Computational modeling of human head conductivity

  • Authors:
  • Adnan Salman;Sergei Turovets;Allen Malony;Jeff Eriksen;Don Tucker

  • Affiliations:
  • NeuroInformatics Center, 5219 University of Oregon, Eugene, OR;NeuroInformatics Center, 5219 University of Oregon, Eugene, OR;NeuroInformatics Center, 5219 University of Oregon, Eugene, OR;Electrical Geodesic, Inc., Eugene, OR;Electrical Geodesic, Inc., Eugene, OR

  • Venue:
  • ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part I
  • Year:
  • 2005

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Abstract

The computational environment for estimation of unknown regional electrical conductivities of the human head, based on realistic geometry from segmented MRI up to 2563 resolution, is described. A finite difference alternating direction implicit (ADI) algorithm, parallelized using OpenMP, is used to solve the forward problem describing the electrical field distribution throughout the head given known electrical sources. A simplex search in the multi-dimensional parameter space of tissue conductivities is conducted in parallel using a distributed system of heterogeneous computational resources. The theoretical and computational formulation of the problem is presented. Results from test studies are provided, comparing retrieved conductivities to known solutions from simulation. Performance statistics are also given showing both the scaling of the forward problem and the performance dynamics of the distributed search.