caa a22 4500 445304146 CHVBK 20180317142607.0 cr unu---uuuuu 170323e20100301xx s 000 0 eng 10.1007/s13246-010-0009-5 doi (NATIONALLICENCE)springer-10.1007/s13246-010-0009-5 A systematic study of head tissue inhomogeneity and anisotropy on EEG forward problem computing [Elektronische Daten] [M. Bashar, Y. Li, P. Wen] In this study, we propose a stochastic method to analyze the effects of inhomogeneous anisotropic tissue conductivity on electroencephalogram (EEG) in forward computation. We apply this method to an inhomogeneous and anisotropic spherical human head model. We apply stochastic finite element method based on Legendre polynomials, Karhunen-Loeve expansion and stochastic Galerkin methods. We apply Volume and Wang's constraints to restrict the anisotropic conductivities for both the white matter (WM) and the skull tissue compartments. The EEGs resulting from deterministic and stochastic FEMs are compared using statistical measurement techniques. Based on these comparisons, we find that EEGs generated by incorporating WM and skull inhomogeneous anisotropic tissue properties individually result in an average of 56.5 and 57.5% relative errors, respectively. Incorporating these tissue properties for both layers together generate 43.5% average relative error. Inhomogeneous scalp tissue causes 27% average relative error and a full inhomogeneous anisotropic model brings in an average of 45.5% relative error. The study results demonstrate that the effects of inhomogeneous anisotropic tissue conductivity are significant on EEG. Australasian College of Physical Scientists and Engineers in Medicine, 2010 EEG nationallicence Forward computation nationallicence Human head modelling nationallicence Tissue conductivity nationallicence Inhomogeneity nationallicence Anisotropy nationallicence Stochastic FEM nationallicence Bashar M. Department of Mathematics and Computing, Centre for Systems Biology, University of Southern Queensland, 4350, Toowoomba, QLD, Australia aut Li Y. Department of Mathematics and Computing, Centre for Systems Biology, University of Southern Queensland, 4350, Toowoomba, QLD, Australia aut Wen P. Faculty of Engineering and Surveying, Centre for Systems Biology, University of Southern Queensland, 4350, Toowoomba, QLD, Australia aut Australasian Physical & Engineering Sciences in Medicine Springer Netherlands 33/1(2010-03-01), 11-21 0158-9938 33:1<11 2010 33 13246 https://doi.org/10.1007/s13246-010-0009-5 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s13246-010-0009-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Bashar M. Department of Mathematics and Computing, Centre for Systems Biology, University of Southern Queensland, 4350, Toowoomba, QLD, Australia aut NATIONALLICENCE 700 1- Li Y. Department of Mathematics and Computing, Centre for Systems Biology, University of Southern Queensland, 4350, Toowoomba, QLD, Australia aut NATIONALLICENCE 700 1- Wen P. Faculty of Engineering and Surveying, Centre for Systems Biology, University of Southern Queensland, 4350, Toowoomba, QLD, Australia aut NATIONALLICENCE 773 0- Australasian Physical & Engineering Sciences in Medicine Springer Netherlands 33/1(2010-03-01), 11-21 0158-9938 33:1<11 2010 33 13246 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer