E. Aykut-bingol, C. Bingol, H. Bro, R. Yener, and B. , Multiway analysis of epilepsy tensors, Bioinformatics, issue.13, pp.23-33, 2007.

M. Aizerman, E. Braverman, and L. Rozonoer, Theoretical foundations of the potential function method in pattern recognition learning. Automation and remote control, pp.821-837, 1964.

H. Akaike, A new look at the statistical model identification, IEEE Trans, 1974.

R. Albright, J. Cox, D. Duling, A. N. Langville, and C. D. Meyer, Algorithms, initializations, and convergence for the nonnegative matrix factorization, 2006.

C. W. Anderson and Z. Sijercic, Classification of EEG signals from four subjects during five mental tasks Solving Engineering Problems with Neural Networks, Proc, 1996.

A. T. Boye, U. Q. Kristiansen, M. Billinger, O. F. Nascimento, and D. Farina, Identification of movement-related cortical potentials with optimized spatial filtering and principal component analysis, References Brain-Computer Interface with cortical electrical activity recording References Brain-Computer Interface with cortical electrical activity recording References Brain-Computer Interface with cortical electrical activity recording, pp.300-304, 2008.
DOI : 10.1016/j.bspc.2008.05.001

R. Bro, Multiway calibration. Multilinear PLS, Journal of Chemometrics, vol.10, issue.1, pp.47-61, 1996.
DOI : 10.1002/(SICI)1099-128X(199601)10:1<47::AID-CEM400>3.0.CO;2-C

R. Bro, Multi-way analysis in the food industry: models, algorithms, and applications, 1998.

E. Buch, C. Weber, L. G. Cohen, C. Braun, M. A. Dimyan et al., Think to Move: a Neuromagnetic Brain-Computer Interface (BCI) System for Chronic Stroke, Think to Move: a Neuromagnetic Brain-Computer Interface (BCI) System for Chronic Stroke, pp.910-917, 2008.
DOI : 10.1161/STROKEAHA.107.505313

C. J. Burges, A tutorial on support vector machines for pattern recognition, 1998.

G. Buzsáki, Rhythms of the Brain, 2006.
DOI : 10.1093/acprof:oso/9780195301069.001.0001

A. F. Cabrera, D. Farina, and K. Dremstrup, Comparison of feature selection and classification methods for a brain???computer interface driven by non-motor imagery, Medical & Biological Engineering & Computing, vol.2005, issue.19, pp.123-132, 2010.
DOI : 10.1007/s11517-009-0569-2

G. A. Carpenter, S. Grossberg, N. Markuzon, J. H. Reynolds, and D. B. Rosen, Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps, IEEE Transactions on Neural Networks, vol.3, issue.5, pp.698-713, 1992.
DOI : 10.1109/72.159059

Z. C. Chao, Y. Nagasaka, and N. Fujii, Long-term asynchronous decoding of arm motion using electrocorticographic signals in monkey, Frontiers in Neuroengineering, vol.3, issue.3, pp.1-10, 2010.
DOI : 10.3389/fneng.2010.00003

Z. C. Chao, Y. Nagasaka, and N. Fujii, Long-term asynchronous decoding of 3D hand trajectories using electrocorticographic signals in primates, Proceedings of the 4th International IEEE EMBS Conference on Neural Engineering Antalya, Turkey, 2009.

J. K. Chapin, K. A. Moxon, R. S. Markowitz, and M. A. Nicolelis, Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex, Nature America Inc, 1999.

W. Wireless, L. Power, M. Ward, R. K. Birch, and G. E. , 64-Channel ECoG Recording Platform for References Brain-Computer Interface with cortical electrical activity recording References Brain-Computer Interface with cortical electrical activity recording Fatourechi A self-paced brain?computer interface system with a low false positive rate, J Neural Eng, vol.55, issue.1, pp.9-23, 2008.

M. Fatourechi, G. E. Birch, and R. K. Ward, A self-paced brain interface system that uses movement related potentials and changes in the power of brain rhythms, Journal of Computational Neuroscience, vol.17, issue.9, pp.21-37, 2007.
DOI : 10.1007/s10827-006-0017-3

M. Fatourechi, A. Bashashati, G. E. Birch, and R. K. Ward, Automatic user customization for improving the performance of a self-paced brain interface system, Medical & Biological Engineering & Computing, vol.17, issue.9, pp.1093-1104, 2006.
DOI : 10.1007/s11517-006-0125-2

E. A. Felton, J. A. Wilson, J. C. Williams, and P. C. Garell, Electrocorticographically controlled brain???computer interfaces using motor and sensory imagery in patients with temporary subdural electrode implants, Journal of Neurosurgery, vol.106, issue.3, pp.495-500, 2007.
DOI : 10.3171/jns.2007.106.3.495

T. Felzer and B. Freisieben, Analyzing EEG signals using the probability estimating guarded neural classifier, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.11, issue.4, pp.361-371, 2003.
DOI : 10.1109/TNSRE.2003.819785

J. H. Friedman, On bias, variance, 0/1-loss, and the curse-of-dimensionality, 1997.

K. Fukunaga, Statistical Pattern Recognition. 2 nd edn, 1990.

F. Galán, M. Nuttin, D. Vanhooydonck, E. Lew, P. W. Ferrez et al., Continuous Brain-Actuated Control of an Intelligent Wheelchair by Human EEG, proceedings, 4th Intl. Brain-Computer Interface Workshop and Training Course, 2008.

Y. Gao, M. J. Black, E. Bienenstock, W. Wu, and J. P. Donoghues, A Quantitative Comparison of Linear and Non-linear Models of Motor Cortical Activity for the Encoding and Decoding of Arm Motions, Proceedings of the 1st International IEEE EMBS Conference on Neural Engineering, 2003.

G. Garcia, T. Ebrahimi, and J. M. Vesin, Correlative exploration of EEG signals for direct brain-computer communication, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., pp.816-819, 2003.
DOI : 10.1109/ICASSP.2003.1200096

G. Garcia, T. Ebrahimi, and J. M. Vesin, Support vector EEG classification in the Fourier and time-frequency correlation domains, First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings., pp.591-594, 2003.
DOI : 10.1109/CNE.2003.1196897

D. Garrett, D. A. Peterson, C. W. Anderson, and M. H. Thaut, Comparison of linear, nonlinear, and feature selection methods for eeg signal classification, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.11, issue.2, 2003.
DOI : 10.1109/TNSRE.2003.814441

P. Geladi and B. R. Kowalski, Partial least-squares regression: a tutorial, Analytica Chimica Acta, vol.185, pp.1-17, 1986.
DOI : 10.1016/0003-2670(86)80028-9

W. Givens, Computation of plane unitary rotations transforming a general matrix to triangular form, J. SIAM, vol.6, issue.1, pp.26-50, 1958.

G. Golub, M. Heath, and G. Wahba, Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter, Technometrics, vol.5, issue.2, pp.215-223, 1979.
DOI : 10.1080/03610927508827223

B. Graimann, J. Huggins, S. Levine, and G. Pfurtscheller, Toward a Direct Brain Interface Based on Human Subdural Recordings and Wavelet-Packet Analysis, IEEE Transactions on Biomedical Engineering, vol.51, issue.6, pp.954-962, 2004.
DOI : 10.1109/TBME.2004.826671

Y. Gu, D. Farina, A. R. Murguialday, K. Dremstrup, P. Montoya et al., Offline identification of imaged speed of wrist movements in paralyzed ALS patients from single-trial EEG, Frontiers in Neuroscience, vol.3, issue.62, pp.1-7, 2009.

G. G. Hamedani and M. N. Tata, On the Determination of the Bivariate Normal Distribution from Distributions of Linear Combinations of the Variables, The American Mathematical Monthly, vol.82, issue.9, pp.913-915, 1975.
DOI : 10.2307/2318494

R. A. Harshman, Foundations of the PARAFAC procedure: Models and conditions for an "explanatory" multi-modal factor analysis, UCLA Working Papers in Phonetics, vol.16, p.84, 1970.

E. Haselsteiner and G. Pfurtscheller, Using time-dependent neural networks for EEG classification, IEEE Transactions on Rehabilitation Engineering, vol.8, issue.4, pp.457-463, 2000.
DOI : 10.1109/86.895948

C. S. Herrmann, Human EEG responses to 1?100???Hz flicker: resonance phenomena in visual cortex and their potential correlation to cognitive phenomena, Experimental Brain Research, vol.137, issue.3-4, pp.346-353, 2001.
DOI : 10.1007/s002210100682

J. M. Hilbe, Logistic Regression Models, 2009.

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, Clinical Neurophysiology, vol.114, issue.3, pp.416-441, 2003.
DOI : 10.1016/S1388-2457(02)00411-X

A. Hiraiwa, K. Shimohara, and Y. Tokunaga, EEG topography recognition by neural networks, IEEE Engineering in Medicine and Biology Magazine, vol.9, issue.3, pp.39-42, 1990.
DOI : 10.1109/51.59211

M. Hirata, T. Yanagisawa, T. Goto, K. Matsushita, T. Suzuki et al., Integrative BMI approach for functional restoration using human electrocorticograms, Neuroscience Research, vol.68, 2010.
DOI : 10.1016/j.neures.2010.07.421

L. R. Hochberg, M. D. Serruya, G. M. Friehs, J. A. Mukand, M. Saleh et al., Neuronal ensemble control of prosthetic devices by a human with tetraplegia, Nature, vol.20, issue.7099, pp.164-171, 2006.
DOI : 10.1038/nature04970

A. E. Hoerl and R. W. Kennard, Ridge Regression: Biased Estimation for Nonorthogonal Problems, Technometrics, vol.24, issue.1, pp.80-86, 2000.
DOI : 10.2307/1909769

U. Hoffmann, Bayesian machine learning applied in a brain-computer interface for disabled users, 2007.

U. Hoffmann, G. Garcia, J. M. Vesin, K. Diserens, and T. Ebrahimi, A Boosting Approach to P300 Detection with Application to Brain-Computer Interfaces, Conference Proceedings. 2nd International IEEE EMBS Conference on Neural Engineering, 2005., 2005.
DOI : 10.1109/CNE.2005.1419562

A. S. Householder, Unitary Triangularization of a Nonsymmetric Matrix, Journal of the ACM, vol.5, issue.4, pp.339-342, 1958.
DOI : 10.1145/320941.320947

URL : https://hal.archives-ouvertes.fr/hal-01316095

T. Hoya, G. Hori, H. Bakardjian, T. Nishimura, T. Suzuki et al., Classification of single trial EEG signals by a combined principal + independent component analysis and probabilistic neural network approach, Proc. ICA2003, pp.197-202, 2003.

