Inverse Solutions

mne.minimum_norm:

Linear inverse solvers based on L2 Minimum Norm Estimates (MNE).

InverseOperator

InverseOperator class to represent info from inverse operator.

apply_inverse(evoked, inverse_operator[, …])

Apply inverse operator to evoked data.

apply_inverse_cov(cov, info, inverse_operator)

Apply inverse operator to covariance data.

apply_inverse_epochs(epochs, …[, method, …])

Apply inverse operator to Epochs.

apply_inverse_raw(raw, inverse_operator, lambda2)

Apply inverse operator to Raw data.

compute_source_psd(raw, inverse_operator[, …])

Compute source power spectral density (PSD).

compute_source_psd_epochs(epochs, …[, …])

Compute source power spectral density (PSD) from Epochs.

compute_rank_inverse(inv)

Compute the rank of a linear inverse operator (MNE, dSPM, etc.).

estimate_snr(evoked, inv[, verbose])

Estimate the SNR as a function of time for evoked data.

make_inverse_operator(info, forward, noise_cov)

Assemble inverse operator.

prepare_inverse_operator(orig, nave, lambda2)

Prepare an inverse operator for actually computing the inverse.

read_inverse_operator(fname[, verbose])

Read the inverse operator decomposition from a FIF file.

source_band_induced_power(epochs, …[, …])

Compute source space induced power in given frequency bands.

source_induced_power(epochs, …[, label, …])

Compute induced power and phase lock.

write_inverse_operator(fname, inv[, verbose])

Write an inverse operator to a FIF file.

make_inverse_resolution_matrix(forward, …)

Compute resolution matrix for linear inverse operator.

resolution_metrics(resmat, src[, function, …])

Compute spatial resolution metrics for linear solvers.

get_cross_talk(resmat, src, idx[, mode, …])

Get cross-talk (CTFs) function for vertices.

get_point_spread(resmat, src, idx[, mode, …])

Get point-spread (PSFs) functions for vertices.

mne.inverse_sparse:

Non-Linear sparse inverse solvers.

mixed_norm(evoked, forward, noise_cov, alpha)

Mixed-norm estimate (MxNE) and iterative reweighted MxNE (irMxNE).

tf_mixed_norm(evoked, forward, noise_cov[, …])

Time-Frequency Mixed-norm estimate (TF-MxNE).

gamma_map(evoked, forward, noise_cov, alpha)

Hierarchical Bayes (Gamma-MAP) sparse source localization method.

make_stc_from_dipoles(dipoles, src[, verbose])

Convert a list of spatio-temporal dipoles into a SourceEstimate.

mne.beamformer:

Beamformers for source localization.

Beamformer

A computed beamformer.

read_beamformer(fname)

Read a beamformer filter.

make_lcmv(info, forward, data_cov[, reg, …])

Compute LCMV spatial filter.

apply_lcmv(evoked, filters[, max_ori_out, …])

Apply Linearly Constrained Minimum Variance (LCMV) beamformer weights.

apply_lcmv_epochs(epochs, filters[, …])

Apply Linearly Constrained Minimum Variance (LCMV) beamformer weights.

apply_lcmv_raw(raw, filters[, start, stop, …])

Apply Linearly Constrained Minimum Variance (LCMV) beamformer weights.

apply_lcmv_cov(data_cov, filters[, verbose])

Apply Linearly Constrained Minimum Variance (LCMV) beamformer weights.

make_dics(info, forward, csd[, reg, …])

Compute a Dynamic Imaging of Coherent Sources (DICS) spatial filter.

apply_dics(evoked, filters[, verbose])

Apply Dynamic Imaging of Coherent Sources (DICS) beamformer weights.

apply_dics_csd(csd, filters[, verbose])

Apply Dynamic Imaging of Coherent Sources (DICS) beamformer weights.

apply_dics_epochs(epochs, filters[, …])

Apply Dynamic Imaging of Coherent Sources (DICS) beamformer weights.

rap_music(evoked, forward, noise_cov[, …])

RAP-MUSIC source localization method.

make_lcmv_resolution_matrix(filters, …)

Compute resolution matrix for LCMV beamformer.

Dipole(times, pos, amplitude, ori, gof[, …])

Dipole class for sequential dipole fits.

DipoleFixed(info, data, times, nave, aspect_kind)

Dipole class for fixed-position dipole fits.

fit_dipole(evoked, cov, bem[, trans, …])

Fit a dipole.

mne.dipole:

Single-dipole functions and classes.

get_phantom_dipoles([kind])

Get standard phantom dipole locations and orientations.