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Modeling and Imaging of Bioelectrical Activity pp 213–250Cite as

Neuromagnetic Source Reconstruction and Inverse Modeling

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Part of the book series: Bioelectric Engineering ((BEEG))

Abstract

The human brain has approximately 1010 neurons in its cerebral cortex. Their electrophysiological activity generates weak but measurable magnetic fields outside the scalp. Magnetoencephalography (MEG) is a method which measures these neuromagnetic fields to obtain information about these neural activities (Hämäläinen et al., 1993; Roberts et al., 1998; Lewine et al., 1995). Among the various kinds of functional neuroimaging methods, such a neuro-electromagnetic approach has a major advantage in that it can provide fine time resolution of millisecond order. Therefore, the goal of neuromagnetic imaging is to visualize neural activities with such fine time resolution and to provide functional information about brain dynamics. To attain this goal, one technical hurdle must be overcome. That is, an efficient method to reconstruct the spatio-temporal neural activities from neuromagnetic measurements needs to be developed. Toward this goal, a number of algorithms for reconstructing spatio-temporal source activities have been investigated (Baillet et al., 2001).

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References

  • Adachi, Y., Shimogawara, M., Higuchi, M., Haruta, Y., and Ochiai, M., 2001, Reduction of non-periodical extramural magnetic noise in MEG measurement by continuously adjusted least squares method, in Proceedings of 12th International Conferences on Biomagnetism, (R. Hari et al., eds.), Helsinki University of Technology, pp. 899–902.

    Google Scholar 

  • A. M. Dale, A. M., Liu, A. K., Fischl, B. R., Buckner, R. L., Belliveau, J. W., Lewine, J. D., and Halgren, E., 2000, Dynamic statistical parametric mapping: Combining fMRI and MEG for high-resolution imaging of cortical activity, Neuron, 26, pp. 55–67.

    Article  Google Scholar 

  • Baillet S. and Garnero, L., 1997, A Bayesian approach to introducing anatomo-functional priors in the EEG/MEG inverse problem, IEEE Trans. Biomed. Eng., 44, pp. 374–385.

    Article  Google Scholar 

  • Baillet, S., Mosher, J. C., and Leahy, R. M., 2001, Electromagnetic brain mapping, IEEE Signal Processing Magazine, 18, pp. 14–30.

    Article  Google Scholar 

  • Barnard, A., Duck, I., Lynn, M., and Timlake, W., 1967, The application of electromagnetic theory to electrocardiography II. Numerical solution of the integral equations, Biophys. J., 7, pp. 433–462.

    Google Scholar 

  • Borgiotti G. and Kaplan, L. J., 1979, Superresolution of uncorrelated interference sources by using adaptive array technique, IEEE Trans. Antenn. and Propagat., 27, pp. 842–845.

    Article  Google Scholar 

  • Bradley, C. P., Harris, G. M., and Pillan, A. J., 2001, The computational performance of a high-order coupled FEM/BEM procedure in electropotential problems, IEEE Trans. Biomed. Eng., 48, pp. 1238–1250.

    Article  Google Scholar 

  • Carlson, B. D., 1988, Covariance matrix estimation errors and diagonal loading in adaptive arrays, IEEE Trans. Aerospace and Electronic Systems, 24, pp. 397–401.

    Article  Google Scholar 

  • Chang, L. and Yeh, C. C., 1992, Performance of DMI and eigenspace-based beamformers, IEEE Trans. Antenn. Propagat., 40, pp. 1336–1347.

    Article  Google Scholar 

  • Chang, L. and Yeh, C. C., 1993, Effect of pointing errors on the performance of the projection beamformer, IEEE Trans. Antenn. Propagat., 41, pp. 1045–1056.

    Article  Google Scholar 

  • Clarke, J., 1994, SQUIDs, Scientific American, 271, pp. 36–43.

    Article  Google Scholar 

  • Cox, H., Zeskind, R. M., and Owen, M. M., 1987, Robust adaptive beamforming, IEEE Trans. Signal Process., 35, pp. 1365–1376.

    Article  Google Scholar 

  • Cuffin B. N. and Cohen D., 1977, Magnetic fields of a dipole in special volume conductor shapes, IEEE Trans. Biomed. Eng., 24, pp. 372–381, 1977.

