Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31105
Study of EEGs from Somatosensory Cortex and Alzheimer's Disease Sources

Authors: Md R. Bashar, Yan Li, Peng Wen


This study is to investigate the electroencephalogram (EEG) differences generated from a normal and Alzheimer-s disease (AD) sources. We also investigate the effects of brain tissue distortions due to AD on EEG. We develop a realistic head model from T1 weighted magnetic resonance imaging (MRI) using finite element method (FEM) for normal source (somatosensory cortex (SC) in parietal lobe) and AD sources (right amygdala (RA) and left amygdala (LA) in medial temporal lobe). Then, we compare the AD sourced EEGs to the SC sourced EEG for studying the nature of potential changes due to sources and 5% to 20% brain tissue distortions. We find an average of 0.15 magnification errors produced by AD sourced EEGs. Different brain tissue distortion models also generate the maximum 0.07 magnification. EEGs obtained from AD sources and different brain tissue distortion levels vary scalp potentials from normal source, and the electrodes residing in parietal and temporal lobes are more sensitive than other electrodes for AD sourced EEG.

Keywords: Finite Element Method, electroencephalogram, Alzheimer's disease (AD), brain tissue distortion

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1545


[1] S. Kloppel, C. M. Stonnington, C. Chu , B. Draganski, R. I. Scahill, J. D. Rohrer, N. C. Fox, C. R. Jack Jr, J. Ashburner and R. S. J. Frackowiak, "Automatic classification of MR scans in Alzheimer-s disease," Brain, vol. 131, pp. 681-689, Jan. 2008.
[2] L. Mosconi, S. Sorbi, M. J. de Leon, Y. Li , B. Nacmias, and P. S. Myong, "Hypometabolism exceeds atrophy in presymptomic early-onset familial Alzheimer's disease," Journal of Neuclear Medicine, vol. 47, pp. 1778-1786, Nov. 2006.
[3] J. C. Baron, G. Chetelat, B. Desgranges, G. Perchey, B. Landeau, V. de la Sayette, and F. Eustache, "In vivo mapping of gray matter loss with voxel-based morphometry in mild Alzheimer's disease," NeuroImage, vol. 14, pp. 298-309, Aug. 2001.
[4] A. D. Smith, and K. A. Jobst, "Use of structural imaging to study the progression of Alzheimer's diseases," British Medical Bulletin, vol. 52, no. 3, pp. 575-586, 1996.
[5] M. Chupi, A. R. Mukuna-Bantumbakulu, D. Hasboun, E. Bardinet, S. Baillet, S. Kinkingnehun, L. Lemieux, B. Dubois, and L. Garnero, , "Anatomically constrained region deformation for the automated segmentation of the hippocampus and amygdala: Method and validation on controls and patients with Alzheimer disease," NeuroImage, vol. 34, pp. 996-1019, Feb. 2007.
[6] T. Patel, R. Polikar, C. Davatzikos, and C. M. Clark, "EEG and MRI Data Fusion for Early Diagnosis of Alzheimer-s Diseas," in proc. 30th Annual International IEEE EMBS Conference, Canada, 2008, pp. 1757- 1760.
[7] R. Polikar, T. D. Green, J. Kounios, and C. M. Clark, "Comparative multiresolution wavelet analysis of ERP spectral bands using an ensamble of classifier approach for early diagnosis for Alzheimer-s disease," Computers in. Biology and Medicine, vol. 37, no. 4, pp. 542- 558, Apr. 2007.
[8] G. Chetelat, B. Desgranges, B. Landeau, F. Mezenge, J. B. Poline, V. de la Sayette, F. Viader, F. Eustache, and J. C. Baron, "Direct voxel-based comparison between grey matter hypometabolism and atrophy in Alzheimer-s disease," Brain, vol. 131, pp. 60-71, Jan. 2008.
