Effects of white matter on EEG of multi-layered spherical head models

Bashar, Md. Rezaul; Li, Yan; Wen, Peng

doi:10.1109/icece.2008.4769173

Cited by 4 publications

(4 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We choose the unit magnitude of the dipoles. The details of a dipole position are illustrated in our previous work [31]. We place 64 dipoles on the head surface.…”

Section: Implementation and Experimentationmentioning

confidence: 99%

See 1 more Smart Citation

A systematic study of head tissue inhomogeneity and anisotropy on EEG forward problem computing

Bashar

Wen

2010

Australas Phys Eng Sci Med

View full text Add to dashboard Cite

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.

show abstract

“…We choose the unit magnitude of the dipoles. The details of a dipole position are illustrated in our previous work [31]. We place 64 dipoles on the head surface.…”

Section: Implementation and Experimentationmentioning

confidence: 99%

“…Therefore, the Volume constrained r long lies between 0.14 and 0.65 S/m and r trans is between 0.14 and 0.065 S/m. The Wang's constraint, proposed by Wang et al [31], is defined as the product of longitudinal and transverse conductivities stay constant and is equal to the square of the isotropic conductivity. It is represented as [5,6,19]:…”

Section: Appendix Cmentioning

confidence: 99%

A systematic study of head tissue inhomogeneity and anisotropy on EEG forward problem computing

Bashar

Wen

2010

Australas Phys Eng Sci Med

View full text Add to dashboard Cite

show abstract

“…Similarly, we meshed a four-layered spherical head volume into 275K tetrahedral elements from 48K nodes. The details of the head model construction are illustrated in our other studies [15,34]. For the construction of a realistic head model, we tessellate the MRIs into 101K brain tissues from 17K nodes by means of the same Tetgen Ò package.…”

Section: Simulationsmentioning

confidence: 99%

Effects of local tissue conductivity on spherical and realistic head models

Bashar

Wen

2010

Australas Phys Eng Sci Med

View full text Add to dashboard Cite

In this study, we consider different conductivity values based on tissue location in a human head model. We implement local conductivity (LC) to compute head surface potentials in three-, four-layered spherical and realistic head models using finite element method (FEM). Implementing LC for all head models, we obtain significant scalp potential variations in the term of relative difference measurement (RDM) and magnification (MAG) values with a maximum of 2.03±1.81 and 8.27±6.36, respectively. We also investigate the effects of conductivity variations (CVs) of head tissue layer on scalp potentials and find a maximum of 2.15±1.93 RDM and 8.57±6.61 MAG values. Our study concludes that it is important to assign LC to each tissue and it is also important to assign appropriate conductivity value in the construction of a head model for achieving accurate scalp potentials.

show abstract

“…From the clinical point of view, skull composition is assumed to have three embedded stratums (a spongy layer between another two hard layers), each one having different conductivity. Thus, anisotropic skull conductivity can be described by a three-layers-isotropic conducting model, namely, two separate compact zones plus a soft one [1]. However, accuracy of this model has been tested against numerical approximated methods (like finite difference method [6] or finite element method [10]) that may jeopardize the error calculation of reconstructed head source parameters [2].…”

Section: Introductionmentioning

confidence: 99%

Three-layer-isotropic skull conductivity representation in the EEG forward problem using spherical head models

Morales

Hallez²,

Vanrumste

et al. 2014

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

View full text Add to dashboard Cite

Abstract-We investigate influence of different conductivity models within a framework of electroencephalogram (EEG) source localization on white matter and skull areas. Particularly, we investigate five different spherical models having either isotropic or anisotropic conductivity for both considered areas. To this end, the anisotropic finite difference reciprocity method is used in solving the EEG forward problem. We evaluate a numeric skull conductivity modeling, in terms of the minimum dipole localization/orientation error. As a result, two skull models reach the lowest dipole localization error (less than 6 mm), namely, single anisotropic layer and three isotropic layers (hard bone/spongy bone/hard bone). Additionally, two different electrode configurations (10 − 20 and 10 − 10 electrodes) are tested showing that the error decreases almost twice for the latter one, although computational burden significantly increases.

show abstract

Effects of white matter on EEG of multi-layered spherical head models

Cited by 4 publications

References 14 publications

A systematic study of head tissue inhomogeneity and anisotropy on EEG forward problem computing

A systematic study of head tissue inhomogeneity and anisotropy on EEG forward problem computing

Effects of local tissue conductivity on spherical and realistic head models

Three-layer-isotropic skull conductivity representation in the EEG forward problem using spherical head models

Contact Info

Product

Resources

About