mne.morph_data(subject_from, subject_to, stc_from, grade=5, smooth=None, subjects_dir=None, buffer_size=64, n_jobs=1, warn=True, verbose=None)

Morph a source estimate from one subject to another


subject_from : string

Name of the original subject as named in the SUBJECTS_DIR

subject_to : string

Name of the subject on which to morph as named in the SUBJECTS_DIR

stc_from : SourceEstimate

Source estimates for subject “from” to morph

grade : int, list (of two arrays), or None

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 grade[0] and grade[1]. Note that specifying the vertices (e.g., grade=[np.arange(10242), np.arange(10242)] for fsaverage on a standard grade 5 source space) can be substantially faster than computing vertex locations. Note that if subject=’fsaverage’ and ‘grade=5’, this set of vertices will automatically be used (instead of computed) for speed, since this is a common morph.

smooth : int or None

Number of iterations for the smoothing of the surface data. If None, smooth is automatically defined to fill the surface with non-zero values.

subjects_dir : string, or None

Path to SUBJECTS_DIR if it is not set in the environment.

buffer_size : int

Morph data in chunks of buffer_size time instants. Saves memory when morphing long time intervals.

n_jobs : int

Number of jobs to run in parallel

warn : bool

If True, warn if not all vertices were used.

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose).


stc_to : SourceEstimate

Source estimate for the destination subject.