mne.make_sphere_model#

mne.make_sphere_model(r0=(0.0, 0.0, 0.04), head_radius=0.09, info=None, relative_radii=(0.9, 0.92, 0.97, 1.0), sigmas=(0.33, 1.0, 0.004, 0.33), verbose=None)[source]#

Create a spherical model for forward solution calculation.

Parameters
r0array-like | str

Head center to use (in head coordinates). If ‘auto’, the head center will be calculated from the digitization points in info.

head_radiusfloat | str | None

If float, compute spherical shells for EEG using the given radius. If ‘auto’, estimate an appropriate radius from the dig points in Info, If None, exclude shells (single layer sphere model).

infomne.Info | None

The mne.Info object with information about the sensors and methods of measurement. Only needed if r0 or head_radius are 'auto'.

relative_radiiarray-like

Relative radii for the spherical shells.

sigmasarray-like

Sigma values for the spherical shells.

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
sphereinstance of ConductorModel

The resulting spherical conductor model.

Notes

The default model has:

relative_radii = (0.90, 0.92, 0.97, 1.0)
sigmas = (0.33, 1.0, 0.004, 0.33)

These correspond to compartments (with relative radii in m and conductivities σ in S/m) for the brain, CSF, skull, and scalp, respectively.

New in version 0.9.0.

Examples using mne.make_sphere_model#

Setting the EEG reference

Setting the EEG reference

Setting the EEG reference
Source alignment and coordinate frames

Source alignment and coordinate frames

Source alignment and coordinate frames
Brainstorm Elekta phantom dataset tutorial

Brainstorm Elekta phantom dataset tutorial

Brainstorm Elekta phantom dataset tutorial
Brainstorm CTF phantom dataset tutorial

Brainstorm CTF phantom dataset tutorial

Brainstorm CTF phantom dataset tutorial
4D Neuroimaging/BTi phantom dataset tutorial

4D Neuroimaging/BTi phantom dataset tutorial

4D Neuroimaging/BTi phantom dataset tutorial
Plot sensor denoising using oversampled temporal projection

Plot sensor denoising using oversampled temporal projection

Plot sensor denoising using oversampled temporal projection
Plotting sensor layouts of EEG systems

Plotting sensor layouts of EEG systems

Plotting sensor layouts of EEG systems