mne.minimum_norm.make_inverse_operator¶

mne.minimum_norm.make_inverse_operator(info, forward, noise_cov, loose='auto', depth=0.8, fixed='auto', limit_depth_chs=None, rank=None, use_cps=True, verbose=None)[source]¶

Assemble inverse operator.

Parameters

infodict: The measurement info to specify the channels to include. Bad channels in info[‘bads’] are not used.
forwarddict: Forward operator.
noise_covinstance of Covariance: The noise covariance matrix.
loosefloat in [0, 1] | ‘auto’: Value that weights the source variances of the dipole components that are parallel (tangential) to the cortical surface. If loose is 0 then the solution is computed with fixed orientation, and fixed must be True or “auto”. If loose is 1, it corresponds to free orientations. The default value (‘auto’) is set to 0.2 for surface-oriented source space and set to 1.0 for volumetric, discrete, or mixed source spaces, unless fixed is True in which case the value 0. is used.
depthNone | float | dict: How to weight (or normalize) the forward using a depth prior. If float (default 0.8), it acts as the depth weighting exponent (exp) to use, which must be between 0 and 1. None is equivalent to 0, meaning no depth weighting is performed. It can also be a dict containing keyword arguments to pass to mne.forward.compute_depth_prior() (see docstring for details and defaults).
fixedbool | ‘auto’: Use fixed source orientations normal to the cortical mantle. If True, the loose parameter must be “auto” or 0. If ‘auto’, the loose value is used.
limit_depth_chsbool: Deprecated and will be removed in 0.19. Use depth=dict(limit_depth_chs=...).
rankNone | dict | ‘info’ | ‘full’: This controls the rank computation that can be read from the measurement info or estimated from the data. See Notes of mne.compute_rank() for details.The default is None.
use_cpsNone | bool (default True): Whether to use cortical patch statistics to define normal orientations. Only used when converting to surface orientation (i.e., for surface source spaces and loose < 1).
verbosebool, str, int, or None: If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

Returns

invinstance of InverseOperator: Inverse operator.

Notes

For different sets of options (loose, depth, fixed) to work, the forward operator must have been loaded using a certain configuration (i.e., with force_fixed and surf_ori set appropriately). For example, given the desired inverse type (with representative choices of loose = 0.2 and depth = 0.8 shown in the table in various places, as these are the defaults for those parameters):

Inverse desired

Forward parameters allowed

loose

depth

fixed

force_fixed

surf_ori

Loose constraint,

Depth weighted

0.2

0.8

False

False

True

Loose constraint

0.2

None

False

False

True

Free orientation,

Depth weighted

1.0

0.8

False

False

True

Free orientation

1.0

None

False

False

True | False

Fixed constraint,

Depth weighted

0.0

0.8

True

False

True

Fixed constraint

0.0

None

True

True

True

Inverse desired	Forward parameters allowed
	loose	depth	fixed	force_fixed	surf_ori
Loose constraint, Depth weighted	0.2	0.8	False	False	True
Loose constraint	0.2	None	False	False	True
Free orientation, Depth weighted	1.0	0.8	False	False	True
Free orientation	1.0	None	False	False	True \| False
Fixed constraint, Depth weighted	0.0	0.8	True	False	True
Fixed constraint	0.0	None	True	True	True

Also note that, if the source space (as stored in the forward solution) has patch statistics computed, these are used to improve the depth weighting. Thus slightly different results are to be expected with and without this information.