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Influence of Modeling Errors in the Boundary Element Analysis of EEG Forward Problems upon the Solution Accuracy

  • Kim, Do-Won (Department of Biomedical Engineering, Yonsei University) ;
  • Jung, Young-Jin (Department of Biomedical Engineering, Yonsei University) ;
  • Im, Chang-Hwan (Department of Biomedical Engineering, Yonsei University)
  • Published : 2009.02.28

Abstract

Accurate electroencephalography (EEG) forward calculation is of importance for the accurate estimation of neuronal electrical sources. Conventional studies concerning the EEG forward problems have investigated various factors influencing the forward solution accuracy, e.g. tissue conductivity values in head compartments, anisotropic conductivity distribution of a head model, tessellation patterns of boundary element models, the number of elements used for boundary/finite element method (BEM/FEM), and so on. In the present paper, we investigated the influence of modeling errors in the boundary element volume conductor models upon the accuracy of the EEG forward solutions. From our simulation results, we could confirm that accurate construction of boundary element models is one of the key factors in obtaining accurate EEG forward solutions from BEM. Among three boundaries (scalp, outer skull, and inner skull boundary), the solution errors originated from the modeling error in the scalp boundary were most significant. We found that the nonuniform error distribution on the scalp surface is closely related to the electrode configuration and the error distributions on the outer and inner skull boundaries have statistically meaningful similarity to the curvature distributions of the boundary surfaces. Our simulation results also demonstrated that the accumulation of small modeling errors could lead to considerable errors in the EEG source localization. It is expected that our finding can be a useful reference in generating boundary element head models.

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References

  1. J. C. Mosher, R. M. Leahy, and P. S. Lewis, 'EEG and MEG: Forward Solutions for Inverse Methods,' IEEE Trans. Biomed. Eng., vol. 46, pp. 245-259, 1999 https://doi.org/10.1109/10.748978
  2. M. S. Hamalainen and J. Sarvas, 'Realistic conductivity geometry model of the human head for interpretation of neuromagnetic data,' IEEE Trans. Biomed. Eng., vol. 36, pp. 165-171, 1989 https://doi.org/10.1109/10.16463
  3. D. Yao, 'Electric potential produced by a dipole in a homogeneous conducting sphere,' IEEE Trans. Biomed. Eng., vol. 47, pp. 964-966, 2000 https://doi.org/10.1109/10.846691
  4. J. C. de Munck, 'The potential distribution in a layered anisotropic spheroidal volume conductor,' J. Appl. Phys., vol. 64, pp. 464-470, 1988 https://doi.org/10.1063/1.341983
  5. B, He, T. Musha, Y. Okamoto, S. Homma, Y. Nakajima, and T. Sato, 'Electric dipole tracing in the brain by means of the boundary element method and its accuracy,' IEEE Trans. Biomed. Eng., vol. 34, pp. 406-414, 1987 https://doi.org/10.1109/TBME.1987.326056
  6. C. H. Wolters, A. Anwander, X. Tricoche, D. Weinstein, M. A. Koch, and R. S. MacLeod, 'Influence of tissue conductivity anisotropy on EEG/MEG field and return current computation in a realistic head model: A simulation and visualization study using high-resolution finite element modeling,' NeuroImage, vol. 30, pp. 813-826, 2006 https://doi.org/10.1016/j.neuroimage.2005.10.014
  7. Y. C. Zhang, S. A. Zhu, and B. He, 'A Second-Order Finite Element Algorithm for Solving the Three-Dimensional EEG Forward Problem,' Phys. Med. Biol., vol. 49, pp. 2975-2987, 2004 https://doi.org/10.1088/0031-9155/49/13/014
  8. Y. C. Zhang, L. Ding, W. van Drongelen, K. Hecox, D. Frim, and B. He, 'A Cortical Potential Imaging Study from Simultaneous Extra- and Intra-cranial Electrical Recordings by Means of the Finite Element Method,' NeuroImage, vol. 31, pp. 1513-1524, 2006 https://doi.org/10.1016/j.neuroimage.2006.02.027
  9. W. H. Lee, T. S. Kim, M. H. Cho, Y. B. Ahn, and S. Y. Lee, 'Methods and evaluations of MRI content-adaptive finite element mesh generation for bioelectromagnetic problems,' Phys. Med. Biol., vol. 51, pp. 6173-6186, 2006 https://doi.org/10.1088/0031-9155/51/23/016
  10. J. Haueisen, C. Ramon, M. Eiselt, H. Brauer, and H. Nowak, 'Influence of tissue resistivities on neuromagnetic fields and electric potentials studied with a finite element model of the head,' IEEE Trans. Biomed. Eng., vol. 44, pp. 727-735, 1997 https://doi.org/10.1109/10.605429
  11. A. S. Ferguson and G. Stroink, 'Factors Affecting the Accuracy of the Boundary Element Method in the Forward Problem - I: Calculating Surface Potentials,' IEEE Trans. Biomed. Eng., vol. 44, pp. 1139-1155, 1997 https://doi.org/10.1109/10.641342
  12. G. Huiskamp, M. Vroeijenstijn, R. van Dijk, G. Wieneke, and A. C. van Huffelen, 'The need for correct realistic geometry in the inverse EEG problem,' IEEE Trans. Biomed. Eng., vol. 46, pp. 1281-1287, 1999 https://doi.org/10.1109/10.797987
  13. B. Dogdas, D. W. Shattuck, and R. M. Leahy, 'Segmentation of skull in 3-D human MRI using mathematical morphology,' Hum. Brain Mapp., vol. 26, pp. 273-285, 2005 https://doi.org/10.1002/hbm.20159
  14. M. S. Atkins and B. T. Mackiewich, 'Fully Automatic Segmentation of the Brain in MRI,' IEEE Trans. Med. Imag., vol. 17, pp. 98-107, 1998 https://doi.org/10.1109/42.668699
  15. W. M. Wells, W. E. L. Grimson, R. Kikinis, and F. A. Jolesz, 'Adaptive segmentation of MRI data,' IEEE Trans. Med. Imag., vol. 15, pp. 429-442, 1996 https://doi.org/10.1109/42.511747
  16. S. J. He, X. Q. Shen, Y. M. Yang, R. J. He, and W. L. Yan, 'Research on MRI brain segmentation algorithm with the application in model-based EEG/MEG,' IEEE Trans. Magn.,vol. 37, pp. 3741-3744, 2001 https://doi.org/10.1109/20.952703
  17. D. van 't Ent, J. C. de Munck, and A. Kaas, 'A Fast Method to Derive Realistic BEM Models for E/MEG Source Reconstruction,' IEEE Trans. Biomed. Eng., vol. 48, pp. 1434-1443, 2001 https://doi.org/10.1109/10.966602
  18. J. Koikkalainen and J. Lotjonen, 'Reconstruction of 3-D Head Geometry From Digitized Point Sets: An Evaluation Study,' IEEE Inf. Technol. Biomed., vol. 8, pp. 377-386, 2004 https://doi.org/10.1109/TITB.2004.834401
  19. M. Fuchs, J. Kastner, M. Wagner, S. Hawes, and J. Ebersole, 'A standardized boundary element method volume conductor model,' Clin. Neurophysiol., vol. 113, pp. 702-712, 2002 https://doi.org/10.1016/S1388-2457(02)00030-5
  20. http://www.mrc-cbu.cam.ac.uk/Imaging/Common/mnispace. shtml#evans_proc
  21. T. F. Oostendorp, J. Delbeke, and D. Stegeman, 'The conductivity of the human skull: results of in vivo and in vitro measurements,' IEEE Trans. Biomed. Eng., vol. 47, pp. 1487-1492, 2000 https://doi.org/10.1109/TBME.2000.880100
  22. http://meshlab.sourceforge.net