InvMinimumNorm

Namespace: INVERSELIB  ·  Library: Inverse Library

Python equivalent

mne.minimum_norm.apply_inverse in MNE-Python.

#include <inv/inv_minimum_norm.h>

class INVLIB::InvMinimumNorm

Minimum norm estimation algorithm.

Computes L2 minimum-norm, dSPM, or sLORETA source estimates from MEG/EEG data using a pre-computed inverse operator.

References: Hamalainen & Ilmoniemi, Med. & Biol. Eng. & Comput. 32, 35-42, 1994.

Dale et al., Neuron 26, 55-67, 2000 (dSPM).

Pascual-Marqui, Methods Find. Exp. Clin. Pharmacol. 24D, 5-12, 2002 (sLORETA).

Minimum norm estimation

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Public Methods

InvMinimumNorm(p_inverseOperator, lambda, method)

Constructs minimum norm inverse algorithm.

Parameters:

• p_inverseOperator : const MNEInverseOperator & The inverse operator.

• lambda : float The regularization factor.

• method : const QString Use mininum norm, dSPM or sLORETA. ("MNE" | "dSPM" | "sLORETA").

Returns:

• the prepared inverse operator.

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InvMinimumNorm(p_inverseOperator, lambda, dSPM, sLORETA)

Constructs minimum norm inverse algorithm.

Parameters:

• p_inverseOperator : const MNEInverseOperator & The inverse operator.

• lambda : float The regularization factor.

• dSPM : bool Compute the noise-normalization factors for dSPM?.

• sLORETA : bool Compute the noise-normalization factors for sLORETA?.

Returns:

• the prepared inverse operator.

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~InvMinimumNorm()

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calculateInverse(p_fiffEvoked, pick_normal)

Computes a L2-norm inverse solution Actual code using these principles might be different because the inverse operator is often reused across data sets.

Parameters:

• p_fiffEvoked : const FiffEvoked & Evoked data.

• pick_normal : bool If True, rather than pooling the orientations by taking the norm, only the. radial component is kept. This is only applied when working with loose orientations.

Returns:

• InvSourceEstimate — the calculated source estimation.

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calculateInverse(data, tmin, tstep, pick_normal)

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doInverseSetup(nave, pick_normal)

Perform the inverse setup: Prepares this inverse operator and assembles the kernel.

Parameters:

• nave : qint32 Number of averages to use.

• pick_normal : bool If True, rather than pooling the orientations by taking the norm, only the. radial component is kept. This is only applied when working with loose orientations.

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getName()

Get the name of the inverse operator.

Returns:

• *const char ** — the name of the inverse operator.

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getSourceSpace()

Get the source space corresponding to this inverse operator.

Returns:

• const MNESourceSpaces & — the source space corresponding to this inverse operator.

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getPreparedInverseOperator()

Get the prepared inverse operator.

Returns:

• MNEInverseOperator & — the prepared inverse operator.

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setMethod(method)

Set minimum norm algorithm method ("MNE" | "dSPM" | "sLORETA" | "eLORETA").

Parameters:

• method : QString Use minimum norm, dSPM, sLORETA, or eLORETA.

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setMethod(dSPM, sLORETA, eLoreta)

Set minimum norm algorithm method ("MNE" | "dSPM" | "sLORETA" | "eLORETA").

Parameters:

• dSPM : bool Compute the noise-normalization factors for dSPM?.

• sLORETA : bool Compute the noise-normalization factors for sLORETA?.

• eLoreta : bool Compute the eLORETA source weights?.

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setRegularization(lambda)

Set regularization factor.

Parameters:

• lambda : float The regularization factor.

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setELoretaOptions(maxIter, eps, forceEqual)

Set eLORETA options.

Parameters:

• maxIter : int Maximum number of eLORETA weight iterations (default: 20).

• eps : double Convergence threshold for weight fitting (default: 1e-6).

• forceEqual : bool If true, use uniform orientation weights (default: false).

---

getKernel()

Get the assembled kernel.

Returns:

• Eigen::MatrixXd & — the assembled kernel.

