# 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
epochsEpochs object

Single trial epochs.

inverse_operatordict

Inverse operator.

lambda2float

The regularization parameter.

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

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

label

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

naveint

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

pick_oriNone | “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_generatorbool

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

preparedbool

If True, do not call prepare_inverse_operator().

method_params

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

New in version 0.16.

verbose

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

Returns
stc

The source estimates for all epochs.

apply_inverse_raw
apply_inverse