J. E. Huggins, B. Graimann, S. Y. Chun, J. Fessler, A. Levine et al., Electrocorticogram as a Brain Computer Interface Signal Source, Towards Brain- Computer Interfacing, pp.129-145, 2007.

J. Miller, K. J. Ojemann, J. G. Wolpaw, J. R. Schalk, and G. , Decoding flexion of individual fingers using electrocorticographic signals in humans, Journal of Neural Engineering, vol.6, issue.6, pp.1-14, 2009.

A. Kübler and K. R. Müller, An introduction to brain computer interfacing, 2007.

A. Kübler, F. Nijboer, J. Mellinger, T. M. Vaughan, H. Pawelzik et al., Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface, Neurology, vol.64, issue.10, pp.641775-1777, 2005.
DOI : 10.1212/01.WNL.0000158616.43002.6D

A. Kübler, B. Kotchoubey, T. Hinterberger, N. Ghanayim, J. Perelmouter et al., The thought translation device: a neurophysiological approach to communication in total motor paralysis, Experimental Brain Research, vol.124, issue.2, 1999.
DOI : 10.1007/s002210050617

R. L. Kutsy, Focal extratemporal epilepsy: clinical features, EEG patterns, and surgical approach, Journal of the Neurological Sciences, vol.166, issue.1, pp.1-15, 1999.
DOI : 10.1016/S0022-510X(99)00107-0

T. N. Lal, M. Schröder, J. Hill, H. Preissl, T. Hinterberger et al., A brain computer interface with online feedback based on magnetoencephalography, Proceedings of the 22nd international conference on Machine learning , ICML '05, pp.465-472, 2005.
DOI : 10.1145/1102351.1102410

E. Lalor, S. P. Kelly, C. Finucane, R. Burke, R. Smith et al., Steady-State VEP-Based Brain-Computer Interface Control in an Immersive 3D Gaming Environment, EURASIP Journal on Advances in Signal Processing, vol.2005, issue.19, pp.3156-3164, 2005.
DOI : 10.1155/ASP.2005.3156

S. Land and J. Friedman, Variable fusion: a new method of adaptive signal regression, 1996.

M. A. Lebedev and M. A. Nicolelis, Brain???machine interfaces: past, present and future, Trends in Neurosciences, vol.29, issue.9, pp.536-546, 2006.
DOI : 10.1016/j.tins.2006.07.004

H. Lee and S. Choi, PCA+HMM+SVM for EEG pattern classification, Proc. 7th Int, 2003.

R. Leeb, V. Settgast, D. W. Fellner, and G. Pfurtscheller, Self-paced exploring of the Austrian National Library through thoughts, International Journal of Bioelectromagnetism, vol.9, pp.237-244, 2007.

S. Lemm, C. Schafer, and G. Curio, BCI Competition 2003???Data Set III: Probabilistic Modeling of Sensorimotor<tex>$mu$</tex>Rhythms for Classification of Imaginary Hand Movements, IEEE Transactions on Biomedical Engineering, vol.51, issue.6, pp.1077-1080, 2004.
DOI : 10.1109/TBME.2004.827076

E. C. Leuthardt, K. J. Miller, G. Schalk, R. P. Rao, and J. G. Ojemann, Electrocorticography-Based Brain Computer Interface???The Seattle Experience, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.14, issue.2, pp.194-198, 2006.
DOI : 10.1109/TNSRE.2006.875536

E. C. Leuthardt, G. Schalk, J. R. Wolpaw, J. G. Ojemann, and D. W. Moran, A brain???computer interface using electrocorticographic signals in humans, Journal of Neural Engineering, vol.1, issue.2, pp.63-71, 2004.
DOI : 10.1088/1741-2560/1/2/001

S. P. Levine, J. E. Huggins, S. L. Bement, R. K. Kushwaha, L. A. Schuh et al., Identification of Electrocorticogram Patterns as the Basis for a Direct Brain Interface, Journal of Clinical Neurophysiology, vol.16, issue.5, pp.16-439, 1999.
DOI : 10.1097/00004691-199909000-00005

J. Li and L. Zhang, Regularized tensor discriminant analysis for single trial EEG classification in BCI Pattern Recognition Letters, pp.31-619, 2010.

J. Li, L. Zhang, D. Tao, H. Sun, and Q. Zhao, A prior neurophysiologic knowledge free tensor-based scheme for single trial EEG classification, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.17, pp.107-115, 2009.

