mne.preprocessing.ieeg.project_sensors_onto_brain#
- mne.preprocessing.ieeg.project_sensors_onto_brain(info, trans, subject, subjects_dir=None, picks=None, n_neighbors=10, copy=True, verbose=None)[source]#
Project sensors onto the brain surface.
- Parameters:
- info
mne.Info The
mne.Infoobject with information about the sensors and methods of measurement.- trans
str|dict| instance ofTransform If str, the path to the head<->MRI transform
*-trans.fiffile produced during coregistration. Can also be'fsaverage'to use the built-in fsaverage transformation.- subject
str The FreeSurfer subject name.
- subjects_dirpath-like |
None The path to the directory containing the FreeSurfer subjects reconstructions. If
None, defaults to theSUBJECTS_DIRenvironment variable.- picks
str| array_like |slice|None Channels 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 onlyecogchannels.- n_neighbors
int The 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.
- copy
bool If
True, return a new instance ofinfo, ifFalseinfois modified in place.- verbose
bool|str|int|None Control verbosity of the logging output. If
None, use the default verbosity level. See the logging documentation andmne.verbose()for details. Should only be passed as a keyword argument.
- info
- Returns:
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.
