mne.make_forward_solution(info, trans, src, bem, meg=True, eeg=True, mindist=0.0, ignore_ref=False, n_jobs=1, verbose=None)[source]

Calculate a forward solution for a subject.

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.

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).


If True (Default), include MEG computations.


If True (Default), include EEG computations.


Minimum distance of sources from inner skull surface (in mm).


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.


The number of jobs to run in parallel (default 1). If -1, it is set to the number of CPU cores. Requires the joblib package.

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.

fwdinstance of Forward

The forward solution.


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