    Article  Google Scholar 

  • Cuffin B. N., 1991, Eccentric spheres models of the head, IEEE Trans. Biomed. Eng., 38, pp. 871–878.

    Article  Google Scholar 

  • Cuffin, B. N., 1996, EEG localization accuracy improvements using realistically shaped head models, IEEE Trans. Biomed. Eng., 43, pp. 299–303, 1996.

    Article  Google Scholar 

  • de Peralta Menendez, R. G., Gonzalez Andino, S., and Lütkenhöner, B., 1996, Figures of merit to compare distributed linear inverse solutions, Brain Topography, 9, pp. 117–124, 1996.

    Article  Google Scholar 

  • de Peralta Menendez, R. G., Hauk, O., Gonzalez Andino, S., Vogt, H., and Michel, C., 1997, Linear inverse solutions with optimal resolution kernels applied to electromagnetic tomography, Human Brain Mapping, 5, pp. 454–467, 1997.

    Article  Google Scholar 

  • Drung, D., Cantor, R., Peters, M., Ryhänen, P., and Koch, H., 1991, Integrated DC SQUID magnetometer with high dv/db, IEEE Trans. Magn., 27, pp. 3001–3004.

    Article  Google Scholar 

  • Feldman, D. D. and Griffiths, L. J., 1991, A constrained projection approach for robust adaptive beamforming, in Proc. Int. Conf. Acoust., Speech, Signal Process., Toronto, May, pp. 1357–1360.

    Google Scholar 

  • Frost, O. T., 1972, An algorithm for linearly constrained adaptive array processing, Proc. IEEE, 60, pp. 926–935.

    Article  Google Scholar 

  • Fuchs, M., Drenckhahn, R., Wischmann, H.-A., and Wagner, M., 1998, An improved boundary element method for realistic volume-conductor modeling, IEEE Trans. Biomed. Eng., 45, pp. 980–997.

    Article  Google Scholar 

  • Geselowitz, D. B., 1970, On the magnetic field generated outside an inhomogeneous volume conductor by internal current sources, IEEE Trans. Biomed. Eng., 2, pp. 346–347.

    Google Scholar 

  • Graumann, R., 1991, The reconstruction of current densities, Tech. Rep. TKK-F-A689, Helsinki University of Technology.

    Google Scholar 

  • Gross J. and Ioannides, A. A., 1999, Linear transformations of data space in MEG, Phys. Med. Biol., 44, pp. 2081–2097.

    Article  Google Scholar 

  • Gross, J., Kujara, J., Hämäläinen, M. S., Timmermann, L., Schnitzler, A., and R. Salmelin, 2001, Dynamic imaging of coherent sources: Studying neural interactions in the human brain, Proceedings of National Academy of Science, 98, pp. 694–699.

    Article  Google Scholar 

  • Hämäläinen, M. S. and Ilmoniemi, R. J., 1984, Interpreting measured magnetic fields of the brain: Estimates of current distributions, Tech. Rep. TKK-F-A559, Helsinki University of Technology.

    Google Scholar 

  • Hämäläinen, M. S. and Sarvas, J., 1989, Realistic conductivity geometry model of the human head for interpretation of neuromagnetic data, IEEE Trans. Biomed. Eng., 36, pp. 165–171.

    Article  Google Scholar 

  • Hämäläinen, M. S., Hari, R., Ilmoniemi, R. J., Knuutila, J., and Lounasmaa, O. V., 1993, Magnetoencephalographytheory, instrumentation, and applications to noninvasive studies of the working human brain, Rev. Mod. Phys., 65, pp. 413–497.

    Article  Google Scholar 

  • Hämäläinen, M. S. and Ilmoniemi, R. J., 1994, Interpreting magnetic fields of the brain: minimum norm estimates, Med. & Biol. Eng. & Comput., 32, pp. 35–42.

    Article  Google Scholar 

  • Hashimoto, I., Sakuma, K., Kimura, T., Iguchi, Y., and Sekihara, K., 2001a, Serial activation of distinct cytoarchitectonic areas of the human SI cortex after posterior tibial nerve stimulation, Neuro Report, 12, pp. 1857–1862.

