mne.minimum_norm.apply_inverse

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

Apply inverse operator to evoked data

Parameters:

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).

Returns:

stc : SourceEstimate | VolSourceEstimate

The source estimates

See also

apply_inverse_raw
Apply inverse operator to raw object
apply_inverse_epochs
Apply inverse operator to epochs object