Abstract
In recent years, significant progress has been made in the area of electroencephalography (EEG) source imaging. Source localization on simple spherical models has become increasingly efficient, with consistently reported accuracy of within 5 mm. In contrast, source localization on realistic head models remains slow, with subcentimeter accuracy being the exception rather than the norm. A primary reason for this discrepancy is that most source imaging techniques are based on lead fields. While the lead field for simplified geometries can be easily computed analytically, an efficient method for computing realistic domain lead fields has, until now, remained elusive. In this paper, we propose two efficient methods for computing realistic EEG lead-field bases: the first is element oriented and the second is node oriented. We compare these two bases, discuss how they can be used to apply recent source imaging methods to realistic models, and report timings for constructing the bases. © 2000 Biomedical Engineering Society.
PAC00: 8719Nn, 8780Tq
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
REFERENCES
Burger, H. C., and J. B. van Milaan. Heart-vector and leads. Part I-Br. Heart J. 8: 157–161, 1946, Part II-Br. Heart J. 9: 154–160, 1947, Part III-Br. Heart J. 10: 229–233, 1948.
Gerson, J., V. A. Cardenas, and G. Fein. Equivalent dipole parameter estimation using simulated annealing. Electroencephalogr. Clin. Neurophysiol.92: 161–168, 1994.
Gorodnitsky, I. F., J. S. George, and B. D. Rao. Neuromagnetic source imaging with FOCUSS: A recursive weighted minimum norm algorithm. Electroencephalogr. Clin. Neurophysiol.95: 231–251, 1995.
Helmholtz, H. Uber einige gesetz der vertheilung elektrischer strome in korperlichen leitern, mit anwendung auf die thierischelektrischen versuche. Ann. Phys. Chem.29: 211–233, 1853; 29: 353–377, 1853.
Jin, J. The Finite Element Method in Electromagnetics. New York: Wiley, 1993.
Johnson, C. R. Numerical methods for bioelectric field problems. In The Biomedical Engineering Handbook, edited by J. D. Bronzino. Boca Raton: CRC Press, 1995, pp. 162–180.
Johnson, C. R. Computational and numerical methods for bioelectric field problems. Crit. Rev. Biomed. Eng.25(1): 1–81, 1997.
Khosla, D., M. Singh, and M. Don. Spatio-temporal EEG source localization using simulated annealing. IEEE Trans. Biomed. Eng.44(11): 1075–1091, 1997.
Krysl, P., and M. Oritz. Variational delaunay approach to the generation of tetrahedral finite element meshes. Int. J. Numer. Methods Eng.(in press).
McFee, R., and F. D. Johnston. Electrocardiographic leads. I Circulation8: 554–568, 1953, II-Circulation 9: 255–266, 1954, III-Circulation 9: 868–880, 1954.
Metropolis, N., A. Rosenbluth, R. Rosenbluth, A. Teller, and E. Teller. Equation of state calculations by fast computing machines. J. Chem. Phys.21: 1087–1092, 1953.
Miller, C. E., and C. S. Henriquez. Finite element analysis of bioelectric phenomena. Crit. Rev. Biomed. Eng.8: 181–205, 1990.
Mosher, J. C., R. M. Leahy, and P. S. Lewis. EEG and MEG: Forward solutions for inverse methods. IEEE Trans. Biomed. Eng.46(3): 245–259, 1999.
Mosher, J. C., P. S. Lewis, and R. M. Leahy. Multiple dipole modeling and localization from spatio-temporal MEG data. IEEE Trans. Biomed. Eng.39(6): 541–557, 1992.
Nedler, J. A., and R. Mead. A simplex method for function minimization. Comput. J. (UK) 7: 308–313, 1965.
Parker, S. G., D. M. Weinstein, and C. R. Johnson. The SCIRun computational steering software system. In Modern Software Tools in Scientific Computing. edited by E. Arge, A. M. Bruaset, and H. P. Langtangen. Boston: Birkhauser, 1997, pp. 1–40.
Pasqual-Marqui, R. D., C. M. Michel, and D. Lehmann. Low resolution electromagnetic tomography: A new method for localizing electrical activity in the brain. Int. J. Psychophysiol.18: 49–65, 1994.
Plonsey, R. Reciprocity applied to volume conductors and the ECG. IEEE Trans. Biomed. Electron.10: 9–12, 1963.
Rush, S., and D. A. Driscoll. Eeg electrode sensitivity—an application of reciprocity. IEEE Trans. Biomed. Eng.16: 15–22, 1969.
Wells, W. M., W. E. L. Grimson, R. Kikinis, and F. A. Jolesz. Statistical intensity correction and segmentation of MRI data. In Visualization in Biomedical Computing. Bellingham: SPIE, 1994, pp. 13–24.
Yan, Y., P. L. Nunez, and R. T. Hart. Finite-element model of the human head: Scalp potentials due to dipole sources. Med. Biol. Eng. Comput.29: 475–481, 1991.
Zhukov, L., D. Weinstein, and C. Johnson. Independent component analysis for EEG source localization. IEEE Eng. Med. Biol. Mag.19: 87–96, 2000.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Weinstein, D., Zhukov, L. & Johnson, C. Lead-field Bases for Electroencephalography Source Imaging. Annals of Biomedical Engineering 28, 1059–1065 (2000). https://doi.org/10.1114/1.1310220
Issue Date:
DOI: https://doi.org/10.1114/1.1310220