mne.minimum_norm.apply_inverse(evoked, inverse_operator, lambda2=0.1111111111111111, method=’dSPM’, pick_ori=None, prepared=False, label=None, verbose=None)[source]

Apply inverse operator to evoked data.


evoked : Evoked object

Evoked data.

inverse_operator: instance of InverseOperator

Inverse operator returned from mne.read_inverse_operator, prepare_inverse_operator or make_inverse_operator.

lambda2 : float

The regularization parameter.

method : “MNE” | “dSPM” | “sLORETA”

Use mininum norm, dSPM or sLORETA.

pick_ori : None | “normal”

If “normal”, rather than pooling the orientations by taking the norm, only the radial component is kept. This is only implemented when working with loose orientations.

prepared : bool

If True, do not call prepare_inverse_operator.

label : Label | None

Restricts the source estimates to a given label. If None, source estimates will be computed for the entire source space.

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).


stc : SourceEstimate | VolSourceEstimate

The source estimates

See also

Apply inverse operator to raw object
Apply inverse operator to epochs object