Computational Modeling of Human Head Conductivity

Abstract. The computational environment for estimation of unknown regional electrical conductivities of the human head, based on realistic geometry from seg-mented MRI up to 2563 resolution, is described. A finite difference alternating di-rection 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 para-meter space of tissue conductivities is conducted in parallel using a distributed system of heterogeneous computational resources. The theoretical and computa-tional formulation of the problem is presented. Results from test studies are pro-vided, 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.