_lh, ].
Cross-hemisphere mapping requires appropriate
sphere.left_rightmorph-maps in the subject’s directory. These morph maps are included with the
fsaverage_symFreeSurfer subject, and can be created for other subjects with the
mris_left_right_registerFreeSurfer command. The
fsaverage_symsubject is included with FreeSurfer > 5.1 and can be obtained as described here. For statistical comparisons between hemispheres, use of the symmetric
fsaverage_symmodel is recommended to minimize bias 1.
New in version 0.17.0.
New in version 0.21.0: Support for morphing mixed source estimates.
Douglas N. Greve, Lise Van der Haegen, Qing Cai, Steven Stufflebeam, Mert R. Sabuncu, Bruce Fischl, and Marc Brysbaert. A surface-based analysis of language lateralization and cortical asymmetry. Journal of Cognitive Neuroscience, 25(9):1477–1492, 2013. doi:10.1162/jocn_a_00405.
Brian B. Avants, Charles L. Epstein, Murray C. Grossman, and James C. Gee. Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Medical Image Analysis, 12(1):26–41, 2008. doi:10.1016/j.media.2007.06.004.