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 | str

The mne.Info object with information about the sensors and methods of measurement. If str, then it should be a filepath to a file with measurement information (e.g. mne.io.Raw).

transstr | dict | instance of Transform | 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.

srcstr | instance of SourceSpaces

If string, should be a source space filename. Can also be an instance of loaded or generated SourceSpaces.

bemdict | str

Filename of the BEM (e.g., “sample-5120-5120-5120-bem-sol.fif”) to use, or a loaded sphere model (dict).

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_backend() 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.

Notes

The --grad option from MNE-C (to compute gradients) is not implemented here.

To create a fixed-orientation forward solution, use this function followed by mne.convert_forward_solution().

Examples using mne.make_forward_solution#

Working with CTF data: the Brainstorm auditory dataset

Working with CTF data: the Brainstorm auditory dataset

Working with CTF data: the Brainstorm auditory dataset
Setting the EEG reference

Setting the EEG reference

Setting the EEG reference
Head model and forward computation

Head model and forward computation

Head model and forward computation
EEG forward operator with a template MRI

EEG forward operator with a template MRI

EEG forward operator with a template MRI
EEG source localization given electrode locations on an MRI

EEG source localization given electrode locations on an MRI

EEG source localization given electrode locations on an MRI
Compute source power spectral density (PSD) of VectorView and OPM data

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

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

Use source space morphing

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

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

Compute MNE inverse solution on evoked data with a mixed source space
From raw data to dSPM on SPM Faces dataset

From raw data to dSPM on SPM Faces dataset

From raw data to dSPM on SPM Faces dataset