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Seeing through the skull: Advanced EEGs use MRIs to accurately measure cortical activity from the scalp

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Summary

There is a vast amount of untapped spatial information in scalp- recorded EEGs. Measuring this information requires use of many electrodes and application of spatial signal enhancing procedures to reduce blur distortion due to transmission through the skull and other tissues. Recordings with 124 electrodes are now routinely made, and spatial signal enhancing techniques have been developed. The most advanced of these techniques uses information from a subject's MRI to correct blur distortion, in effect providing a measure of the actual cortical potential distribution. Examples of these procedures are presented, including a validation from subdural recordings in an epileptic patient. Examples of equivalent dipole modeling of the somatosensory evoked potential are also presented in which two adjacent fingers are clearly separated. These results demonstrate that EEGs can provide images of superficial cortical electrical activity with spatial detail approaching that of O15 PET scans. Additionally, equivalent dipole modeling with EEGs appears to have the same degree of spatial resolution as that reported for MEGs. Considering that EEG technology costs ten to fifty times less than other brain imaging modalities, that it is completely harmless, and that recordings can be made in naturalistic settings for extended periods of time, a greater investment in advancing EEG technology seems very desirable.

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References

  • Basar, E. (Ed.). Dynamics of Sensory and Cognitive Processing by the Brain. Springer-Verlag, Heidelberg, 1989.

    Google Scholar 

  • Cohen, D., Cuffin, B.N., Yunokuchi, K., Maniewski, R., Purcell, C., Cosgrove, G.R., Ives, J., Kennedy, J.G. and Schomer, D.L. MEG versus EEG localization test using implanted sources in the human brain. Ann. Neurol., 1990, 28: 811–817.

    Google Scholar 

  • Duffy F.M. (Ed.). Topographic Mapping of Brain Electrical Activity. Buttersworths, Boston, 1986.

    Google Scholar 

  • Fender, D.H. Source localization of brain electrical activity. In: A.S. Gevins and A. Remond (Eds.), Handbook of Electroencephalography and Clinical Neurophysiology: Vol.1, Methods of Analysis of Brain Electrical and Magnetic Signals. Elsevier, Amsterdam, 1987: 355–403.

    Google Scholar 

  • Foley, J.D., van Dam, A., Feiner, S.K. and Hughes, J.F. Computer Graphics: Principles and Practice, 2nd Ed. Addison-Wesley, New York, 1990.

    Google Scholar 

  • Freeman, W.J. Use of spatial deconvolution to compensate for distortion of EEG by volume conduction. IEEE Trans. Biomed. Engr., 1980, 27: 421–429.

    Google Scholar 

  • Gevins, A.S. Application of pattern recognition to brain electrical potentials. IEEE Trans. Pattern Ana. Mach. Intell., 1980, 12: 38

    Google Scholar 

  • Gevins, A. Dynamic functional topography of cognitive tasks. Brain Topography, 1989, 2: 37–56.

    Google Scholar 

  • Gevins, A.S. Dynamic patterns in multiple lead data. In: J.W. Rohrbaugh, R. Parasuraman and R. Johnson, Jr. (Eds.), Event-Related Brain Potentials: Basic Issues and Applications. Oxford University Press, New York, 1990: 44–56.

    Google Scholar 

  • Gevins, A.S. and Bressler, S.L. Functional topography of the human brain. In: G. Pfurtscheller and F.H. Lopes da Silva (Eds.), Functional Brain Imaging. Hans Huber Publishers, Bern, 1988: 99–116.

    Google Scholar 

  • Gevins, A.S. and Morgan, N.H. Applications of neural-network (NN) signal processing in brain research. IEEE ASSP Trans., 1988, 7: 1152–1161.

    Google Scholar 

  • Gevins, A.S. and Remond, A. (Eds.). Methods of Analysis of Brain Electrical and Magnetic Signals. Handbook of Electroencephalography and Clinical Neurophysiology, Vol.1. Elsevier, Amsterdam, 1987.

    Google Scholar 

  • Gevins, A.S., Bressler, S.L., Morgan, N.H., Cutillo, B.A., White, R.M., Greer, D.S. and Illes, J. Event-related covariances during a bimanual visuomotor task. I. Methods and analysis of stimulus- and response-locked data. Electroenceph. Clin. Neurophysiol., 1989, 74: 58–75.

    Google Scholar 

  • Gevins, A.S., Doyle, J.C., Cutillo, B.A., Schaffer, R.E., Tannehill, R.S., Ghannam, J.H., Gilcrease, V.A. and Yeager, C.L. Electrical potentials in human brain during cognition: New method reveals dynamic patterns of correlation. Science, 1981, 213: 918–922.

    Google Scholar 

  • Gevins, A., Brickett, P., Costales, B., Le, J., Reutter, B. Beyond topographic mapping: Towards functional-anatomical imaging with 124-channel EEGs and 3-D MRIs. Brain Topography, 1990, 3: 53–64.

    Google Scholar 

  • Heffernan, P.B. and Robb, R.A. A new method for shaded surface display of biological and medical images. IEEE Trans. Medical Imaging, 1985, 4: 26–38.

    Google Scholar 

  • Hill, C.D., Kearfott, R.B and Sidman, R.D. The inverse problem of electroencephalography using an imaging technique for simulating cortical surface data. In: R. Vichnevetsky, P. Borne, J. Vignes (Eds)., Proc. 12th IMACS World Cong., Vol. 3, 1988: 735–738.

    Google Scholar 

  • Hjorth, B. An on-line transformation of EEG scalp potentials into orthogonal source derivations Electroenceph. Clin. Neurophysiol., 1975, 39: 526–530.

