Citation
J. Mikael Eklund, Ruzena Bajcsy, Jonathan Sprinkle, Gregory V. Simpson. "Computing Inverse MEG Signals in the Brain". 2005 IEEE Computational Systems Bioinformatics Conference, Controlling Complexity, 332-335, August, 2005.

Abstract
This paper deals with the complexity of the inverse computation of brain currents from magnetoencephalography (MEG) signals. MEG measures the magnetic field outside the head: in effect, the resultant field from the flow of current inside the brain. We describe our current techniques to perform this inverse computation (called source estimation in much of the literature), which provides a view of brain activity that is less sensitive to disturbances which affect other kinds of brain activity measurements, though much more expensive to record.

Electronic downloads

• http://ieeexplore.ieee.org/iel5/10336/32899/01540637.pdf?tp=&arnumber=1540637&isnumber=32899

• HTML

  J. Mikael Eklund, Ruzena Bajcsy, Jonathan Sprinkle, Gregory
  V. Simpson. <a
  href="http://chess.eecs.berkeley.edu/pubs/70.html"
  >Computing Inverse MEG Signals in the Brain</a>,
  2005 IEEE Computational Systems Bioinformatics Conference,
  Controlling Complexity, 332-335, August, 2005.

• Plain text

  J. Mikael Eklund, Ruzena Bajcsy, Jonathan Sprinkle, Gregory
  V. Simpson. "Computing Inverse MEG Signals in the
  Brain". 2005 IEEE Computational Systems Bioinformatics
  Conference, Controlling Complexity, 332-335, August, 2005.

• BibTeX

  @inproceedings{EklundBajcsySprinkleSimpson05_ComputingInverseMEGSignalsInBrain,
      author = {J. Mikael Eklund and Ruzena Bajcsy and Jonathan
                Sprinkle and Gregory V. Simpson},
      title = {Computing Inverse MEG Signals in the Brain},
      booktitle = {2005 IEEE Computational Systems Bioinformatics
                Conference, Controlling Complexity},
      pages = {332-335},
      month = {August},
      year = {2005},
      abstract = {This paper deals with the complexity of the
                inverse computation of brain currents from
                magnetoencephalography (MEG) signals. MEG measures
                the magnetic field outside the head: in effect,
                the resultant field from the flow of current
                inside the brain. We describe our current
                techniques to perform this inverse computation
                (called source estimation in much of the
                literature), which provides a view of brain
                activity that is less sensitive to disturbances
                which affect other kinds of brain activity
                measurements, though much more expensive to record.},
      URL = {http://chess.eecs.berkeley.edu/pubs/70.html}
  }
  

Posted by Jonathan Sprinkle on 9 May 2006.
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