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, 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.
- Parameters
- epochsinstance of
Epochs The raw data.
- inverse_operatorinstance 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.
- 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_split
intorNone 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.
- 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_jobs
int The number of jobs to run in parallel (default
1). If-1, it is set to the number of CPU cores. Requires thejoblibpackage. It is only used if adaptive=True.- preparedbool
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.
- return_sensorbool
If True, also return the sensor PSD for each epoch as an EvokedArray.
New in version 0.17.
- use_cpsbool
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, andpick_ori='normal'.New in version 0.20.
- verbosebool |
str|int|None Control verbosity of the logging output. If
None, use the default verbosity level. See the logging documentation andmne.verbose()for details. Should only be passed as a keyword argument.
- epochsinstance of
- Returns
See also
Examples using mne.minimum_norm.compute_source_psd_epochs#
Compute Power Spectral Density of inverse solution from single epochs