F. Lotte, M. Congedo, A. Lécuyer, F. Lamarche, and B. Arnaldi, A review of classification algorithms for EEG-based brain???computer interfaces, Journal of Neural Engineering, vol.4, issue.2, pp.1-13, 2007.
DOI : 10.1088/1741-2560/4/2/R01

URL : https://hal.archives-ouvertes.fr/inria-00134950

K. A. Ludwig, R. M. Miriani, N. B. Langhals, M. D. Joseph, D. J. Anderson et al., Using a Common Average Reference to Improve Cortical Neuron Recordings From Microelectrode Arrays, Journal of Neurophysiology, vol.101, issue.3, pp.1679-1689, 2009.
DOI : 10.1152/jn.90989.2008

S. Makeig, M. Westerfield, J. Townsend, T. P. Jung, E. Courchesne et al., Functionally independent components of early event-related potentials in a visual spatial attention task, Philosophical Transactions of the Royal Society B: Biological Sciences, vol.354, issue.1387, pp.1135-1144, 1999.
DOI : 10.1098/rstb.1999.0469

E. Margalit, J. D. Weiland, R. E. Clatterbuck, G. Y. Fujii, M. Maia et al., Visual and electrical evoked response recorded from subdural electrodes implanted above the visual cortex in normal dogs under two methods of anesthesia, Journal of Neuroscience Methods, vol.123, issue.2, pp.129-137, 2003.
DOI : 10.1016/S0165-0270(02)00345-X

H. Martens and T. Naes, Maltivariate Calibration, 1989.

J. Martin, The collective electrical behavior of cortical neurons: The electroencephalogram and the mechanisms of epilepsy. Principles of neural science, pp.777-790, 1991.

E. Martínez-montes, J. M. Sánchez-bornot, and P. A. Valdés-sosa, Penalized PARAFAC analysis of spontaneous EEEG recordings, Statistica Sinica, vol.18, pp.1449-1464, 2008.

S. G. Mason and G. E. Birch, Temporal control paradigms for direct brain interfaces ? rethinking the definition of asynchronous and synchronous, Proceedings of HCI International, 2005.

S. G. Mason and G. E. Birch, A brain-controlled switch for asynchronous control applications, IEEE Transactions on Biomedical Engineering, vol.47, issue.10, pp.1297-1307, 2000.
DOI : 10.1109/10.871402

D. J. Mcfarland, D. J. Krusienski, and J. R. Wolpaw, Brain???computer interface signal processing at the Wadsworth Center: mu and sensorimotor beta rhythms, Progress in Brain Research, vol.159, pp.411-419, 2006.
DOI : 10.1016/S0079-6123(06)59026-0

D. J. Mcfarland, L. A. Miner, T. M. Vaughan, and J. R. Wolpaw, Mu and beta rhythm topographies during motor imagery and actual movements, Brain Topography, vol.12, issue.3, p.177, 2000.
DOI : 10.1023/A:1023437823106

D. J. Mcfarland, L. M. Mccane, S. V. David, and J. R. Wolpaw, Spatial filter selection for EEG-based communication, Electroencephalography and Clinical Neurophysiology, vol.103, issue.3, pp.386-394, 1997.
DOI : 10.1016/S0013-4694(97)00022-2

J. R. Millán, F. Renkens, J. Mourino, and W. Gerstner, Noninvasive Brain-Actuated Control of a Mobile Robot by Human EEG, IEEE Transactions on Biomedical Engineering, vol.51, issue.6, pp.1026-1033, 2004.
DOI : 10.1109/TBME.2004.827086

J. R. Millán, J. Mouriño, F. Cincotti, F. Babiloni, M. Varsta et al., Local neural classifier for EEG-basedrecognition of mental tasks, ENNS Int. Joint Conf. on Neural Networks, 2000.

K. Miller, E. Leuthardt, G. Schalk, R. Rao, N. Anderson et al., Spectral Changes in Cortical Surface Potentials during Motor Movement, Journal of Neuroscience, vol.27, issue.9, pp.2424-2432, 2007.
DOI : 10.1523/JNEUROSCI.3886-06.2007

M. Mørup, L. K. Hansen, and S. M. Arnfred, Algorithms for Sparse Nonnegative Tucker Decompositions, Neural Computation, vol.5, issue.8, pp.2112-2131, 2008.
DOI : 10.1016/S0167-8655(01)00070-8

K. R. Müller, M. Krauledat, G. Dornhege, G. Curio, and B. Blankertz, Machine learning techniques for brain?computer interfaces, Biomed. Technol, vol.49, pp.11-22, 2004.

G. R. Müller-putz, V. Kaiser, T. Solis-escalante, and G. Pfurtscheller, Fast set-up asynchronous brain-switch based on detection of foot motor imagery in 1-channel EEG. International Federation for, Medical and Biological Engineering, pp.10-1007, 2010.

