Uncertainty and sensitivity analysis for anisotropic inhomogeneous head tissue conductivity in human head modelling

Bashar, M. R. and Li, Y. and Wen, P. (2010) Uncertainty and sensitivity analysis for anisotropic inhomogeneous head tissue conductivity in human head modelling. Australasian Physical and Engineering Sciences in Medicine, 33 (2). pp. 145-152. ISSN 0158-9938


The accuracy of an electroencephalography (EEG) forward problem partially depends on the head tissue conductivities. These conductivities are anisotropic and
inhomogeneous in nature. This paper investigates the
effects of conductivity uncertainty and analyses its sensitivity on an EEG forward problem for a spherical and a
realistic head models. We estimate the uncertain conductivities using an efficient constraint based on an optimization method and perturb it by means of the volume and directional constraints. Assigning the uncertain conductivities, we construct spherical and realistic head models by
means of a stochastic finite element method for fixed
dipolar sources. We also compute EEG based on the constructed head models. We use a probabilistic sensitivity
analysis method to determine the sensitivity indexes. These
indexes characterize the conductivities with the most or the
least effects on the computed outputs. These results demonstrate that conductivity uncertainty has significant effects on EEG. These results also show that the uncertain conductivities of the scalp, the radial direction of the skull and transversal direction in the white matter are more sensible.

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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information (displayed to public): Author version not held.
Depositing User: Dr Yan Li
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 14 Nov 2010 11:29
Last Modified: 03 Jul 2013 00:04
Uncontrolled Keywords: conductivity; uncertainty; probabilistic sensitivity analysis; stochastic finite element method; EEG and Forward problem
Fields of Research (FoR): 06 Biological Sciences > 0699 Other Biological Sciences > 069999 Biological Sciences not elsewhere classified
11 Medical and Health Sciences > 1103 Clinical Sciences > 110320 Radiology and Organ Imaging
11 Medical and Health Sciences > 1109 Neurosciences > 110999 Neurosciences not elsewhere classified
Socio-Economic Objective (SEO): E Expanding Knowledge > 97 Expanding Knowledge > 970110 Expanding Knowledge in Technology
Identification Number or DOI: doi: 10.1007/s13246-010-0015-7
URI: http://eprints.usq.edu.au/id/eprint/8865

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