An evaluation of EEG scanner's dependence on the imaging technique, forward model computation method, and array dimensionality

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Volumn , Issue , 2012, Pages 1538-1541

  Stahlhut, Carsten ^a   Attias, Hagai Thomas ^b   Stopczynski, Arkadiusz ^a   Petersen, Michael Kai ^a   Larsen, Jakob Eg ^a   Hansen, Lars Kai ^a  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

^b Convex Imaging ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE BEAMFORMER; FORWARD MODELING; FORWARD MODELS; FORWARD PROPAGATION; HIGH DENSITY; ILL POSED; SOURCE RECONSTRUCTION; SPARSE BAYESIAN LEARNING;

INVERSE PROBLEMS;

IMAGING TECHNIQUES;

ARTICLE; BAYES THEOREM; COMPUTER SIMULATION; ELECTROENCEPHALOGRAPHY; ELECTROMAGNETIC FIELD; EQUIPMENT; HEAD; HUMAN; IMAGE PROCESSING; METHODOLOGY; PHYSIOLOGY; TEMPORAL LOBE; THEORETICAL MODEL;

BAYES THEOREM; COMPUTER SIMULATION; ELECTROENCEPHALOGRAPHY; ELECTROMAGNETIC FIELDS; HEAD; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MODELS, THEORETICAL; TEMPORAL LOBE;

MLCS; MLOWN;

EID: 84881443144     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EMBC.2012.6346235     Document Type: Conference Paper

References (21)

1. M. Scherg, T. Bast, and P. Berg, "Multiple source analysis of interictal spikes: Goals, requirements, and clinical value," J. Clin. Neurophysiol., vol. 16, pp. 214-224, 1999.
2. M.S. Hämäläinen and R.J. Ilmoniemi, "Interpreting magnetic fields of the brain: minimum norm estimates," Med. Biol. Eng. Comput., vol. 32, pp. 35-42, 1994.
3. R.D. Pascual-Marqui, M. Michel, and D. Lehmann, "Low resolution electromagnetic tomography: A new method for localizing electrical activity in the brain," Int J. Psychophys, vol. 18, pp. 49-65, 1994.
4. M. Fuchs, M. Wagner, T. Kohler, and H.A. Wischman, "Linear and nonlinear current density reconstructions," J. Clin. Neurophysiol., vol. 16, no. 3, pp. 267-295, 1999.
5. p-norm priors," NeuroImage, vol. 26, pp. 870-884, 2005.
6. F. Darvas, D. Pantazis, E. Kucukaltun Yildrium, and R. Leahy, "Mapping human brain function with MEG and EEG: methods and validation," NeuroImage, vol. 25, pp. 383-394, 2004.
7. N.J. Trujillo-Barreto, E. Aubert-Vazquez, and P.A. Valdes-Sosa, "Bayesian model averaging in EEG/MEG imaging," NeuroImage, vol. 21, no. 4, pp. 1300-1319, 2004.
8. K. Friston, L. Harrison, J. Daunizeau, S. Kiebel, C. Phillips, N. Trujillo-Barreto, R. Henson, G. Flandin, and J. Mattout, "Multiple sparse priors for the M/EEG inverse problem," NeuroImage, vol. 39, pp. 1104-1120, 2008.
9. D. P. Wipf, J. P. Owen, H. T. Attias, K. Sekihara, and S. S. Nagarajan, "Robust Bayesian estimation of the location, orientation, and time course of multiple correlated neural sources using MEG," Neuroimage, vol. 49, no. 1, pp. 641-655, 2010.
10. Carsten Stahlhut, Hagai T. Attias, David Wipf, Lars K. Hansen, and Srikantan S. Nagarajan, "Sparse spatio-temporal inference of electromagnetic brain sources," in Machine Learning in Medical Imaging, vol. 6357 of Lecture Notes in Computer Science, pp. 157-164. Springer Berlin / Heidelberg, 2010.
11. A. Stopczynski, J. Larsen, C. Stahlhut, M. Petersen, and L. Hansen, "A smartphone interface for a wireless eeg headset with real-time 3d reconstruction," Affective Computing and Intelligent Interaction, pp. 317-318, 2011.
12. G. Huiskamp, M. Vroeijenstijn, R. van Dijk, G. Wieneke, and A.C. van Huffelen, "The need for correct realistic geometry in the inverse EEG problem," IEEE Trans. Biomed. Eng., vol. 46, no. 11, pp. 1281-1287, Nowember 1999.
13. C.H. Wolters, A. Anwander, X. Tricoche, D. Weinstein, M.A. Koch, and R.S. MacLeod, "Influence of tissue conductivity anisotropy on EEG/MEG field and return current computation in a realistic head model: A simulation and visualization study using high-resolution finite element modeling," Neuroimage, vol. 30, no. 3, pp. 813-826, 2006.
14. M. Fuchs, R. Drenckhahn, H. Wischmann, and M. Wagner, "An improved boundary element method for realistic volume-conductor modeling," IEEE Transactions on Biomedical Engineering, vol. 45, no. 8, pp. 980-997, 1998.
15. Carsten Stahlhut, Functional Brain Imaging by EEG: A Window to the Human Mind, Ph.D. thesis, Technical Univeristy of Denmark, DTU Informatics, DK-2800 Richard Petersens Plads, Denmark, 2011.
16. H. Hallez, B. Vanrumste, R. Grech, J. Muscat, W. De Clercq, A. Vergult, Y. D'Asseler, K.P. Camilleri, S.G. Fabri, S. Van Huffel, et al., "Review on solving the forward problem in EEG source analysis," J of NeuroEng. and Rehab, vol. 4, no. 1, pp. 46, 2007.
17. O. Steinsträter, S. Sillekens, M. Junghoefer, M. Burger, and C.H. Wolters, "Sensitivity of beamformer source analysis to deficiencies in forward modeling," Human brain mapping, vol. 31, no. 12, pp. 1907-1927, 2010.
18. S. Baillet and L. Garnero, "A bayesian approach to introducing anatomo-functional priors in the EEG/MEG inverse problem," IEEE Trans. on Biomedical Engineering, vol. 44, no. 5, pp. 374-385, 1997.
19. C. M. Bishop, Pattern Recognition and Machine Learning, Springer, NY 10013 (USA), 2006.
20. C.L.M. Phillips, "Source estimation in EEG: Combining anatomical and functional constraints," PhD Thesis, 2000.
21. A. Gramfort, T. Papadopoulo, E. Olivi, M. Clerc, et al., "Openmeeg: opensource software for quasistatic bioelectromagnetics," Biomedical engineering online, vol. 9, no. 1, pp. 45, 2010.