O. F. Nascimento, K. Dremstrup, and M. Voigt, Movement-related parameters modulate cortical activity during imaginary isometric plantar-flexions, Experimental Brain Research, vol.85, issue.3, pp.78-90, 2006.
DOI : 10.1007/s00221-005-0247-z

K. Nazarpour, Brain Signal Analysis in Space-Time-Frequency Domain; An Application to Brain Computer Interfacing, 2008.

K. Nazarpour, S. Sanei, L. Shoker, and J. A. Chambers, Parallel space-timefrequency decomposition of eeg signals for brain computer interfacing, 2006.

M. A. Nicolelis, D. Dimitrov, J. M. Carmena, R. Crist, G. Lehew et al., Chronic, multisite, multielectrode recordings in macaque monkeys, Proceedings of the National Academy of Sciences, vol.100, issue.19, pp.11041-11046, 2003.
DOI : 10.1073/pnas.1934665100

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC196923

S. Nieuwenhuis, G. Aston-jones, and J. D. Cohen, Decision making, the P3, and the locus coeruleus--norepinephrine system., Psychological Bulletin, vol.131, issue.4, pp.510-532, 2005.
DOI : 10.1037/0033-2909.131.4.510

J. Nilsson, S. De-jong, and A. K. Smilde, Multiway calibration in 3D QSAR, Journal of Chemometrics, vol.11, issue.6, pp.511-524, 1997.
DOI : 10.1002/(SICI)1099-128X(199711/12)11:6<511::AID-CEM488>3.0.CO;2-W

R. A. Normann, E. M. Maynard, P. J. Rousche, and D. J. Warren, A neural interface for a cortical vision prosthesis, Vision Research, vol.39, issue.15, pp.2577-2587, 1999.
DOI : 10.1016/S0042-6989(99)00040-1

B. Obermeier, C. Guger, C. Neuper, and G. Pfurtscheller, Hidden Markov models for online classification of single trial EEG data, Pattern Recognition Letters, vol.22, issue.12, pp.1299-1309, 2001.
DOI : 10.1016/S0167-8655(01)00075-7

B. Obermaier, C. Neuper, C. Guger, and G. Pfurtscheller, Information transfer rate in a five-classes brain-computer interface, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.9, issue.3, pp.283-288, 2000.
DOI : 10.1109/7333.948456

A. V. Oppenheim and R. W. Schafer, Discrete-time signal processing, 1989.

R. Palaniappan, Brain Computer Interface Design Using Band Powers Extracted During Mental Tasks, Conference Proceedings. 2nd International IEEE EMBS Conference on Neural Engineering, 2005., 2005.
DOI : 10.1109/CNE.2005.1419622

R. Palaniappan, R. Paramesran, S. Nishida, and N. Saiwaki, A new brain-computer interface design using fuzzy ARTMAP, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.10, issue.3, pp.140-148, 2002.
DOI : 10.1109/TNSRE.2002.802854

W. D. Penny, S. J. Roberts, E. A. Curran, and M. J. Stokes, EEG-based communication: a pattern recognition approach, IEEE Transactions on Rehabilitation Engineering, vol.8, issue.2, pp.214-215, 2000.
DOI : 10.1109/86.847820

G. Pfurtscheller, B. Z. Allison, C. Brunner, G. Bauernfeind, T. Solis-escalante et al., The hybrid BCI, Frontiers in Neuroscience, vol.4, issue.42, pp.1-11, 2010.
DOI : 10.3389/fnpro.2010.00003

G. Pfurtscheller, T. Solis-escalante, R. Ortner, P. Linortner, and G. R. Muller-putz, Self-Paced Operation of an SSVEP-Based Orthosis With and Without an Imagery-Based &#x201C;Brain Switch:&#x201D; A Feasibility Study Towards a Hybrid BCI, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.18, issue.4, pp.409-414, 2010.
DOI : 10.1109/TNSRE.2010.2040837

G. Pfurtscheller and T. Solis-escalante, Could the beta rebound in the EEG be suitable to realize a ???brain switch????, Clinical Neurophysiology, vol.120, issue.1, pp.24-29, 2009.
DOI : 10.1016/j.clinph.2008.09.027

G. Pfurtscheller, C. Neuper, C. Brunner, and F. H. Lopes-da-silva, Beta rebound after different types of motor imagery in man, Neuroscience Letters, vol.378, issue.3, pp.156-159, 2005.
DOI : 10.1016/j.neulet.2004.12.034

G. Pfurtscheller, B. Graimann, J. E. Huggins, and S. P. Levine, Chapter 62 Brain-computer communication based on the dynamics of brain oscillations, Suppl Clin Neurophysiol, vol.57, pp.583-591, 2004.
DOI : 10.1016/S1567-424X(09)70398-8

G. Pfurtscheller and C. Neuper, Motor imagery and direct brain-computer communication, Proceedings of the IEEE, vol.89, issue.7, pp.1123-1134, 2001.
DOI : 10.1109/5.939829

G. Pfurtscheller, EEG event-related desynchronization (ERD) and event-related synchronization (ERS) Electroencephalography: Basic Principles, Clinical References Brain-Computer Interface with cortical electrical activity recording 176, 1999.

G. Pfurtscheller and F. H. Da-silva, Event-Related Desynchronisation, Handbook of Electroencephalogr, Clin. Neurophysiol. Revised Series, 1999.