    Google Scholar 

  • Hashimoto, I., Kimura, T., Iguchi, Y., Takino, R., and K. Sekihara, 2001b, Dynamic activation of distinct cytoarchitectonic areas of the human SI cortex after median nerve stimulation, Neuro Report, 12, pp. 1891–1897.

    Google Scholar 

  • Herman, G. T., 1980, Image Reconstruction from projections, Academic Press, New York, USA.

    MATH  Google Scholar 

  • J. D. Lewine J. D. and Orrison Jr., W. W., 1995, Magnetoencephalography and magnetic source imaging, in Functional Brain Imaging, (W. W. Orrison Jr. et al., eds.), pp. 369–417. Mosby-Year Book, Inc.

    Google Scholar 

  • Liu, A. K., Belliveau, J. W., and Dale, A. M., 1998, Spatiotemporal imaging of human brain activity using functional MRI constrained magnetoencephalography data: Monte Carlo simulations, Proc. Natl. Acad. Sci., 95, pp. 8945–8950.

    Article  Google Scholar 

  • Lütkenhöner, B. and de Peralta Menendez, R. G., 1997, The resolution field concept, Electroenceph. Clin. Neurophysiol., 102, pp. 326–334.

    Article  Google Scholar 

  • Mosher, J. C., Lewis, P. S., and Leahy, R. M., 1992, Multiple dipole modeling and localization from spatio-temporal MEG data, IEEE Trans. Biomed. Eng., 39, pp. 541–557.

    Article  Google Scholar 

  • Okada, Y., Lauritzen, M., and Nicholson, C., 1987, MEG source models and physiology, Phys. Med. Biol, 32, pp. 43–51.

    Article  Google Scholar 

  • Parkkonen, L. T., Simola, J. T., Tuoriniemi, J. T., and Ahonen, A. I., 1999, An interference suppression system for multichannel magnetic field detector arrays, in Recent Advances in Biomagnetism, (T. Yoshimoto et al., eds.), Tohoku University Press, Sendai, pp. 13–16.

    Google Scholar 

  • Pascual-Marqui, R. D. and Michel, C. M., 1994, Low resolution electromagnetic tomography: A new method for localizing electrical activity in the brain, Int. J. Psychophysiol., 18, pp. 49–65.

    Article  Google Scholar 

  • Paulraj, A., Ottersten, B., Roy, R., Swindlehurst, A., Xu, G., and Kailath, T., 1993, Subspace methods for directions-of-arrival estimation, in Handbook of Statistics, (N. K. Bose and C. R. Rao, eds.), Elsevier Science Publishers, Netherlands, pp. 693–739.

    Google Scholar 

  • Roberts, T. P. L., Poeppel, D., and Rowley, H. A., 1998, Magnetoencephalography and magnetic source imaging, Neuropsychiatry, Neuropsychology, and Behavioral Neurology, 11, pp. 49–64.

    Google Scholar 

  • Robinson, S. E. and Vrba, J., 1999, Functional neuroimaging by synthetic aperture magnetometry (SAM), in Recent Advances in Biomagnetism, (T. Yoshimoto et al., eds.), Tohoku University Press, Sendai, pp. 302–305.

    Google Scholar 

  • Sarvas, J., 1987, Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem, Phys. Med. Biol., 32, pp. 11–22.

    Article  Google Scholar 

  • Scharf, L. L., 1991, Statistical Signal Processing: detection, estimation, and time series analysis, Addison-Wesley Publishing Company, New York.

    MATH  Google Scholar 

  • Schmidt, D. M., George, J. S., and Wood, C. C., 1999, Bayesian inference applied to the electromagnetic inverse problem, Human Brain Mapping, 7, pp. 195–212.

    Article  Google Scholar 

  • Schmidt, R. O., 1981, A signal subspace approach to multiple emitter location and spectral estimation, PhD thesis, Stanford University, Stanford, CA.

    Google Scholar 

  • Schmidt, R. O., 1986, Multiple emitter location and signal parameter estimation, IEEE Trans. Antenn. Propagat., 34, pp. 276–280.

    Article  Google Scholar 

  • Sekihara, K., Poeppel, D., Marantz, A., and Miyashita, Y., 2000, Neuromagnetic inverse modeling: applications of eigenstructure-based approaches to extracting cortical activities from MEG data, in Image, Language, Brain, (Alec Marantz et al., eds.), The MIT Press, Cambridge, pp. 197–231.