    Google Scholar 

  • Jack, C.R., Marsh, W.R., Hirschorn, K.A., Sharbrough, F.W., Cascino, G.D., Karwoski, R.A. and Robb, R.A. EEG scalp electrode projection onto three-dimensional surface rendered images of the brain. Radiology, 1990, 176: 413–418.

    Google Scholar 

  • Jasper, H.H. The ten-twenty electrode system of the international federation. Electroenceph. Clin. Neurophysiol., 1958, 10: 371–375.

    Google Scholar 

  • John, E.R. Neurometrics: Clinical Applications of Quantitative Electrophysiology. Lawrence Erlbaum, Hillsdale, NJ, 1977.

    Google Scholar 

  • Le, J. and Gevins, A.S. Laplacian derivation of scalp-recorded EEGs computed with realistic head model and 3-D spline. In preparation, a.

  • Le, J. and Gevins, A.S. MRI-based finite element model deblurring of scalp-recorded EEGs. In preparation, b.

  • Lehmann, D. Spatial analysis of EEG and evoked potential data. In: F.H. Duffy (Ed.), Topographic Mapping of Brain Electrical Activity. Buttersworths, Boston, 1986: 23–61.

    Google Scholar 

  • Levin, D.N., Hu, X., Tan, K.K. and Galhotra, S. Surface of the brain: three-dimensional MR images created with volumerendering. Radiology, 1989, 171: 277–280.

    Google Scholar 

  • Levoy, M. Display of surfaces from volume data. IEEE Comput. Graph. and Applic., 1988, 8: 29–37.

    Google Scholar 

  • Lopes da Silva, F.H., Storm van Leeuwen W. and Remond, A. (Eds.). Handbook of Electroencephalography and Clinical Neurophysiology, Vol. 2: Clinical Applications of Computer Analysis of EEG and other Neurophysiological Signals. Elsevier, Amsterdam, 1986.

    Google Scholar 

  • Lorensen, W. E. and Cline, H. E. Marching cubes: A high resolution 3-D surface construction algorithm. Comput. Graph., 1987, 21: 163–170.

    Google Scholar 

  • Luders, H., Dinner, D.S., Lesser, R.P. and Morris, H.H. Evoked potentials in cortical localization. J. Clin. Neurophysiol., 1986, 3: 75–84.

    Google Scholar 

  • Mintun, M.A., Fox, P.T. and Raichle, M. A highly accurate method of localizing regions of neuronal activation in the human brain with positron emission tomography. J. Cereb. Blood Flow Metab. 1989, 9: 96–103.

    Google Scholar 

  • Nicholas, P. and Deloche, G. Convolution computer processing of the brain electrical image transmission. Int. J. Bio-Med. Comput., 1976, 7: 143–159.

    Google Scholar 

  • Nunez, P. Estimation of large scale neocortical source activity with EEG surface Laplacians. Brain Topography, 1989, 2: 141–154.

    Google Scholar 

  • Okada, Y.C., Tannenbaum, R., Williamson, S.J. and Kaufman, L. Somatopic organization of the human somatosensory cortex revealed by neuromagnetic measurement. Exp. Brain Res. 1984, 56: 197–205.

    Google Scholar 

  • Pfurtscheller, G. and Lopes da Silva, F.H. (Eds.). Functional Brain Imaging. Hans Huber Publishers, Bern, 1988.

    Google Scholar 

  • Reutter, B.W. and Gevins, A.S. Algorithms for analysis of Magnetic Resonance Images. In preparation.

  • Sidman, R.D., Kearfort, R.B., Major, D.J., Hill, D.C., Ford, M.R., Smith, D.B., Lee, L. and Kramer, R. Development and application of mathematical techniques for the noninvasive localization of the sources of scalp-recorded electric potentials. In: J. Eisenfield and D.S. Levine (Eds.), IMACS Trans. Scientific Computing., Vol. 5. J. C. Baltzer AG, Basel, 1989: 133–157.

    Google Scholar 

  • Wang, J., Cohen, L.M. and Hallett, M. Scalp topography of somatosensory evoked potentials following electrical stimulation of femoral nerve. Electroenceph. Clin. Neurophysiol., 1989, 74: 112- 123.

    Google Scholar 

  • Wood, C.C., Cohen, D., Cuffin, B.N., Yarita, M. and Allison, T. Electrical sources in human somatosensory cortex: Identification by combined magnetic and potential recordings. Science, 1985, 227: 1051–1053.

    Google Scholar 

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Authors and Affiliations

  1. EEG Systems Laboratory and Sam Technology, 51 Federal, 94017, San Francisco, CA, USA

    Alan Gevins, Jian Le, Paul Brickett, Bryan Reutter & John Desmond

Authors
  1. Alan Gevins
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  2. Jian Le
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  3. Paul Brickett
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  4. Bryan Reutter
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  5. John Desmond
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Additional information

Supported by the National Institute of Neurological Diseases and Stroke, the National Institute of Mental Health, the National Institute of Health, the Air Force Office of Scientific Research, the Air Force School of Aerospace Medicine and the Office of Naval Research. Access to neurosurgery patients was kindly provided by the Northern California Comprehensive Epilepsy Center at the University of California (San Francisco), Dr. Kenneth Laxer, Director, and Dr. Nicolas Barbaro, Neurosurgeon. Contributions to the research presented here were also made by our colleagues at EEG Systems Laboratory including Jim Alexander, Brian Cutillo, Judy McLaughlin, and Michael Ward.

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Gevins, A., Le, J., Brickett, P. et al. Seeing through the skull: Advanced EEGs use MRIs to accurately measure cortical activity from the scalp. Brain Topogr 4, 125–131 (1991). https://doi.org/10.1007/BF01132769

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