G. Pfurtscheller, D. Flotzinger, and J. Kalcher, Brain-Computer Interface???a new communication device for handicapped persons, Journal of Microcomputer Applications, vol.16, issue.3, pp.293-299, 1993.
DOI : 10.1006/jmca.1993.1030

J. Pine, A History of MEA Development Advances in Network Electrophysiology Using Multi-Electrode Arrays, pp.3-23, 2006.

T. Pistohl, T. Ball, A. Schulze-bonhage, A. Aertse, and C. Mehring, Prediction of arm movement trajectories from ECoG-recordings in humans, Journal of Neuroscience Methods, vol.167, issue.1, pp.167-105, 2008.
DOI : 10.1016/j.jneumeth.2007.10.001

K. Qian, P. Nikolov, D. Huang, D. Y. Fei, X. Chen et al., A motor imagerybased online interactive brain-controlled switch: paradigm development and preliminary test, Clinical Neurophysiology, vol.121, pp.1303-1313, 2010.

J. Qin, Y. Li, and A. Cichocki, ICA and Committee Machine-Based Algorithm for Cursor Control in a BCI System, Lecture Notes in Computer Science, 2005.
DOI : 10.1007/11427391_156

S. J. Qin, Recursive PLS algorithms for adaptive data modeling. Computers chem, 1998.

L. R. Rabiner, A tutorial on hidden Markov models and selected applications in speech recognition, Proc. IEEE, pp.257-286, 1989.

A. Rakotomamonjy, V. Guigue, G. Mallet, and V. Alvarado, Ensemble of SVMs for Improving Brain Computer Interface P300 Speller Performances, International Conference on Artificial Neural Networks, 2005.
DOI : 10.1007/11550822_8

H. Ramoser, J. Muller-gerking, and G. Pfurtscheller, Optimal spatial filtering of single trial EEG during imagined hand movement, IEEE Transactions on Rehabilitation Engineering, vol.8, issue.4, pp.441-446, 2000.
DOI : 10.1109/86.895946

N. Ramsey, M. Van-de-heuvel, K. Kho, and F. Leijten, Towards Human BCI Applications Based on Cognitive Brain Systems: An Investigation of Neural Signals Recorded From the Dorsolateral Prefrontal Cortex, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.14, issue.2, pp.214-217, 2006.
DOI : 10.1109/TNSRE.2006.875582

C. J. Rijsbergen, Information retrieval, 1979.

A. G. Rouse and D. W. Moran, Neural adaptation of epidural electrocorticographic (EECoG) signals during closed-loop brain computer interface (BCI) tasks, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.5514-5517, 2009.
DOI : 10.1109/IEMBS.2009.5333180

V. Salanova, H. H. Morris, P. C. Van-ness, H. Luders, D. Dinner et al., Comparison of Scalp Electroencephalogram With Subdural Electrocorticogram Recordings and Functional Mapping in Frontal Lobe Epilepsy, Archives of Neurology, vol.50, issue.3, pp.294-299, 1993.
DOI : 10.1001/archneur.1993.00540030058015

F. Sauter-starace, O. Bibari, F. Berger, P. Caillat, and A. L. Benabid, ECoG recordings of a non-human primate using carbon nanotubes electrodes on a flexible polyimide implant, 2009 4th International IEEE/EMBS Conference on Neural Engineering, 2009.
DOI : 10.1109/NER.2009.5109247

G. Schalk, K. J. Miller, N. R. Anderson, J. A. Wilson, M. D. Smyth et al., Two-dimensional movement control using electrocorticographic signals in humans, Journal of Neural Engineering, vol.5, issue.1, pp.75-84, 2008.
DOI : 10.1088/1741-2560/5/1/008

R. Scherer, F. Lee, A. Schlgl, R. Leeb, H. Bischof et al., Toward Self-Paced Brain&#x2013;Computer Communication: Navigation Through Virtual Worlds, IEEE Transactions on Biomedical Engineering, vol.55, issue.2, pp.675-682, 2008.
DOI : 10.1109/TBME.2007.903709

R. Scherer, A. Schloegl, F. Lee, H. Bischof, J. Jan?a et al., The Self-Paced Graz Brain-Computer Interface: Methods and Applications, Computational Intelligence and Neuroscience, vol.2007, p.79826, 2007.
DOI : 10.1109/TBME.2004.827078

R. Scherer, G. R. Müller, C. Neuper, B. Graimann, and G. Pfurtscheller, An Asynchronously Controlled EEG-Based Virtual Keyboard: Improvement of the Spelling Rate, IEEE Transactions on Biomedical Engineering, vol.51, issue.6, pp.979-984, 2004.
DOI : 10.1109/TBME.2004.827062

R. Scherer, B. Graimann, J. E. Huggins, S. P. Levine, and G. Pfurtscheller, Frequency component selection for an ECoG-based brain-computer interface, 2003.

A. Schlögl, J. Kronegg, J. Huggins, and S. G. Mason, Evaluation criteria in BCI research, Towards Brain-Computer Interfacing (G. Dornhege, 2007.

