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Neuromagnetic Source Reconstruction and Inverse Modeling

  • Kensuke Sekihara
  • Srikantan S. Nagarajan
Part of the Bioelectric Engineering book series (BEEG)

Abstract

The human brain has approximately 1010 neurons in its cerebral cortex. Their electrophysiological activity generates weak but measurable magnetic fields outside the scalp. Magnetoencephalography (MEG) is a method which measures these neuromagnetic fields to obtain information about these neural activities (Hämäläinen et al., 1993; Roberts et al., 1998; Lewine et al., 1995). Among the various kinds of functional neuroimaging methods, such a neuro-electromagnetic approach has a major advantage in that it can provide fine time resolution of millisecond order. Therefore, the goal of neuromagnetic imaging is to visualize neural activities with such fine time resolution and to provide functional information about brain dynamics. To attain this goal, one technical hurdle must be overcome. That is, an efficient method to reconstruct the spatio-temporal neural activities from neuromagnetic measurements needs to be developed. Toward this goal, a number of algorithms for reconstructing spatio-temporal source activities have been investigated (Baillet et al., 2001).

Keywords

Inverse Modeling Spatial Filter Lead Field Posterior Tibial Nerve Stimulation Sensor Coil 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic/Plenum Publishers, New York 2004

Authors and Affiliations

  • Kensuke Sekihara
    • 1
  • Srikantan S. Nagarajan
    • 2
  1. 1.Department of Electronic Systems and EngineeringTokyo Metropolitan Institute of TechnologyTokyoJapan
  2. 2.Department of RadiologyUniversity of California, San FranciscoSan FranciscoUSA

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