mne.make_bem_model#

mne.make_bem_model(subject, ico=4, conductivity=(0.3, 0.006, 0.3), subjects_dir=None, verbose=None)[source]#

Create a BEM model for a subject.

Note

To get a single layer bem corresponding to the –homog flag in the command line tool set the conductivity parameter to a list/tuple with a single value (e.g. [0.3]).

Parameters
subjectstr

The subject.

icoint | None

The surface ico downsampling to use, e.g. 5=20484, 4=5120, 3=1280. If None, no subsampling is applied.

conductivityarray of int, shape (3,) or (1,)

The conductivities to use for each shell. Should be a single element for a one-layer model, or three elements for a three-layer model. Defaults to [0.3, 0.006, 0.3]. The MNE-C default for a single-layer model would be [0.3].

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
surfaceslist of dict

The BEM surfaces. Use make_bem_solution to turn these into a ConductorModel suitable for forward calculation.

Notes

New in version 0.10.0.

Examples using mne.make_bem_model#

Working with CTF data: the Brainstorm auditory dataset

Working with CTF data: the Brainstorm auditory dataset

Working with CTF data: the Brainstorm auditory dataset
Head model and forward computation

Head model and forward computation

Head model and forward computation
Fixing BEM and head surfaces

Fixing BEM and head surfaces

Fixing BEM and head surfaces