inv_lcmv.h File Reference

Linearly Constrained Minimum Variance (LCMV) beamformer — time-domain source-power and source-time-course estimation. More...

#include "../inv_global.h"
#include "../inv_source_estimate.h"
#include "inv_beamformer.h"
#include "inv_beamformer_settings.h"
#include <fiff/fiff_cov.h>
#include <QList>

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Classes
class	INVLIB::InvLCMV
	LCMV beamformer (time-domain). More...

Namespaces
namespace	MNELIB
	Core MNE data structures (source spaces, source estimates, hemispheres).
namespace	FIFFLIB
	FIFF file I/O, in-memory data structures and high-level readers/writers.
namespace	INVLIB
	Inverse source estimation (MNE, dSPM, sLORETA, dipole fitting).

Detailed Description

Linearly Constrained Minimum Variance (LCMV) beamformer — time-domain source-power and source-time-course estimation.

SPDX-License-Identifier: BSD-3-Clause Copyright (c) 2026 MNE-CPP Authors

Author

Christoph Dinh chris.nosp@m.toph.nosp@m..dinh.nosp@m.@mne.nosp@m.-cpp..nosp@m.org

Since

2.1.0

Date

March 2026

INVLIB::InvLCMV implements the LCMV spatial filter of Van Veen et al., IEEE TBME 44(9), 867-880 (1997): it inverts a regularised data-covariance matrix and constrains the resulting filter so that the forward field of every grid point passes through with unit gain and all other sources are suppressed in the minimum-variance sense. The class exposes makeLCMV (filter design from forward solution + data covariance), applyLCMV / applyLCMVRaw / applyLCMVEpochs (time-course projection) and applyLCMVCov (source-power map from a covariance). A makeLCMVResolutionMatrix helper feeds the resolution analysis pipeline. All normalisation conventions follow Sekihara & Nagarajan (Springer, 2008) so output matches mne-python's mne.beamformer.make_lcmv.

Definition in file inv_lcmv.h.