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A spatial filtering technique to detect and localize multiple sources in the brain

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Summary

An algorithm for localization of electromagnetic activity in the central nervous system is explored. This algorithm generates a neural activity index map within the brain by passing surface recordings through a set of spatial filters. The covariance matrix of the surface recordings is used to optimize the spatial filters' responses. This approach is studied in simulated situations and in real data. The simulations show the method's capability to detect areas of activity without prior knowledge of the number of sources. The resolving power of the method increases with number of electrodes and signal-to-noise ratio, and it decreases with depth. The analysis of the electrophysiological data indicates that the method can distinguish simultaneously active areas in a realistic fashion. The analyzed recordings are bilateral median SEP responses, an epoch of spike activity showing several active regions and a recording with eye movement superimposed on spike activity. The method and the results are discussed in relation to current localization techniques.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Wisconsin - Madison, Madison, WI, USA

    B. D. Van Veen

  2. Department of Clinical Neurophysiology, University Hospital Utrecht, Utrecht, The Netherlands

    A. C. van Huffelen

  3. Nicolet Biomedical Inc., 5225 Verona Road, P.O. Box 44451, 53744-4451, Madison, WI, USA

    W. van Drongelen & M. Yuchtman

Authors
  1. W. van Drongelen
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  2. M. Yuchtman
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  3. B. D. Van Veen
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  4. A. C. van Huffelen
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Additional information

The authors wish to thank Dr. J. M. Guerit, Dr. R.E. Lasky and G. Rook for their valuable suggestions. We thank Dr. K. Hecox for his support and R. Birrenkot for preparing the figures.

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van Drongelen, W., Yuchtman, M., Van Veen, B.D. et al. A spatial filtering technique to detect and localize multiple sources in the brain. Brain Topogr 9, 39–49 (1996). https://doi.org/10.1007/BF01191641

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