mne.minimum_norm.compute_source_psd_epochs

mne.minimum_norm.compute_source_psd_epochs(epochs, inverse_operator, lambda2=0.1111111111111111, method='dSPM', fmin=0.0, fmax=200.0, pick_ori=None, label=None, nave=1, pca=True, inv_split=None, bandwidth=4.0, adaptive=False, low_bias=True, return_generator=False, n_jobs=1, prepared=False, method_params=None, return_sensor=False, verbose=None)[source]

Compute source power spectrum density (PSD) from Epochs.

This uses the multi-taper method to compute the PSD for each epoch.

Parameters
epochsinstance of Epochs

The raw data.

inverse_operatorinstance of InverseOperator

The inverse operator.

lambda2float

The regularization parameter.

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

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

fminfloat

The lower frequency of interest.

fmaxfloat

The upper frequency of interest.

pick_oriNone | “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.

labelLabel

Restricts the source estimates to a given label.

naveint

The number of averages used to scale the noise covariance matrix.

pcabool

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_splitint or None

Split inverse operator into inv_split parts in order to save memory.

bandwidthfloat | str

The bandwidth of the multi taper windowing function in Hz. Can also be a string (e.g., ‘hann’) to use a single window.

adaptivebool

Use adaptive weights to combine the tapered spectra into PSD (slow, use n_jobs >> 1 to speed up computation).

low_biasbool

Only use tapers with more than 90% spectral concentration within bandwidth.

return_generatorbool

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

n_jobsint

Number of parallel jobs to use (only used if adaptive=True).

preparedbool

If True, do not call prepare_inverse_operator().

method_paramsdict | None

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

New in version 0.16.

return_sensorbool

If True, also return the sensor PSD for each epoch as an EvokedArray.

New in version 0.17.

verbosebool, str, int, or None

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

Returns
outlist (or generator object)

A list (or generator) for the source space PSD (and optionally the sensor PSD) for each epoch.

Examples using mne.minimum_norm.compute_source_psd_epochs