mne.minimum_norm.read_inverse_operator¶

mne.minimum_norm.read_inverse_operator(fname, verbose=None)[source]¶

Read the inverse operator decomposition from a FIF file.

Parameters:	fname : string The name of the FIF file, which ends with -inv.fif or -inv.fif.gz. verbose : bool, str, int, or None If not None, override default verbose level (see mne.verbose() and Logging documentation for more).
Returns:	inv : instance of InverseOperator The inverse operator.

See also

write_inverse_operator, make_inverse_operator

Examples using mne.minimum_norm.read_inverse_operator¶

Compute coherence in source space using a MNE inverse solution

Compute full spectrum source space connectivity between labels

Compute source space connectivity and visualize it using a circular graph

Compute Phase Slope Index (PSI) in source space for a visual stimulus

Decoding source space data

Compute MNE-dSPM inverse solution on single epochs

Compute sLORETA inverse solution on raw data

Compute MNE-dSPM inverse solution on evoked data in volume source space

Generate a functional label from source estimates

Extracting the time series of activations in a label

Compute cross-talk functions (CTFs) for labels for MNE/dSPM/sLORETA

Compute point-spread functions (PSFs) for MNE/dSPM/sLORETA

Reading an inverse operator

Plot an estimate of data SNR

Compute Power Spectral Density of inverse solution from single epochs

Compute power and phase lock in label of the source space

Compute power spectrum densities of the sources with dSPM

Compute induced power in the source space with dSPM

Basic MEG and EEG data processing

Corrupt known signal with point spread

Permutation t-test on source data with spatio-temporal clustering

Repeated measures ANOVA on source data with spatio-temporal clustering