A novel volume integral equation for solving the Electroencephalography forward problem

In this paper, a novel volume integral equation for solving the Electroencephalography forward problem is presented. Differently from other integral equation methods standardly used for the same purpose, the new formulation can handle inhomogeneous and fully anisotropic realistic head models. The new equation is obtained by a suitable use of Green's identities together with an appropriate handling of all boundary conditions for the EEG problem. The new equation is discretized with a consistent choice of volume and boundary elements. Numerical results shows validity and convergence of the approach, together with its applicability to real case models obtained from MRI data.

[1]  Bart Vanrumste,et al.  Review on solving the forward problem in EEG source analysis , 2007, Journal of NeuroEngineering and Rehabilitation.

[2]  Z. Zhang,et al.  A fast method to compute surface potentials generated by dipoles within multilayer anisotropic spheres. , 1995, Physics in medicine and biology.

[3]  Jens Haueisen,et al.  Influence of anisotropic electrical conductivity in white matter tissue on the EEG/MEG forward and inverse solution. A high-resolution whole head simulation study , 2010, NeuroImage.

[4]  Robert Plonsey,et al.  Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Fields , 1995 .

[5]  Qianqian Fang,et al.  Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates , 2010, Biomedical optics express.

[6]  D. Wilton,et al.  A tetrahedral modeling method for electromagnetic scattering by arbitrarily shaped inhomogeneous dielectric bodies , 1984 .

[7]  C. Michel,et al.  128-Channel EEG Source Imaging in Epilepsy: Clinical Yield and Localization Precision , 2004, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[8]  G. Pfurtscheller,et al.  Brain-Computer Interfaces for Communication and Control. , 2011, Communications of the ACM.

[9]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[10]  A Van Cott,et al.  Technical advantages of digital EEG. , 1998, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[11]  R. Green,et al.  Benefits, Shortcomings, and Costs of EEG Monitoring , 1985, Annals of surgery.

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

[13]  Richard M. Leahy,et al.  Source localization using recursively applied and projected (RAP) MUSIC , 1997 .

[14]  Dennis J. McFarland,et al.  Brain–computer interfaces for communication and control , 2002, Clinical Neurophysiology.

[15]  Fusheng Yang,et al.  Standardized shrinking LORETA-FOCUSS (SSLOFO): a new algorithm for spatio-temporal EEG source reconstruction , 2005, IEEE Transactions on Biomedical Engineering.

[16]  Jens Haueisen,et al.  Evaluation of the distortion of EEG signals caused by a hole in the skull mimicking the fontanel in the skull of human neonates , 2005, Clinical Neurophysiology.

[17]  V. C. Edwards Benefits , 1993, Encyclopedia of Evolutionary Psychological Science.

[18]  C. Miniussi,et al.  New insights into rhythmic brain activity from TMS–EEG studies , 2009, Trends in Cognitive Sciences.

[19]  W. Marsden I and J , 2012 .

[20]  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.

[21]  H. Flor,et al.  A spelling device for the paralysed , 1999, Nature.

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

[23]  I F Gorodnitsky,et al.  Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm. , 1995, Electroencephalography and clinical neurophysiology.

[24]  Sabine Fenstermacher,et al.  Numerical Approximation Of Partial Differential Equations , 2016 .

[25]  R D Pascual-Marqui,et al.  Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. , 2002, Methods and findings in experimental and clinical pharmacology.