---

Example

Source: src/examples/ex_inverse_mne/main.cpp

#include <iostream>
#include <vector>
#include <math.h>

//=============================================================================================================
// MNE INCLUDES
//=============================================================================================================

#include <fiff/fiff_evoked_set.h>
#include <mne/mne_inverse_operator.h>

#include <fiff/fiff_evoked.h>
#include <inv/inv_source_estimate.h>
#include <inv/minimum_norm/inv_minimum_norm.h>

#include <utils/generics/mne_logger.h>

//=============================================================================================================
// QT INCLUDES
//=============================================================================================================

#include <QtCore/QCoreApplication>
#include <QCommandLineParser>
#include <QFile>

//=============================================================================================================
// USED NAMESPACES
//=============================================================================================================

using namespace FIFFLIB;
using namespace MNELIB;
using namespace INVLIB;
using namespace UTILSLIB;

//=============================================================================================================
// MAIN
//=============================================================================================================

//=============================================================================================================
/**
 * The function main marks the entry point of the program.
 * By default, main has the storage class extern.
 *
 * @param[in] argc (argument count) is an integer that indicates how many arguments were entered on the command line when the program was started.
 * @param[in] argv (argument vector) is an array of pointers to arrays of character objects. The array objects are null-terminated strings, representing the arguments that were entered on the command line when the program was started.
 * @return the value that was set to exit() (which is 0 if exit() is called via quit()).
 */
int main(int argc, char *argv[])
{
    qInstallMessageHandler(MNELogger::customLogWriter);
    QCoreApplication app(argc, argv);

    // Command Line Parser
    QCommandLineParser parser;
    parser.setApplicationDescription("Inverse MNE Example");
    parser.addHelpOption();

    QCommandLineOption evokedFileOption("ave", "Path to evoked <file>.", "file", QCoreApplication::applicationDirPath() + "/../resources/data/MNE-sample-data/MEG/sample/sample_audvis-ave.fif");
    QCommandLineOption invFileOption("inv", "Path to inverse operator <file>.", "file", QCoreApplication::applicationDirPath() + "/../resources/data/MNE-sample-data/MEG/sample/sample_audvis-meg-eeg-oct-6-meg-eeg-inv.fif");
    QCommandLineOption snrOption("snr", "The <snr> value used for computation.", "snr", "1.0");
    QCommandLineOption methodOption("method", "Inverse estimation <method>, i.e., 'MNE', 'dSPM' or 'sLORETA'.", "method", "dSPM");
    QCommandLineOption stcFileOption("stcOut", "Path to stc <file>, which is to be written.", "file", "");

    parser.addOption(evokedFileOption);
    parser.addOption(invFileOption);
    parser.addOption(snrOption);
    parser.addOption(methodOption);
    parser.addOption(stcFileOption);
    parser.process(app);

    QFile t_fileEvoked(parser.value(evokedFileOption));
    QFile t_fileInv(parser.value(invFileOption));

    float snr = parser.value(snrOption).toFloat();
    QString method(parser.value(methodOption));
    QString t_sFileNameStc(parser.value(stcFileOption));

    double lambda2 = 1.0 / pow(snr, 2);
    qDebug() << "Start calculation with: SNR" << snr << "; Lambda" << lambda2 << "; Method" << method << "; stc:" << t_sFileNameStc;

    //
    //   Read the data first
    //
    fiff_int_t setno = 0;
    QPair<float, float> baseline(-1.0f, -1.0f);
    FiffEvoked evoked(t_fileEvoked, setno, baseline);
    if(evoked.isEmpty())
        return 1;

    //
    //   Then the inverse operator
    //
    MNEInverseOperator inverse_operator(t_fileInv);

    //
    // Compute inverse solution
    //
    InvMinimumNorm minimumNorm(inverse_operator, lambda2, method);
    InvSourceEstimate sourceEstimate = minimumNorm.calculateInverse(evoked);

    //
    //Results
    //
    std::cout << "\npart ( block( 0, 0, 10, 10) ) of the inverse solution:\n" << sourceEstimate.data.block(0,0,10,10) << std::endl;
    printf("tmin = %f s\n", sourceEstimate.tmin);
    printf("tstep = %f s\n", sourceEstimate.tstep);

    if(!t_sFileNameStc.isEmpty())
    {
        QFile t_fileStc(t_sFileNameStc);
        sourceEstimate.write(t_fileStc);

        //test if everything was written correctly
        InvSourceEstimate readSourceEstimate(t_fileStc);

        std::cout << "\npart ( block( 0, 0, 10, 10) ) of the inverse solution:\n" << readSourceEstimate.data.block(0,0,10,10) << std::endl;
        printf("tmin = %f s\n", readSourceEstimate.tmin);
        printf("tstep = %f s\n", readSourceEstimate.tstep);
    }

    return 0;//app.exec();
}

Authors of this file

• Christoph Dinh <christoph.dinh@mne-cpp.org>