mne.stc_to_label#

mne.stc_to_label(stc, src=None, smooth=True, connected=False, subjects_dir=None, verbose=None)[source]#

Compute a label from the non-zero sources in an stc object.

Parameters:
stcSourceEstimate

The source estimates.

srcSourceSpaces | str | None

The source space over which the source estimates are defined. If it’s a string it should the subject name (e.g. fsaverage). Can be None if stc.subject is not None.

smoothbool

Fill in vertices on the cortical surface that are not in the source space based on the closest source space vertex (requires src to be a SourceSpace).

connectedbool

If True a list of connected labels will be returned in each hemisphere. The labels are ordered in decreasing order depending of the maximum value in the stc.

subjects_dirpath-like | None

The path to the directory containing the FreeSurfer subjects reconstructions. If None, defaults to the SUBJECTS_DIR environment variable.

verbosebool | str | int | None

Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

Returns:
labelslist of Label | list of list of Label

The generated labels. If connected is False, it returns a list of Labels (one per hemisphere). If no Label is available in a hemisphere, None is returned. If connected is True, it returns for each hemisphere a list of connected labels ordered in decreasing order depending of the maximum value in the stc. If no Label is available in an hemisphere, an empty list is returned.

Examples using mne.stc_to_label#

Generate a functional label from source estimates

Generate a functional label from source estimates