mne.minimum_norm.apply_inverse_epochs

mne.minimum_norm.apply_inverse_epochs(epochs, inverse_operator, lambda2, method='dSPM', label=None, nave=1, pick_ori=None, return_generator=False, prepared=False, method_params=None, verbose=None)[source]

Apply inverse operator to Epochs.

Parameters:
epochs : Epochs object

Single trial epochs.

inverse_operator : dict

Inverse operator.

lambda2 : float

The regularization parameter.

method : “MNE” | “dSPM” | “sLORETA” | “eLORETA”

Use mininum norm, dSPM (default), sLORETA, or eLORETA.

label : Label | None

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

nave : int

Number of averages used to regularize the solution. Set to 1 on single Epoch by default.

pick_ori : None | “normal” | “vector”

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. If “vector”, no pooling of the orientations is done and the vector result will be returned in the form of a mne.VectorSourceEstimate object. This does not work when using an inverse operator with fixed orientations.

return_generator : bool

Return a generator object instead of a list. This allows iterating over the stcs without having to keep them all in memory.

prepared : bool

If True, do not call prepare_inverse_operator().

method_params : dict | None

Additional options for eLORETA. See Notes of apply_inverse().

New in version 0.16.

verbose : bool, str, int, or None

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

Returns:
stc : list of (SourceEstimate | VectorSourceEstimate | VolSourceEstimate)

The source estimates for all epochs.

See also

apply_inverse_raw
Apply inverse operator to raw object
apply_inverse
Apply inverse operator to evoked object