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=None, prepared=False, method_params=None, return_sensor=False, use_cps=True, verbose=None)[source]#

Compute source power spectral density (PSD) from Epochs.

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

epochsinstance of Epochs

The raw data.

inverse_operatorinstance of InverseOperator

The inverse operator.


The regularization parameter.

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

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


The lower frequency of interest.


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.


Restricts the source estimates to a given label.


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


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.


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


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


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

n_jobsint | None

The number of jobs to run in parallel. If -1, it is set to the number of CPU cores. Requires the joblib package. None (default) is a marker for ‘unset’ that will be interpreted as n_jobs=1 (sequential execution) unless the call is performed under a joblib.parallel_config context manager that sets another value for n_jobs. It is only used if adaptive=True.


If True, do not call prepare_inverse_operator().

method_paramsdict | None

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

New in v0.16.


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

New in v0.17.


Whether to use cortical patch statistics to define normal orientations for surfaces (default True).

Only used when the inverse is free orientation (loose=1.), not in surface orientation, and pick_ori='normal'.

New in v0.20.

verbosebool | str | int | None

Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

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#

Compute Power Spectral Density of inverse solution from single epochs

Compute Power Spectral Density of inverse solution from single epochs