title: Uncertainty and sensitivity analysis for anisotropic inhomogeneous head tissue conductivity in human head modelling.
abstract: 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.
authors.affiliation: Department of Mathematics and Computing, Centre for Systems Biology, University of Southern Queensland, Toowoomba, QLD, 4350, Australia. bashar@usq.edu.au
authors.forename: M R
authors.initials: MR
authors.lastname: Bashar
authors.forename: Y
authors.initials: Y
authors.lastname: Li
authors.forename: P
authors.initials: P
authors.lastname: Wen
mesh_terms: D016880:Anisotropy; D001921:Brain / Q000502:physiology; D003198:Computer Simulation; D004553:Electric Conductivity; D004569:Electroencephalography; D020342:Finite Element Analysis; D006257:Head; D006801:Humans; D008959:Models, Neurological; D013269:Stochastic Processes