A. Schlögl, F. Lee, H. Bischof, and G. Pfurtscheller, Characterization of four-class motor imagery EEG data for the BCI-competition 2005, Journal of Neural Engineering, vol.2, issue.4, pp.14-22, 2005.
DOI : 10.1088/1741-2560/2/4/L02

M. Schmidt, Least Squares Optimization with L1-Norm Regularization, Cs542B Project Report, 2005.

L. Schuh and M. Drury, Intraoperative electrocorticography and direct cortical electrical stimulation, Seminars in Anesthesia, Perioperative Medicine and Pain, vol.16, issue.1, pp.46-55, 1996.
DOI : 10.1016/S0277-0326(97)80007-4

A. B. Schwartz, CORTICAL NEURAL PROSTHETICS, Annual Review of Neuroscience, vol.27, issue.1, pp.487-507, 2004.
DOI : 10.1146/annurev.neuro.27.070203.144233

G. Schwartz, Estimating the Dimension of a Model, The Annals of Statistics, vol.6, issue.2, pp.461-464, 1978.
DOI : 10.1214/aos/1176344136

B. A. Shenoi, Introduction to digital signal processing and filter design, 2006.
DOI : 10.1002/0471656372

J. Sherwood and R. Derakhshani, On classifiability of wavelet features for EEG-based brain-computer interfaces, 2009 International Joint Conference on Neural Networks, pp.2508-2515, 2009.
DOI : 10.1109/IJCNN.2009.5178939

S. K. Shevade and S. S. Keerthi, A simple and efficient algorithm for gene selection using sparse logistic regression, Bioinformatics, vol.19, issue.17, pp.2246-2253, 2003.
DOI : 10.1093/bioinformatics/btg308

R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi et al., Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain???computer interface, NeuroImage, vol.34, issue.4, pp.1416-1427, 2007.
DOI : 10.1016/j.neuroimage.2006.11.005

R. Sitaram, Y. Hoshi, and C. Guan, Near infrared spectroscopy based braincomputer interfaces, 2005.

S. Solhjoo, A. M. Nasrabadi, and M. R. Golpayegani, Classification of chaotic signals using HMM classifiers: EEG-based mental task classification, Proc. European Signal Processing Conference, 2005.

S. Solhjoo and M. H. Moradi, Mental task recognition: a comparison between some of classification methods, 2004.

T. Solis-escalante, G. R. Müller-putz, C. Brunner, V. Kaiser, and G. Pfurtscheller, Analysis of sensorimotor rhythms for the implementation of a brain switch for healthy subjects, Biomedical Signal Processing and Control, vol.5, issue.1, pp.15-20, 2010.
DOI : 10.1016/j.bspc.2009.09.002

K. C. Squires, C. Wickens, N. K. Squires, and E. Donchin, The effect of stimulus sequence on the waveform of the cortical event-related potential, Science, vol.193, issue.4258, pp.1142-1146, 1976.
DOI : 10.1126/science.959831

R. Srinivasan, Methods to improve the spatial resolution of EEG, International Journal of Bioelectromagnetism, vol.1, pp.102-111, 1999.

E. E. Sutter, The brain response interface: communication through visually-induced electrical brain responses, Journal of Microcomputer Applications, vol.15, issue.1, pp.31-45, 1992.
DOI : 10.1016/0745-7138(92)90045-7

M. Tangermann, Contributions from mathematics: Applying machine learning algorithms to BCI, Brain Computer Interfacing, 2008.

M. Tangermann, Feature Selection for Brain-Computer Interfaces, 2007.

D. M. Taylor, The importance of online error correction and feed-forward adjustment in brain-machine interfaces for restoration of movement, Towards Brain-Computer Interfacing (G. Dornhege, 2007.

D. Taylor, S. Tillery, and A. Schwartz, Direct Cortical Control of 3D Neuroprosthetic Devices, Science, vol.296, issue.5574, pp.1829-1832, 2002.
DOI : 10.1126/science.1070291

A. Teolis, Computational Signal Processing with Wavelets, 1998.
DOI : 10.1007/978-1-4612-4142-3

R. Tibshirani, Regression shrinkage and variable selection via the lasso, J. Roy. Statist. Soc. Ser. B, vol.58, pp.267-288, 1996.

N. F. Ramsey, Gain of the human dura in vivo and its effects on invasive brain signal feature detection, J Neurosci Methods, vol.187, issue.2, pp.270-279, 2010.

