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Brain Topography

, Volume 10, Issue 1, pp 31–39 | Cite as

Confidence Interval of Single Dipole Locations Based on EEG Data

  • Christoph Braun
  • Stefan Kaiser
  • Wilhelm-Emil Kincses
  • Thomas Elbert
Article

Abstract

Noise in EEG and MEG measurements leads to inaccurate localizations of the sources. A confidence volume is used to describe the amount of localization error. Previous methods to estimate the confidence volume proved insufficient. Thus a new procedure was introduced and compared with previous ones. As one procedure, Monte Carlo simulations (MCS) were performed. The confidence volume was also estimated using two methods with different assumptions about a linear transfer function between source location and the distribution of the potential. One method used variable (LVM) and the other fixed dipole orientations (LFM). Finally, the confidence volume was estimated through a procedure in which there was no linearization of the transfer function. This procedure scans the confidence volume by varying the dipole location in multiple directions. Confidence volumes were calculated for simulated distributions of the electrical potential and for experimental data including somatosensory evoked responses to stimulation of lower lip, thumb, and little finger. Results from simulated data indicated that confidence volumes calculated with the MCS method were largest, and those calculated with the LFM method were smallest. For dipole locations close to the brain surface, the confidence volume was smaller than for a central deeper source. An increase in electrode density resulted in smaller confidence volumes. When the noise was correlated, only the method using the MCS produced acceptable results. Since the noise in experimental data is highly correlated, only the MCS method would appear to be useful in estimating the size of the confidence volume of the dipole locations. Thus, using real data with the MCS method, we easily distinguished separate and distinct representations of the thumb, little finger, and lower lip in the somatosensory cortex (SI). It was concluded that adequate estimation of confidence volumes is useful for localizing neural activity. On a practical level, this information can be used prior to an experiment for determining the conditions necessary to distinguish between different dipole sources, including the required signal to noise ratio and the minimum electrode density.

Dipole localization EEG MEG Monte Carlo Confidence interval 

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References

  1. Barth, D.S., Sutherling, W., Broffmann, J. and Beartty, J. Magnetic localization of a dipolar current source implanted in a sphere and a human cranium. Electroencephalography and Clinical Neurophysiology, 1986, 63: 260–273.Google Scholar
  2. Cohen, D., Cuffin, B. N., Yanokuchi, K., Municwski, R., Purcell, C., Cosgrove, G. R., Ives, J., Kennedym, J. G. and Schomer, D. MEG versus EEG localization Test using implanted sources in the human brain. Annals of Neurology, 1990, 28(6): 811–817.Google Scholar
  3. Cuffin, B.N. Effects on measurement errors and noise on MEG moving dipole inverse solutions. IEEE Transaction on Biomedical Engineering, 1986, 33: 854–861.Google Scholar
  4. Cuffin, B.N. and Cohen, D. Comparison of the magnetoencephalogram and the electroencephalogram. Electroencencephalography and Clinical Neurophysiology, 1979, 47: 132–146.Google Scholar
  5. Gharib, S., Sutherling, W. W., Nakasato, N., Barth, D. S., Baumgartner, C., Alexopoulos, N., Taylor, S. and Roberts, R. L. MEG and ECoG localization accuracy test. Electroencephalography and Clinical Neurophysiology, 1995, 94: 109–114.Google Scholar
  6. Hari, R., Joutsiniemi, S.-L. and Sarvas, J. Saptial resolution of neuromagnetic records: theoretical calculations in spherical model. Electroencephalography and Clinical Neurophysiology, 1988, 71: 64–72.Google Scholar
  7. Huizenga, H. M. and Molenaar, C. M. Equivalent source estimation of scalp potential fields contaminated by heteroscedastic and correlated noise. Brain Topography, 1995, 8(1): 13–33.Google Scholar
  8. Junghöfer, M., Elbert, T., Leiderer, P., Berg, P., Rockstroh, B. Mapping EEG-potentials on the surface of the brain: A strategy for unvovering cortical sources. Brain Topography, 1997, 9(3): 203–217.Google Scholar
  9. Kuriki, S., Murase, M. and Takeuchi, F. Locating accuracy of a current source of neurmagnetic responses: simulation study for a single current dipole in spherical conductor. Electroencephalography and Clinical Neurophysiology, 1989 73: 499–506.Google Scholar
  10. Mosher, J. C., Spencer, M. E., Leahy, R. M. and Lewis, P. S. Error bounds for EEG and MEG dipole source localization. Electroencephalography and Clinical Neurophysiology, 1993, 86, 303–321.Google Scholar
  11. Ogura, Y. and Sekihara, K. Relationship between dipole parameter estimation errors and measurement conditions in magnetoencephalography. IEEE-Transactions on Biomedical Engineering, 1993, 40(9): 919–924.Google Scholar
  12. Radich, B. M. EEG dipole localization bounds and MAP algorithms for head models with parameter uncertainities. IEEE Transactions on Biomedical Engineering, 1995, 42(3): 233–241.Google Scholar
  13. Sarvas, J. Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem. Phys. Med. Biol., 1987, 32(1): 11–22.Google Scholar
  14. Stok, C. J. The influence of model parameters on EEG/MEG single dipole source estimation. IEEE Transactions on Biomedical Engineering, 1987, 34(4) 289–296.Google Scholar
  15. Yamazaki, T., van Dijk, B. W. and Spekreijse, H. Confidence limits for the parameter estimation in the dipole localization method on the basis of spatial correlation of background EEG. Brain Topography, 1992, 5(2): 195–197.Google Scholar

Copyright information

© Human Sciences Press, Inc. 1997

Authors and Affiliations

  • Christoph Braun
    • 1
  • Stefan Kaiser
    • 1
  • Wilhelm-Emil Kincses
    • 1
  • Thomas Elbert
    • 2
  1. 1.Institute of Medical PsychologyUniversity of TübingenGermany
  2. 2.Dept. of PsychologyUniversity of KonstanzGermany

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