Literature DB >> 10495121

Forward problem solution of electromagnetic source imaging using a new BEM formulation with high-order elements.

N G Gençer1, I O Tanzer.   

Abstract

Representations of the active cell populations on the cortical surface via electric and magnetic measurements are known as electromagnetic source images (EMSIs) of the human brain. Numerical solution of the potential and magnetic fields for a given electrical source distribution in the human brain is an essential part of electromagnetic source imaging. In this study, the performance of the boundary element method (BEM) is explored with different surface element types. A new BEM formulation is derived that makes use of isoparametric linear, quadratic or cubic elements. The surface integration is performed with Gauss quadrature. The potential fields are solved assuming a concentric three-shell model of the human head for a tangential dipole at different locations. In order to achieve 2% accuracy in potential solutions, the number of quadratic elements is of the order of hundreds. However, with linear elements, this number is of the order of ten thousand. The relative difference measures (RDMs) are obtained for the numerical models that use different element types. The numerical models that employ quadratic and cubic element types provide superior performance over linear elements in terms of accuracy in solutions. Assuming a homogeneous sphere model of the head, the RDMs are also obtained for the three components (radial and tangential) of the magnetic fields. The RDMs obtained for the tangential fields are, in general, much higher than those obtained for the radial fields. Both quadratic and cubic elements provide superior performance compared with linear elements for a wide range of dipole locations.

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Year:  1999        PMID: 10495121     DOI: 10.1088/0031-9155/44/9/314

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  6 in total

1.  Neuroelectromagnetic forward head modeling toolbox.

Authors:  Zeynep Akalin Acar; Scott Makeig
Journal:  J Neurosci Methods       Date:  2010-05-08       Impact factor: 2.390

2.  Accuracy of quadratic versus linear interpolation in noninvasive Electrocardiographic Imaging (ECGI).

Authors:  Subham Ghosh; Yoram Rudy
Journal:  Ann Biomed Eng       Date:  2005-09       Impact factor: 3.934

3.  Parallel implementation of the accelerated BEM approach for EMSI of the human brain.

Authors:  Y Ataseven; Z Akalin-Acar; C E Acar; N G Gençer
Journal:  Med Biol Eng Comput       Date:  2008-02-26       Impact factor: 2.602

4.  Somatosensory system deficits in schizophrenia revealed by MEG during a median-nerve oddball task.

Authors:  Ming-Xiong Huang; Roland R Lee; Kathleen M Gaa; Tao Song; Deborah L Harrington; Cathy Loh; Rebecca J Theilmann; J Christopher Edgar; Gregory A Miller; Jose M Canive; Eric Granholm
Journal:  Brain Topogr       Date:  2009-11-27       Impact factor: 3.020

Review 5.  Review on solving the forward problem in EEG source analysis.

Authors:  Hans Hallez; Bart Vanrumste; Roberta Grech; Joseph Muscat; Wim De Clercq; Anneleen Vergult; Yves D'Asseler; Kenneth P Camilleri; Simon G Fabri; Sabine Van Huffel; Ignace Lemahieu
Journal:  J Neuroeng Rehabil       Date:  2007-11-30       Impact factor: 4.262

6.  Forward field computation with OpenMEEG.

Authors:  Alexandre Gramfort; Théodore Papadopoulo; Emmanuel Olivi; Maureen Clerc
Journal:  Comput Intell Neurosci       Date:  2011-03-14
  6 in total

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