[9] (Online source) D. W. Shattuck. (2005). BrainSuite 2 Tutorial. Available:
[10] D. W. Shattuck, S. R. Sandor-Leahy, K. A. Schaper, D. A. Rottenberg, and R. M. Leahy,"Magnetic Resonance Image Tissue Classification Using a Partial Volume Model," NeuroImage, vol. 13, no. 5, pp. 856- 876, 2001.
[11] D. W. Shattuck, and R. M. Leahy, "BrainSuite: An Automated Cortical Surface Identification Tool," Medical Image Analysis, vol. 8, no. 2, pp. 129-142, June 2002.
[12] B. Dogdas, D. W. Shattuck, and R. M. Leahy, "Segmentation of Skull and Scalp in 3-D Human MRI using Mathematical Morphology," Human Brain Mapping, vol. 26, pp. 273-285, June 2005.
[13] M. R. Bashar, Y. Li, and P. Wen, "EEG analysis on skull conductivity perturbations using realistic head model," Lecture Notes on Computer Science, vol. 5589, pp. 208-215, July 2009.
[14] R. N. Klepfer, C. R. Johnson, and S. M. Robert, "The effects of Inhomogeneities and Anisotropies on Electrocardiographic Fields: A 3- D Finite -element Study," IEEE Transactions on Biomedical Engineering, vol. 44, no. 8, pp. 706-719, Aug. 1997.
[15] C. H. Wolters, "Influence of Tissue Conductivity Inhomogeneity and Anisotropy on EEG/MEG based Source Localization in the Human Brain," PhD thesis. University of Leipzig. France; July 2003.
[16] M. R. Bashar, Y. Li, and P. Wen, "Influence of white matter inhomogeneous anisotropy on EEG forward computing," Australasian Physical & Engineering Sciences in Medicine, vol. 31, no. 2, pp. 122- 130, 2008.
[17] P. Wen P, and Y. Li, "EEG human head modelling based on heterogeneous tissue conductivity," Australasian Physical & Engineering Sciences in Medicine, vol. 29, no. 3, pp. 235-240, 2006.
[18] D. Gullmar, J. Haueisen, M. Wiselt, F. Giebler, L. Flemming, A. Anwander, T. R. Knosche, C. H. Wolters, M. Dumpelmann, D. S. Tuch and J. R. Reichenbach., "Influence of Anisotropic Conductivity on EEG source Reconstruction: Investigations in a Rabbit Model," IEEE Transactions on Biomedical Engineering, vol. 53, no. 9, pp. 1841-1850, Sep. 2006.
[19] J. Hauseisen, C. Ramon, M. Eiselt, H. Brauer, and H. Nowak,"Influence of Tissue Resistivities on Neuromagnetic Fields and Electric Potentials studied with a Finite Element Model of the Head," IEEE Transactions on Biomedical Engineering, vol. 44, no. 8, pp. 727-735, Aug. 1997.
[20] K. A. Awada, S. B. Baumann, and D. R. Jackson," Effect of conductivity uncertainties on EEG source localization using a 2D finite element model," in Proc. of 19th International Conference - IEEE/EMBS, USA, 1997, pp. 2124-2127.
[21] (Online Source) H. Si. (2004). TetGen. Available:
[22] S. Baillet, J. C. Mosher, and R. M. Leahy, "Electromagnetic Brain Imaging using Brainstorm," in Proc. IEEE Int. Symposium on Biomed. Eng.: Macro to Nano 2004, pp. 652-655.
[23] G. B. Frisoni, M. Pievani, C. Testa, S. F. Francesca, L. Bresciani , M. Bonetti, A. Beltramello, K. M. Hayashi, A. W. Toga, and P. M. Thompson, "The topography of grey matter involvement in early and late onset Alzheimer-s disease," Brain, vol. 130, pp. 720-730, Feb. 2007.
[24] J. W. Meijis, O. W. Weier, M. J. Peters, and A. van Oosterom, "On the numerical accuracy of the boundary element method," IEEE Transactions on Biomedical Engineering, vol. 36, no. 10, pp. 1038- 1049, Oct. 1989.
[25] (Online Source) ANT Software, The Netherland. (2007). Advanced Source Analysis. Available: