Single-trial EEG source reconstruction for brain-computer interface.

Brain/physiology; Brain Mapping/methods; Electroencephalography/methods; Evoked Potentials/physiology; Humans; Man-Machine Systems; Pattern Recognition, Automated/methods; User-Computer Interface

Abstract :

[en] A new way to improve the classification rate of an EEG-based brain-computer interface (BCI) could be to reconstruct the brain sources of EEG and to apply BCI methods to these derived sources instead of raw measured electrode potentials. EEG source reconstruction methods are based on electrophysiological information that could improve the discrimination between BCI tasks. In this paper, we present an EEG source reconstruction method for BCI. The results are compared with results from raw electrode potentials to enable direct evaluation of the method. Features are based on frequency power change and Bereitschaft potential. The features are ranked with mutual information before being fed to a proximal support vector machine. The dataset IV of the BCI competition II and data from four subjects serve as test data. Results show that the EEG inverse solution improves the classification rate and can lead to results comparable to the best currently known methods.

Disciplines :

Engineering, computing & technology: Multidisciplinary, general & others

Author, co-author :

Noirhomme, Quentin ; Université de Liège - ULiège > Centre de recherches du cyclotron

Kitney, Richard I

Macq, Benolt

Language :

English

Title :

Single-trial EEG source reconstruction for brain-computer interface.

Publication date :

2008

Journal title :

IEEE Transactions on Biomedical Engineering

ISSN :

0018-9294

eISSN :

1558-2531

Publisher :

IEEE, New York, United States - New York

Volume :

Issue :

Pages :

1592-601

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 27 October 2010

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52 (2 by ULiège)

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2 (1 by ULiège)

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Bibliography

J. R. Wolpaw, N. Birbaumer, D. J. McFarland, G. Pfurtscheller, and T. M. Vaughan, "Brain-computer interfaces for communication and control," Clin. Neurophysiol., vol. 113, pp. 767-791, 2002.
M. A. Lebedev and M. A. Nicolelis, "Brain-machine interfaces: Past, present and future," Trends Neurosci., vol. 29, no. 9, pp. 536-546, 2006.
S.-S. Yoo, T. Fairneny, N.-K. Chen, S.-E. Choo, L. P. Panych, H. Park, S.-Y. Lee, and F. A. Jolesz, "Brain-computer interface using fMRI: Spatial navigation by thoughts," Neuroreport, vol. 15, no. 10, pp. 1591-1595, 2004.
N. Weiskopf, K. Mathiak, S. W. Bock, F. Scharnowski, R. Veit, W. Grodd, R. Goebel, and N. Birbaumer, "Principles of a brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI)," IEEE Trans. Biomed. Eng., vol. 51, no. 6, pp. 966-970, Jun. 2004.
J. R. Wolpaw and D. J. McFarland, "Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans," PNAS, vol. 101, no. 51, pp. 17849-17854, Dec. 2004.
M. Cheng, X. Gao, S. Gao, and D. Xu, "Design and implementation of a Brain-computer interface with high transfer rates," IEEE Trans. Biomed. Eng., vol. 49, no. 10, pp. 1181-1186, Oct. 2002.
R. Scherer, G. R. Muller, C. Neuper, B. Graimann, and G. Pfurtscheller, "An asynchronously controlled EEG-based virtual keyboard: Improvement of the spelling rate," IEEE Trans. Biomed. Eng., vol. 51, no. 6, pp. 979-984, Jun. 2004.
G. Dornhege, B. Blankertz, G. Curio, and K.-R. Müller, "Boosting bit rates in noninvasive EEG single-trial classifications by features combination and multiclass paradigms," IEEE Trans. Biomed. Eng., vol. 51, no. 6, pp. 993-1002, Jun. 2004.
G. Pfurtscheller, C. Neuper, C. Guger, H. W., H. Ramoser, A. Schlögl, B. Obermaier, and M. Pregenzer, "Current trends in graz brain-computer interface (BCI) research," IEEE Trans. Rehabil. Eng., vol. 8, no. 2, pp. 216-219, Jun. 2000.
T. Hinterberger, A. Kübler, J. Kaiser, N. Neumann, and N. Birbaumer, "A brain-computer-interface (BCI) for the locked-in: Comparison of different EEG classifications for the thought translation device (TTD)," Clin. Neurophysiol., vol. 114, pp. 416-425, 2003.
V. Bostanov, "BCI competition 2003 - data set Ib and IIb: Feature extraction from event-related brain potentials with the continuous wavelet transform and the t-value scalogram," IEEE Trans. Biomed. Eng., vol. 51, no. 6, pp. 1057-1061, Jun. 2004.
S. Lemm, C. Schäfer, and G. Curio, "BCI competition 2003 - data set III: Probalistic modeling of sensorimotor μ rhythms for classification of imaginary hand movements," IEEE Trans. Biomed. Eng., vol. 51, no. 6, pp. 1077-1080, Jun. 2004.
R. Grave de Peralta Menendez, S. L. González Andino, L. Perez, P. W. Ferrez, and J. d. R. Millán, "Non-invasive estimation of local field potentials for neuroprosthesis control," Cogn. Process, vol. 6, pp. 59-64, 2005.
H. Ramoser, J. Müller-Gerking, and G. Pfurtscheller, "Optimal spatial filtering of single trial EEG during imagined hand movement," IEEE Trans. Rehabil. Eng., vol. 8, no. 4, pp. 441-446, Dec. 2000.
Y. Wang, Z. Zhang, Y. Li, X. Gao, S. Gao, and F. Yang, "BCI competition 2003 - Data set IV: An algorithm based on CSSD and FDA for classifying single-trial EEG," IEEE Trans. Biomed. Eng., vol. 51, no. 6, pp. 1081-1086, Jun. 2004.
S. Baillet, J. C. Mosher, and R. M. Leahy, "Electromagnetic brain mapping," IEEE Signal Process. Mag., vol. 18, no. 6, pp. 14-30, Nov. 2001.
C. M. Michel, M. M. Murray, G. Lantz, S. Gonzalez, L. Spinelli, and R. Grave de Peralta, "EEG source imaging," Clin. Neurophysiol., vol. 115, pp. 2195-2222, 2004.
L. Qin, L. Ding, and B. He, "Motor imagery classification by means of source analysis for brain-computer interface applications," J. Neural Eng., vol. 1, pp. 133-141, 2004.
B. Kamousi, Z. Liu, and B. He, "An EEG inverse solution based brain-computer interface," Int. J. Bioelectromag., vol. 7, no. 2, pp. 292-294, 2005.
M. Congedo, F. Lotte, and A. Lécuyer, "Classification ofmovement intention by spatially filtered electromagnetic inverse solutions," Phys. Med. Biol., vol. 51, pp. 1971-1989, 2006.
J. C. Mosher, R. M. Leahy, and P. S. Lewis, "EEG and MEG: Forward solutions for inverse methods," IEEE Trans. Biomed. Eng., vol. 46, no. 3, pp. 245-259, Mar. 1999.
R. Grave de Peralta Menendez, S. L. González Andino, S. Morand, C. M. Michel, and T. Landis, "Imaging the electrical activity of the brain: ELECTRA," Hum. Brain Mapp., vol. 9, pp. 1-12, 2000.
R. Grave de Peralta Menendez, M. M. Murray, C. M. Michel, R. Martuzzi, and S. L. González Andino, "Electrical neuroimaging based on biophysical constraints," NeuroImage, vol. 21, pp. 527-539, 2004.
B. Blankertz, K.-R. Müller, G. Curio, T. M. Vaughan, G. Schalk, J. R. Wolpaw, A. Schlögl, C. Neuper, G. Pfurtscheller, T. Hinterberger, M. Schröder, and N. Birbaumer, "The BCI competition 2003: Progress and perspectives in detection and discrimination of EEG single trials," IEEE Trans. Biomed. Eng., vol. 51, no. 6, pp. 1044-1051, Jun. 2004.
P. L. Nunez and R. B. Silberstein, "On the relationship of synaptic activity to macroscopic measurements: Does co-registration of EEG and fMRI make sense?," Brain Topogr., vol. 13, no. 2, pp. 79-96, 2000.
P. Berg and M. Scherg, "A fast method for forward computation of multiple-shell spherical head models," Electroencephalogr. Clin. Neurophysiol., vol. 90, pp. 58-64, 1994.
A. N. Tikhonov and V. Y. Arsenin, Solutions of Ill-Posed Problems. New-York: Wiley, 1977.
J. C. Mosher, S. Baillet, and R. M. Leahy, "Equivalence of linear approaches in bioelectromagnetic inverse solutions," in Proc. 2003 IEEE Workshop Stat. Signal Process., St-Louis, MO, 2003, pp. 294-297.
C. Phillips, J. Mattout, M. D. Rugg, P. Maquet, and K. J. Friston, "An empirical Bayesian solution to the source reconstruction problem in EEG," NeuroImage, vol. 24, pp. 997-1011, 2005.
R. D. Pascual-Marqui, C. M. Michel, and D. Lehmann, "Low resolution electromagnetic tomography: A new method for localizing electrical activity in the brain," Int. J. Psychophysiol., vol. 18, pp. 49-65, 1994.
S. Baillet and L. Garnero, "A Bayesian approach to introducing anatomofunctional priors in the EEG/MEG inverse problem," IEEE Trans. Biomed. Eng., vol. 44, no. 5, pp. 374-385, May 1997.
T. I. Alecu, S. Voloshynovskiy, and T. Pun, "Regularized two-step brain activity reconstruction from spatio-temporal EEG data," in Proc. Image Reconstr. Incomplete Data III, Denver, CO, SPIE Int. Symp. Opt. Sci. Technol. Aug. 2004.
P. C. Hansen, "Analysis of discrete ill-posed problems by means of the L-curve," SIAM Rev., vol. 34, pp. 561-580, 1992.
R. D. Pascual-Marqui, "Review of methods for solving the EEG inverse problem," Int. J. Bioelectromag., vol. 1, no. 1, pp. 75-86, 1999.
N. J. Trujillo-Barreto, E. Aubert-Vázquez, and P. A. Valdés-Sosa, "Bayesian model averaging in EEG/MEG imaging," NeuroImage, vol. 21, pp. 1300-1319, 2004.
J. Daunizeau, C. Grova, J. Mattout, G. Marrelec, D. Clonda, B. Goulard, M. Pelegrini-Issac, J.-M. Lina, and H. Benali, "Assessing the relevance of fMRI-based prior in the EEG inverse problem: A Bayesian model comparison approach," IEEE Trans. Signal Process., vol. 53, no. 9, pp. 3461-3472, Sep. 2005.
O. Yamashita, A. Galka, T. Ozaki, R. Biscay, and P. Valdes-Sosa, "Recursive penalized least squares solution for dynamical inverse problems of EEG generation," Hum. Brain Mapp., vol. 21, pp. 221-235, 2004.
A. Galka, O. Yamashita, T. Ozaki, R. Biscay, and P. Valdés-Sosa, "A solution to the dynamical inverse problem of EEG generation using spatiotemporal Kalman filtering," NeuroImage, vol. 23, pp. 435-453, 2004.
H. Patterson and R. Thompson, "Recovery of inter-block information when block sizes are unequal," Biometrika, vol. 58, no. 3, pp. 545-554, Dec. 1971.
D. A. Harville, "Bayesian inference for variance components using only error constrasts," Biometrika, vol. 61, no. 2, pp. 383-385, Aug. 1974.
C. Phillips, M. D. Rugg, and K. J. Friston, "Systematic regularization of linear inverse solutions of the EEG source localization problem," NeuroImage, vol. 17, pp. 287-301, 2002.
B. Blankertz, G. Curio, and K.-R. Müller, "Classifying single trial EEG: Towards brain-computer interfacing," in Proc. Adv. Neural Inf. Proc. Syst. (NIPS 01), 2002, T. G. Diettrich, S. Becker, and Z. Ghahramani, Eds., vol. 14.
E. Niedermeyer, "The normal EEG of the waking adult," in Electroencephalography Basic Principles, Clinical Applications, and Related Fields, E. Niedermeyer and F. Lopes da Silva, Eds. Baltimore, MD: Williams and Wilkins, 1999.
G. Pfurtscheller and C. Neuper, "Motor imagery activates primary sensorimotor area in man," Neurosci. Lett., vol. 239, pp. 65-68, 1997.
G. Pfurtscheller, "Event-related desynchronization (ERD) and eventrelated synchronization (ERS)," in Electroencephalography Basic Principles, Clinical Applications, and Related Fields, E. Niedermeyer and F. Lopes da Silva, Eds. Baltimore, MD: Williams and Wilkins, 1999.
F. Rossi, A. Lendasse, D. Francois, V. Wertz, and M. Verleysen, "Mutual information for the selection of relevant variables in spectrometric nonlinear modelling," Chemom. Intell. Lab. Syst., vol. 80, pp. 215-226, 2006.
A. Kraskov, H. Stögbauer, and P. Grassberger, "Estimating mutual information," Phys. Rev. E, Stat. Phys. Plasmas Fluids Relat. Interdiscip. Top., vol. 69, no. 6, pp. 066138-226, 2004.
G. Fung and O. L. Mangasarian, "Proximal support vector machine classifiers," in Proc. KDD-2001: Knowl. Discov. Data Min., F. Provost and R. Srikant, Eds. San Francisco, CA, Aug. 26-29, 2001, New York: Asscociation for Computing Machinery, 2001, pp. 77-86.
C. J. C. Burges, "A tutorial on support vector machines for pattern recognition," Data Min. Knowl. Discov., vol. 2, no. 2, pp. 121-167, 1998.
J. R. Wolpaw, N. Birbaumer, W. J. Heetderks, D. J. McFarland, P. H. Peckham, G. Schalk, E. Donchin, L. A. Quatrano, C. J. Robinson, and T. M. Vaughan, "Brain-computer interface technology: A review of the first international meeting," IEEE Trans. Rehabil. Eng., vol. 8, no. 2, pp. 164-173, Jun. 2000.
G. Blanchard and B. Blankertz, "BCI competition 2003-data set IIa: Spatial patterns of self-controlled brain rhythm modulations," IEEE Trans. Biomed. Eng., vol. 51, no. 6, pp. 1062-1066, Jun. 2004.
Y. Wang, P. Berg, and M. Scherg, "Common spatial subspace decomposition applied to analysis of brain responses under multiple task conditions: A stimulation study," Clin. Neurophysiol., vol. 110, pp. 604-614, 1999.