Effects of local tissue conductivity on spherical and realistic head models

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.

[1]  Yan Li,et al.  EEG Analysis on Skull Conductivity Perturbations Using Realistic Head Model , 2009, RSKT.

[2]  R. W. Lau,et al.  The dielectric properties of biological tissues: III. Parametric models for the dielectric spectrum of tissues. , 1996, Physics in medicine and biology.

[3]  Carlos H. Muravchik,et al.  Effects of geometric head model perturbations on the EEG forward and inverse problems , 2006, IEEE Transactions on Biomedical Engineering.

[4]  Sylvain Baillet,et al.  Influence of skull anisotropy for the forward and inverse problem in EEG: Simulation studies using FEM on realistic head models , 1998, Human brain mapping.

[5]  J Haueisen,et al.  The influence of local tissue conductivity changes on the magnetoencephalogram and the electroencephalogram. , 2000, Biomedizinische Technik. Biomedical engineering.

[6]  Bin He,et al.  Estimating cortical potentials from scalp EEG's in a realistically shaped inhomogeneous head model by means of the boundary element method. , 1999, IEEE transactions on bio-medical engineering.

[7]  P. Bruno,et al.  Interaction between noise and lesion modeling errors on EEG source localization accuracy , 2001, 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  R.M. Leahy,et al.  Electromagnetic brain imaging using BrainStorm , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

[9]  R. Leahy,et al.  Magnetic Resonance Image Tissue Classification Using a Partial Volume Model , 2001, NeuroImage.

[10]  P. Wen,et al.  EEG human head modelling based on heterogeneous tissue conductivity , 2006, Australasian Physics & Engineering Sciences in Medicine.

[11]  Chi Tang,et al.  Image reconstruction incorporated with the skull inhomogeneity for electrical impedance tomography , 2008, Comput. Medical Imaging Graph..

[12]  J P Kaipio,et al.  Effects of local skull inhomogeneities on EEG source estimation. , 1999, Medical engineering & physics.

[13]  Jens Haueisen,et al.  Dipole models for the EEG and MEG , 2002, IEEE Transactions on Biomedical Engineering.

[14]  Onno W. Weier,et al.  On the numerical accuracy of the boundary element method (EEG application) , 1989, IEEE Transactions on Biomedical Engineering.

[15]  Paolo Inchingolo,et al.  Improving Lesion Conductivity Estimate by Means of EEG Source Localization Sensitivity to Model Parameter , 2002, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[16]  R. Sadleir,et al.  Modeling Skull Electrical Properties , 2007, Annals of Biomedical Engineering.

[17]  D.R. Jackson,et al.  Effect of conductivity uncertainties and modeling errors on EEG source localization using a 2-D model , 1998, IEEE Transactions on Biomedical Engineering.

[18]  Richard M. Leahy,et al.  BrainSuite: An Automated Cortical Surface Identification Tool , 2000, MICCAI.

[19]  C. Wolters Influence of tissue conductivity inhomogeneity and anisotropy on EEG/MEG based source localization in the human brain , 2003 .

[20]  J. Haueisen,et al.  Influence of head models on neuromagnetic fields and inverse source localizations , 2006, Biomedical engineering online.

[21]  S. K. Law,et al.  Thickness and resistivity variations over the upper surface of the human skull , 2005, Brain Topography.

[22]  P. Celsis,et al.  Cortical Imaging on a Head Template: A Simulation Study Using a Resistor Mesh Model (RMM) , 2008, Brain Topography.

[23]  A. Aarabi,et al.  High‐resolution electroencephalography and source localization in neonates , 2008, Human brain mapping.

[24]  P. Celsis,et al.  Effects of skull thickness, anisotropy, and inhomogeneity on forward EEG/ERP computations using a spherical three‐dimensional resistor mesh model , 2004, Human brain mapping.

[25]  J. Haueisen,et al.  The Influence of Brain Tissue Anisotropy on Human EEG and MEG , 2002, NeuroImage.

[26]  I. Lemahieu,et al.  Dipole location errors in electroencephalogram source analysis due to volume conductor model errors , 2000, Medical and Biological Engineering and Computing.

[27]  J. Haueisen,et al.  Influence of tissue resistivities on neuromagnetic fields and electric potentials studied with a finite element model of the head , 1997, IEEE Transactions on Biomedical Engineering.

[28]  J. Haueisen,et al.  Influence of head models on EEG simulations and inverse source localizations , 2006, Biomedical engineering online.

[29]  Belma Dogdas,et al.  Segmentation of skull and scalp in 3‐D human MRI using mathematical morphology , 2005, Human brain mapping.

[30]  J Haueisen,et al.  Effect of model complexity on EEG source localizations. , 2004, Neurology & clinical neurophysiology : NCN.

[31]  P. Wen,et al.  Influence of white matter inhomogeneous anisotropy on EEG forward computing , 2008, Australasian Physics & Engineering Sciences in Medicine.

[32]  Richard M. Leahy,et al.  Electromagnetic brain mapping , 2001, IEEE Signal Process. Mag..

[33]  Don M. Tucker,et al.  Regional head tissue conductivity estimation for improved EEG analysis , 2000, IEEE Transactions on Biomedical Engineering.

[34]  David N. Kennedy,et al.  MRI-based anatomical model of the human head for specific absorption rate mapping , 2008, Medical & Biological Engineering & Computing.

[35]  R. T. Hart,et al.  Finite-element model of the human head: scalp potentials due to dipole sources , 1991, Medical and Biological Engineering and Computing.

[36]  Yan Li,et al.  Effects of white matter on EEG of multi-layered spherical head models , 2008, 2008 International Conference on Electrical and Computer Engineering.