Project sensors onto the brain surface.
mne.InfoThe mne.Info object with information about the sensors and methods of measurement.
str | dict | instance of TransformIf str, the path to the head<->MRI transform *-trans.fif file produced
during coregistration. Can also be 'fsaverage' to use the built-in
fsaverage transformation.
strThe FreeSurfer subject name.
NoneThe path to the directory containing the FreeSurfer subjects
reconstructions. If None, defaults to the SUBJECTS_DIR environment
variable.
str | list | slice | NoneChannels to include. Slices and lists of integers will be interpreted as
channel indices. In lists, channel type strings (e.g., ['meg',
'eeg']) will pick channels of those types, channel name strings (e.g.,
['MEG0111', 'MEG2623'] will pick the given channels. Can also be the
string values “all” to pick all channels, or “data” to pick data
channels. None (default) will pick only ecog channels.
intThe number of neighbors to use to compute the normal vectors for the projection. Must be 2 or greater. More neighbors makes a normal vector with greater averaging which preserves the grid structure. Fewer neighbors has less averaging which better preserves contours in the grid.
If True, return a new instance of info, if False
info is modified in place.
str | int | NoneControl 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.
Notes
This is useful in ECoG analysis for compensating for “brain shift” or shrinking of the brain away from the skull due to changes in pressure during the craniotomy.
To use the brain surface, a BEM model must be created e.g. using mne watershed_bem using the T1 or mne flash_bem using a FLASH scan.
mne.preprocessing.ieeg.project_sensors_onto_brain#