Boundary element method volume conductor models for EEG source reconstruction

Objectives: The boundary element method (BENI) approximates the different c ompartments of volume conductor models by closed triangle meshes with a lim ited number of nodes. The shielding effect of the weakly conducting skull l ayer of the human head leads to decreasing potential gradients from the ins ide to the outside. Thus, there may be an optimum distribution of nodes to the compartments for a given number of nodes corresponding to a fixed compu tational effort, resulting in improved accuracy as compared to standard uni form distributions. Methods: Spherical and realistically shaped surfaces are approximated by 50 0, 1000, 2000, and 3000 nodes, each leading to BEM models with 1500-9000 no des in total. Electrodes are placed on extended 10/20-system positions. Pot ential distributions of test-dipoles at 4000 random positions within the in nermost compartment are calculated. Dipoles are then fitted using 192 diffe rent models to find the optimum node distribution. Results: Fitted dipole positions for all BEM models are evaluated to show t he dependency of the averaged and maximum localization errors on their node distributions. Dipoles close to the innermost boundary exhibit the largest localization errors, which mainly depend on the refinement of this compart ment's triangle mesh. Conclusions: More than 500 nodes per compartment are needed for reliable BE M models. For a state-of-the-art model consisting of 6000 nodes overall, th e best model consists of 3000, 2000, and 1000 nodes from the inside to the outside. (C) 2001 Elsevier Science Ireland Ltd. All rights reserved.