mne.make_forward_solution#

mne.make_forward_solution(info, trans, src, bem, meg=True, eeg=True, *, mindist=0.0, ignore_ref=False, n_jobs=None, verbose=None)[source]#

Calculate a forward solution for a subject.

Parameters:

infomne.Info | path-like: The mne.Info object with information about the sensors and methods of measurement. If path-like, it should be a str or pathlib.Path to a file with measurement information (e.g. mne.io.Raw).
transpath-like | dict | instance of Transform | "fsaverage" | None: If 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. If trans is None, an identity matrix is assumed.

Changed in version 0.19: Support for 'fsaverage' argument.
srcpath-like | instance of SourceSpaces: Either a path to a source space file or a loaded or generated SourceSpaces.
bempath-like | ConductorModel: Filename of the BEM (e.g., "sample-5120-5120-5120-bem-sol.fif") to use, or a loaded ConductorModel. See make_bem_model() and make_bem_solution() to create a mne.bem.ConductorModel.
megbool: If True (default), include MEG computations.
eegbool: If True (default), include EEG computations.
mindistfloat: Minimum distance of sources from inner skull surface (in mm).
ignore_refbool: If True, do not include reference channels in compensation. This option should be True for KIT files, since forward computation with reference channels is not currently supported.
n_jobsint | None: The number of jobs to run in parallel. If -1, it is set to the number of CPU cores. Requires the joblib package. None (default) is a marker for ‘unset’ that will be interpreted as n_jobs=1 (sequential execution) unless the call is performed under a joblib.parallel_config context manager that sets another value for n_jobs.
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:

fwdinstance of Forward: The forward solution.

Examples using `mne.make_forward_solution`#

From raw data to dSPM on SPM Faces dataset

Use source space morphing

Compute MNE inverse solution on evoked data with a mixed source space

Plot point-spread functions (PSFs) for a volume

Compute source power spectral density (PSD) of VectorView and OPM data

Head model and forward computation

EEG forward operator with a template MRI

EEG source localization given electrode locations on an MRI

Working with CTF data: the Brainstorm auditory dataset

Setting the EEG reference

Preprocessing optically pumped magnetometer (OPM) MEG data

mne.make_forward_solution#

Examples using mne.make_forward_solution#

Examples using `mne.make_forward_solution`#