- epochs : instance of Epochs
The raw data.
- inverse_operator : instance of InverseOperator
The inverse operator.
- lambda2 : float
The regularization parameter.
- method : “MNE” | “dSPM” | “sLORETA” | “eLORETA”
Use minimum norm, dSPM (default), sLORETA, or eLORETA.
- fmin : float
The lower frequency of interest.
- fmax : float
The upper frequency of interest.
- 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.
- label : Label
Restricts the source estimates to a given label.
- nave : int
The number of averages used to scale the noise covariance matrix.
- pca : bool
If True, the true dimension of data is estimated before running
the time-frequency transforms. It reduces the computation times
e.g. with a dataset that was maxfiltered (true dim is 64).
- inv_split : int or None
Split inverse operator into inv_split parts in order to save memory.
- bandwidth : float | str
The bandwidth of the multi taper windowing function in Hz.
Can also be a string (e.g., ‘hann’) to use a single window.
- adaptive : bool
Use adaptive weights to combine the tapered spectra into PSD
(slow, use n_jobs >> 1 to speed up computation).
- low_bias : bool
Only use tapers with more than 90% spectral concentration within
bandwidth.
- 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.
- n_jobs : int
Number of parallel jobs to use (only used if adaptive=True).
- prepared : bool
If True, do not call prepare_inverse_operator().
- method_params : dict | None
Additional options for eLORETA. See Notes of apply_inverse().
- return_sensor : bool
If True, also return the sensor PSD for each epoch as an EvokedArray.
- verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose()
and Logging documentation for more).