G. Townsend, B. Graimann, and G. Pfurtscheller, Continuous EEG Classification During Motor Imagery???Simulation of an Asynchronous BCI, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.12, issue.2, 2004.
DOI : 10.1109/TNSRE.2004.827220

C. Vidaurre, N. Krämer, B. Blankertz, and A. Schlögl, Time Domain Parameters as a feature for EEG-based Brain???Computer Interfaces, Neural Networks, vol.22, issue.9, pp.1313-1319, 2009.
DOI : 10.1016/j.neunet.2009.07.020

W. G. Walter, R. Cooper, V. J. Aldridge, W. C. Mccallum, and A. L. Winter, Contingent Negative Variation : An Electric Sign of Sensori-Motor Association and Expectancy in the Human Brain, Nature, vol.15, issue.4943, pp.380-384, 1964.
DOI : 10.1038/203380a0

Y. Wang, R. Wang, X. Gao, B. Hong, and S. Gao, A Practical VEP-Based Brain???Computer Interface, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.14, issue.2, pp.234-239, 2006.
DOI : 10.1109/TNSRE.2006.875576

Y. Wang, Z. Zhang, Y. Li, X. Gao, S. Gao et al., BCI Competition 2003???Data Set IV: An Algorithm Based on CSSD and FDA for Classifying Single-Trial EEG, IEEE Transactions on Biomedical Engineering, vol.51, issue.6, 2004.
DOI : 10.1109/TBME.2004.826697

J. Wessberg, C. R. Stambaugh, J. D. Kralik, P. D. Beck, M. Laubach et al., Real-time prediction of hand trajectory by ensembles of cortical neurons in primates, Nature, vol.408, issue.6810, pp.361-365, 2000.

J. C. Williams, R. L. Rennaker, and D. R. Kipke, Long-term neural recording characteristics of wire microelectrode arrays implanted in cerebral cortex, Brain Research Protocols, vol.4, issue.3, 1999.
DOI : 10.1016/S1385-299X(99)00034-3

J. A. Wilson, E. A. Felton, P. C. Garell, G. Schalk, and J. C. Williams, ECoG Factors Underlying Multimodal Control of a Brain???Computer Interface, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.14, issue.2, pp.246-250, 2006.
DOI : 10.1109/TNSRE.2006.875570

J. R. Wolpaw and D. J. Mcfarland, Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans, Proceedings of the National Academy of Sciences, vol.101, issue.51, pp.17849-17854, 2004.
DOI : 10.1073/pnas.0403504101

J. R. Wolpaw, D. J. Mcfarland, T. M. Vaughan, and G. Schalk, The wadsworth center brain-computer interface (bci) research and development program, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.11, issue.2, pp.1-4, 2003.
DOI : 10.1109/TNSRE.2003.814442

J. R. Wolpaw, N. Birbaumerc, D. J. Mcfarlanda, G. Pfurtschellere, and T. M. Vaughana, Brain???computer interfaces for communication and control, Clinical Neurophysiology, vol.113, issue.6, pp.767-791, 2002.
DOI : 10.1016/S1388-2457(02)00057-3

J. R. Wolpaw, D. J. Mcfarland, G. W. Neatb, and C. A. Forneris, An EEG-based brain-computer interface for cursor control, Electroencephalography and Clinical Neurophysiology, vol.78, issue.3, pp.252-259, 1991.
DOI : 10.1016/0013-4694(91)90040-B

D. H. Wolpert, Stacked generalization, Neural Networks, vol.5, issue.2, pp.241-259, 1992.
DOI : 10.1016/S0893-6080(05)80023-1

W. Wu, Y. Gao, E. Bienenstock, J. P. Donoghues, and M. J. Black, Bayesian Population Decoding of Motor Cortical Activity Using a Kalman Filter, Neural Computation, vol.79, issue.1, pp.80-118, 2006.
DOI : 10.1109/TBME.2004.826666

F. Yates, The analysis of replicated experiments when the field results are incomplete. The empire journal of experimental agriculture, p.129, 1933.

E. Yom-tov and G. F. Inbar, Detection of movement-related potentials from the electro-encephalogram for possible use in a brain-computer interface, Medical & Biological Engineering & Computing, vol.85, issue.1, pp.85-93, 2003.
DOI : 10.1007/BF02343543

H. P. Zaveri, W. J. Williams, L. D. Iasemidis, and J. C. Sackellares, Time-frequency representation of electrocorticograms in temporal lobe epilepsy, IEEE Transactions on Biomedical Engineering, vol.39, issue.5, pp.39-502, 1992.
DOI : 10.1109/10.135544

H. Zhang and C. Guan, A maximum mutual information approach for constructing a 1D continuous control signal at a self-paced brain???computer interface, Journal of Neural Engineering, vol.7, issue.5, pp.1-11, 2010.
DOI : 10.1088/1741-2560/7/5/056009

Q. Zhao, C. F. Caiafa, A. Cichocki, L. Zhang, and A. H. Phan, Slice Oriented Tensor Decomposition of EEG Data for Feature Extraction in Space, Frequency and Time Domains, Lecture Notes in Computer Science, vol.5863, pp.221-228, 2009.
DOI : 10.1007/978-3-642-10677-4_25

Q. Zhao, L. Zhang, and A. Cichocki, EEG-based asynchronous BCI control of a car in 3D virtual reality environments, Chinese Science Bulletin, vol.51, issue.6, pp.78-87, 2008.
DOI : 10.1007/s11434-008-0547-3

J. Zhu and T. Yao, An evaluation of statistical spam filtering techniques, ACM Transactions on Asian Language Information Processing (TALIP), vol.3, issue.4, pp.243-269, 2004.

H. Zou and T. Hastie, Regularization and variable selection via the elastic net, J, 2005.