Computational Modeling of Human Head Conductivity

Abstract

Abstract. The computational environment for estimation of unknown regional electrical conductivities of the human head, based on realistic geometry from segmented MRI up to 256 3 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.

Use of Parallel Simulated Annealing for Computational Modeling of Human Head Conductivity

“…Together, the forward and inverse calculations define the (indirect) conductivity modeling problem. A complete formal description of the forward and inverse problems can be found in our early ICCS paper [2]. Here we provide only a brief review.…”

“…In our earlier work, we parallelized the forward solver using OpenMP and achieved speedups of 5.8 on eight processors and 8.2 on sixteen processors on a 16-processor IBM p690 system (see [2]). Here we also parallelized the simulated annealing algorithm along the searchradius, modifying the parallel MPI-based methods described in [7] for our problem domain.…”

“…In our 2005 ICCS paper [2], we combined FDM modeling with a parameterized electrical impedance tomography (EIT) measurement procedure and a downhill simplex algorithm to extract three-and four-tissue conductivities in simulations with reasonable accuracy. We parallelized the simplex search using a multi-start technique and good speedup was achieved.…”

An Open Domain-Extensible Environment for Simulation-Based Scientific Investigation (ODESSI)

“…ODESSI was inspired by our research in human neuroscience where we are developing computational models of human head electromagnetics for use in dynamic brain analysis [18,20,21]. The main goal of our research is to estimate the locations of the active brain regions given measured electroencephalogram (EEG) recordings.…”

“…The development of the ODESSI prototype is discussed in §4. ODESSI was inspired by our prior ICCS work [18,20] on computational modeling of human head conductivity. Section §5 outlines the domain problem in human brain science we are investigating and shows how ODESSI is applied to improve scientific productivity in this domain.…”