    Google Scholar 

  • Sekihara, K. and Scholz, B., 1996, Generalized Wiener estimation of three-dimensional current distribution from biomagnetic measurements, in Biomag 96: Proceedings of the Tenth International Conference on Biomagnetism, (C. J. Aine et al., eds.), Springer-Verlag, New York, pp. 338–341.

    Google Scholar 

  • Sekihara, K., Nagarajan, S. S., Poeppel, D., Marantz, A., and Miyashita, Y., 2001, Reconstructing spatio-temporal activities of neural sources using an MEG vector beamformer technique, IEEE Trans. Biomed. Eng., 48, pp. 760–771.

    Article  Google Scholar 

  • Spencer, M. E., Leahy, R. M., Mosher, J. C., and Lewis, P. S., 1992, Adaptive filters for monitoring localized brain activity from surface potential time series, in Conference Record for 26th Annual Asilomer Conference on Signals, Systems, and Computers, November, pp. 156–161.

    Google Scholar 

  • van Drongelen, W., Yuchtman, M., van Veen, B. D., and van Huffelen, A. C., 1996, A spatial filtering technique to detect and localize multiple sources in the brain, Brain Topography, 9, pp. 39–49.

    Article  Google Scholar 

  • van Veen, B. D. and Buckley, K. M., 1988, Beamforming: A versatile approach to spatial filtering, IEEE ASSP Magazine, 5, pp. 4–24, April.

    Article  Google Scholar 

  • van Veen, B. D., 1988, Eigenstructure based partially adaptive array design, IEEE Trans. Antenn. Propagat., 36, pp. 357–362.

    Article  Google Scholar 

  • van Veen, B. D., van Drongelen, W., Yuchtman, W. and Suzuki, A., 1997, Localization of brain electrical activity via linearly constrained minimum variance spatial filtering, IEEE Trans. Biomed. Eng., 44, pp. 867–880.

    Article  Google Scholar 

  • van’t Ent, D., de Munck, J. C., and Kaas, A. L., 2001, A fast method to derive realistic BEM models for E/MEG source reconstruction, IEEE Trans. Biomed. Eng., 48, pp. 1434–1443.

    Article  Google Scholar 

  • Vrba, J. and Robinson, S., 2001, The effect of environmental noise on magnetometer-and gardiometer-based MEG systems, in Proceedings of 12th International Conferences on Biomagnetism, (R. Hari et al., eds.), Helsinki University of Technology, pp. 953–956.

    Google Scholar 

  • Wagner, M., Fuchs, M., Wischmann, H.-A., Drenckharn, R., and Köhler, T., 1996, Smooth reconstruction of cortical sources from EEG or MEG recordings, NeuroImage, 3, pp. S168.

    Article  Google Scholar 

  • Wang, J. Z., Williamson, S. J., and Kaufman, L., 1992, Magnetic source images determined by a lead-field analysis: The unique minimum-norm least-squares estimation, IEEE Trans. Biomed. Eng., 39, pp. 565–575.

    Article  Google Scholar 

  • Yu, J. L. and Yeh, C. C., 1995, Generalized eigenspace-based beamformers, IEEE Trans. Signal Process., 43, pp. 2453–2461.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electronic Systems and Engineering, Tokyo Metropolitan Institute of Technology, Asahigaoka 6-6, Hino, Tokyo, 191-0065, Japan

    Kensuke Sekihara Ph.D.

  2. Department of Radiology, University of California, San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA, 94143, USA

    Srikantan S. Nagarajan

Authors
  1. Kensuke Sekihara Ph.D.
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  2. Srikantan S. Nagarajan
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Editors and Affiliations

  1. University of Minnesota, Minneapolis, Minnesota

    Bin He

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© 2004 Kluwer Academic/Plenum Publishers, New York

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Sekihara, K., Nagarajan, S.S. (2004). Neuromagnetic Source Reconstruction and Inverse Modeling. In: He, B. (eds) Modeling and Imaging of Bioelectrical Activity. Bioelectric Engineering. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-49963-5_7

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  • DOI: https://doi.org/10.1007/978-0-387-49963-5_7

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-306-48112-3

  • Online ISBN: 978-0-387-49963-5

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