B. Z. Allison and J. A. Pineda, ERPs evoked by different matrix sizes: implications for a brain computer interface (bci) system, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.11, issue.2, pp.110-113, 2003.
DOI : 10.1109/TNSRE.2003.814448

B. Z. Allison and J. A. Pineda, Effects of SOA and flash pattern manipulations on ERPs, performance, and preference: Implications for a BCI system, International Journal of Psychophysiology, vol.59, issue.2, pp.127-140, 2006.
DOI : 10.1016/j.ijpsycho.2005.02.007

Y. Arbel, A. Murphy, and E. Donchin, On the Utility of Positive and Negative Feedback in a Paired-associate Learning Task, Journal of Cognitive Neuroscience, vol.26, issue.7, pp.1445-1453, 2014.
DOI : 10.1093/cercor/bhp224

X. Artusi, I. K. , N. Lucas, M. Farina, and D. , Theoretical framework and simulation of an adaptive bci based on movement-related and error potentials, Proc. of the 5th Int. BCI Workshop and Training Course, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00660468

C. Bellebaum and I. Daum, Learning-related changes in reward expectancy are reflected in the feedback-related negativity, European Journal of Neuroscience, vol.7, issue.7, pp.1123-1835, 2008.
DOI : 10.1523/JNEUROSCI.4537-03.2004

B. Blankertz, K. R. Müller, D. J. Krusienski, G. Schalk, J. R. Wolpaw et al., The BCI Competition III: Validating Alternative Approaches to Actual BCI Problems, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.14, issue.2, pp.152-159, 2006.
DOI : 10.1109/TNSRE.2006.875642

B. Blankertz, C. Schäfer, G. Dornhege, and G. Curio, Single Trial Detection of EEG Error Potentials: A Tool for Increasing BCI Transmission Rates, ICANN '02 Proc. of the Int. Conf. on Artificial Neural Networks, pp.1137-1143, 2002.
DOI : 10.1007/3-540-46084-5_184

B. Blankertz, R. Tomioka, S. Lemm, M. Kawanabe, and K. Uller, Optimizing Spatial filters for Robust EEG Single-Trial Analysis, IEEE Signal Processing Magazine, vol.25, issue.1, pp.41-56, 2008.
DOI : 10.1109/MSP.2008.4408441

G. Buccino, S. Vogt, A. Ritzl, G. Fink, K. Zilles et al., Neural Circuits Underlying Imitation Learning of Hand Actions, Neuron, vol.42, issue.2, pp.323-334, 2004.
DOI : 10.1016/S0896-6273(04)00181-3

T. Chaminade and J. Decety, Leader or follower? Involvement of the inferior parietal lobule in agency, NeuroReport, vol.13, issue.15, pp.1975-1978, 2002.
DOI : 10.1097/00001756-200210280-00029

C. Chang and C. J. Lin, LIBSVM, ACM Transactions on Intelligent Systems and Technology, vol.2, issue.3, pp.1-27, 2011.
DOI : 10.1145/1961189.1961199

M. X. Cohen and C. Ranganath, Reinforcement Learning Signals Predict Future Decisions, Journal of Neuroscience, vol.27, issue.2, pp.371-378, 2007.
DOI : 10.1523/JNEUROSCI.4421-06.2007

C. Cortes and V. Vapnik, Support-vector networks, Machine Learning, vol.1, issue.3, pp.273-297, 1995.
DOI : 10.1007/BF00994018

E. A. Curran and M. J. Stokes, Learning to control brain activity: A review of the production and control of EEG components for driving brain???computer interface (BCI) systems, Brain and Cognition, vol.51, issue.3, pp.326-336, 2003.
DOI : 10.1016/S0278-2626(03)00036-8

J. Danckert, S. Ferber, T. Doherty, H. Steinmetz, D. Nicolle et al., Selective non-lateralized impairment of motor imagery following right parietal damage, Neurocase, vol.8, pp.194-204, 2002.

J. Decety, T. Chaminade, J. Grèzes, and A. N. Meltzoff, A PET Exploration of the Neural Mechanisms Involved in Reciprocal Imitation, NeuroImage, vol.15, issue.1, pp.265-272, 2002.
DOI : 10.1006/nimg.2001.0938
URL : https://hal.archives-ouvertes.fr/inserm-00000001

J. Decety, J. Grèzes, N. Costes, D. Perani, M. Jeannerod et al., Brain activity during observation of actions. Influence of action content and subject's strategy, Brain, vol.120, issue.10, pp.1763-1777, 1997.
DOI : 10.1093/brain/120.10.1763
URL : https://hal.archives-ouvertes.fr/hal-00655257

E. Donchin and M. Coles, Is the P300 component a manifestation of context updating?, Behavioral and Brain Sciences, vol.2, issue.03, pp.355-425, 1988.
DOI : 10.1016/0001-6918(83)90016-1

M. A. Eckert, V. Menon, A. Walczak, J. Ahlstrom, S. Denslow et al., At the heart of the ventral attention system: The right anterior insula, Human Brain Mapping, vol.1, issue.8, pp.2530-2541, 2009.
DOI : 10.1002/hbm.20688

P. Ferrez, Error-related EEG potentials in brain-computer interfaces, 2007.

P. Ferrez and J. Millán, You are wrong!?automatic detection of interaction errors from brain waves, Proc. 19th Int. Joint Conference on Artificial Intelligence, pp.1413-1418, 2005.

P. Ferrez and J. Millán, EEG-based brain-computer interaction: Improved accuracy by automatic single-trial error detection, Advances in Neural Information Processing Systems, pp.441-448, 2007.

P. Ferrez and J. Millán, Error-Related EEG Potentials Generated During Simulated Brain–Computer Interaction, IEEE Transactions on Biomedical Engineering, vol.55, issue.3, pp.923-929, 2008.
DOI : 10.1109/TBME.2007.908083

R. A. Fischer, THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS, Annals of Eugenics, vol.59, issue.2, pp.179-188, 1936.
DOI : 10.1111/j.1469-1809.1936.tb02137.x

F. G. Flynn, D. F. Benson, and A. Ardila, Anatomy of the insula functional and clinical correlates, Aphasiology, vol.14, issue.1, pp.55-78, 1999.
DOI : 10.1016/S0006-8993(97)00284-9

M. Fuchs, J. Kastner, M. Wagner, S. Hawes, and J. Ebersole, A standardized boundary element method volume conductor model, Clinical Neurophysiology, vol.113, issue.5, pp.702-712, 2002.
DOI : 10.1016/S1388-2457(02)00030-5

W. J. Gehring and A. R. Willoughby, The Medial Frontal Cortex and the Rapid Processing of Monetary Gains and Losses, Science, vol.295, issue.5563, pp.2279-2282, 2002.
DOI : 10.1126/science.1066893

J. Grèzes, N. Costes, and J. Decety, TOP DOWN EFFECT OF STRATEGY ON THE PERCEPTION OF HUMAN BIOLOGICAL MOTION: A PET INVESTIGATION, Cognitive Neuropsychology, vol.43, issue.6-8, pp.553-582, 1998.
DOI : 10.1093/cercor/3.2.79

I. Guyon, J. Weston, S. Barnill, and V. Vapnik, Gene selection for cancer classification using support vector machines, Machine Learning, vol.46, issue.1/3, pp.389-422, 2002.
DOI : 10.1023/A:1012487302797

G. Hajcak, J. S. Moser, C. B. Holroyd, and R. F. Simons, It's worse than you thought: The feedback negativity and violations of reward prediction in gambling tasks, Psychophysiology, vol.2, issue.6, pp.905-912, 2007.
DOI : 10.1523/JNEUROSCI.4537-03.2004

B. Hjorth, An on-line transformation of EEG scalp potentials into orthogonal source derivations, Electroencephalography and Clinical Neurophysiology, vol.39, issue.5, pp.526-230, 1975.
DOI : 10.1016/0013-4694(75)90056-5

C. B. Holroyd and M. G. Coles, The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity., Psychological Review, vol.109, issue.4, pp.679-709, 2002.
DOI : 10.1037/0033-295X.109.4.679

C. B. Holroyd, O. E. Krigolson, R. Baker, S. Lee, and J. Gibson, When is an error not a prediction error? An electrophysiological investigation, Cognitive, Affective, & Behavioral Neuroscience, vol.9, issue.1, pp.59-80, 2009.
DOI : 10.3758/CABN.9.1.59

C. B. Holroyd, S. Nieuwenhuis, N. Yeung, and J. D. Cohen, Errors in reward prediction are reflected in the event-related brain potential, NeuroReport, vol.14, issue.18, pp.2481-2484, 2003.
DOI : 10.1097/00001756-200312190-00037

J. Kaiser, On a simple algorithm to calculate the 'energy' of a signal, International Conference on Acoustics, Speech, and Signal Processing, pp.381-384, 1990.
DOI : 10.1109/ICASSP.1990.115702

T. Klein, T. Endrass, N. Kathmann, J. Neumann, D. Y. Von-cramon et al., Neural correlates of error awareness, NeuroImage, vol.34, issue.4, pp.1774-1781, 2007.
DOI : 10.1016/j.neuroimage.2006.11.014

A. S. Koerner, Q. Zhang, and V. R. De-sa, The effect of real-time feedback valence on motor imagery performance, Frontiers in Neurosciences, vol.8, 2014.

A. Kreiglinger, C. Neuper, and G. Müller-putz, Implementation of error detection into the graz-brain-computer interface, the interaction error potential, 2009.

A. Kreiglinger, C. Neuper, and G. Müller-putz, Error potential detection during continuous movement of an artificial arm controlled by brain???computer interface, Medical & Biological Engineering & Computing, vol.113, issue.12, pp.223-230, 2012.
DOI : 10.1007/s11517-011-0858-4

A. Kreilinger, C. Neuper, and G. Müller-putz, Detection of error potentials during a car-game with combined continuous and discrete feedback, Proc. of the 5th Int. BCI Workshop and Training Course, 2011.

O. E. Krigolson and C. B. Holroyd, Evidence for hierarchical error processing in the human brain, Neuroscience, vol.137, issue.1, pp.13-17, 2006.
DOI : 10.1016/j.neuroscience.2005.10.064

O. E. Krigolson and C. B. Holroyd, Hierarchical error processing: Different errors, different systems, Brain Research, vol.1155, pp.70-80, 2007.
DOI : 10.1016/j.brainres.2007.04.024

F. Lotte, M. Congedo, A. Lécuyer, F. Lamarche, and .. B. , 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

F. Lotte, A. Lécuyer, and B. Arnaldi, FuRIA: A Novel Feature Extraction Algorithm for Brain-Computer Interfaces using Inverse Models and Fuzzy Regions of Interest, 2007 3rd International IEEE/EMBS Conference on Neural Engineering, pp.175-178, 2007.
DOI : 10.1109/CNE.2007.369640
URL : https://hal.archives-ouvertes.fr/inria-00134961

F. Lotte, A. Lécuyer, and B. Arnaldi, FuRIA: An Inverse Solution Based Feature Extraction Algorithm Using Fuzzy Set Theory for Brain–Computer Interfaces, IEEE Transactions on Signal Processing, vol.57, issue.8, pp.3253-3263, 2009.
DOI : 10.1109/TSP.2009.2020752

F. Lotte, A. Lécuyer, and C. Guan, Towards a fully interpretable EEG-based bci system, Proc. 4th International Brain-Computer Interface meeting, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00504658

W. H. Miltner, C. H. Braun, and M. G. Coles, Event-Related Brain Potentials Following Incorrect Feedback in a Time-Estimation Task: Evidence for a ???Generic??? Neural System for Error Detection, Journal of Cognitive Neuroscience, vol.9, issue.6, pp.788-798, 1997.
DOI : 10.1016/0013-4694(78)90027-5

F. Nijboer, N. Birbaumer, and A. Kübler, The influence of psychological state and motivation on brain-computer interface performance in patients with amyotrophic lateral schlerosis -a longtitudinal study, Frontiers in Neuroscience, vol.4, 2010.

D. Papo, P. Baudonnì-ere, L. Hugueville, and J. Caverni, Feedback in Hypothesis Testing: An ERP Study, Journal of Cognitive Neuroscience, vol.80, issue.4, pp.508-522, 2003.
DOI : 10.1080/17470216008416717
URL : https://hal.archives-ouvertes.fr/hal-01441355

R. Pascual-marqui, Low resolution brain electromagnetic tomography (LORETA), Electroencephalography and Clinical Neurophysiology, vol.103, issue.1, 2003.
DOI : 10.1016/S0013-4694(97)88020-4

M. Perrin, E. Maby, R. Bouet, O. Bertrand, and J. Mattout, Detecting and interpreting responses to feedback in bci, Proc. of the 5th Int. BCI Workshop and Training Course, 2011.

M. Perrin, E. Maby, S. Daligault, O. Bertrand, and J. Mattout, Objective and subjective evaluation of online error correction during p300-based spelling Advances in Human-Computer Interaction, 2012.

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

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

J. Polich, Updating P300: An integrative theory of P3a and P3b, Clinical Neurophysiology, vol.118, issue.10, pp.2128-2148, 2007.
DOI : 10.1016/j.clinph.2007.04.019

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

Y. Renard, F. Lotte, G. Gibert, M. Congedo, E. Maby et al., OpenViBE: An Open-Source Software Platform to Design, Test, and Use Brain???Computer Interfaces in Real and Virtual Environments, Presence: Teleoperators and Virtual Environments, vol.2008, issue.3, pp.35-53, 2010.
DOI : 10.1016/j.patrec.2007.10.009
URL : https://hal.archives-ouvertes.fr/hal-00477153

B. Reuderink, M. Poel, and A. Nijholt, The Impact of Loss of Control on Movement BCIs, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.19, issue.6, pp.628-367, 2011.
DOI : 10.1109/TNSRE.2011.2166562

K. Ridderinkhof, M. Ullsperger, E. Crone, and S. Nieuwenhuis, The Role of the Medial Frontal Cortex in Cognitive Control, Science, vol.306, issue.5695, pp.443-447, 2004.
DOI : 10.1126/science.1100301

G. Sanchez, J. Daunizeau, E. Maby, O. Bertrand, A. Bompas et al., Toward a New Application of Real-Time Electrophysiology: Online Optimization of Cognitive Neurosciences Hypothesis Testing, Brain Sciences, vol.4, issue.1, pp.49-72, 2014.
DOI : 10.3390/brainsci4010049
URL : https://hal.archives-ouvertes.fr/hal-00941183

A. Schlögl and C. Brunner, BioSig: A Free and Open Source Software Library for BCI Research, Computer, vol.41, issue.10, pp.44-50, 2008.
DOI : 10.1109/MC.2008.407

N. M. Schmidt, B. Blankertz, and M. S. Treder, Online detection of errorrelated potentials boosts the performance of mental typewriters, 2012.

J. Schwoebel, C. Boronat, and H. Branch-coslett, The man who executed ???imagined??? movements: Evidence for dissociable components of the body schema, Brain and Cognition, vol.50, issue.1, pp.1-6, 2002.
DOI : 10.1016/S0278-2626(02)00005-2

P. Shenoy, M. Krauledat, B. Blankertz, R. P. Rao, and K. Uller, Towards adaptive classification for BCI, Journal of Neural Engineering, vol.3, issue.1, p.13, 2006.
DOI : 10.1088/1741-2560/3/1/R02

A. Sirigu, J. Duhamel, L. Cohen, B. Pillon, B. Dubois et al., The Mental Representation of Hand Movements After Parietal Cortex Damage, Science, vol.273, issue.5281, pp.1564-1568, 1996.
DOI : 10.1126/science.273.5281.1564

S. Solnik, P. Rider, K. Steinwg, P. Devita, and T. Hortobágyi, Teager???Kaiser energy operator signal conditioning improves EMG onset detection, European Journal of Applied Physiology, vol.21, issue.3, pp.489-498, 2010.
DOI : 10.1007/s00421-010-1521-8

E. Thomas, M. Dyson, and M. Clerc, An analysis of performance evaluation for motor-imagery based BCI, Journal of Neural Engineering, vol.10, issue.3, 2013.
DOI : 10.1088/1741-2560/10/3/031001
URL : https://hal.archives-ouvertes.fr/hal-00821971

M. Ullsperger, A. G. Fischer, R. Nigbur, and T. Endrass, Neural mechanisms and temporal dynamics of performance monitoring, Trends in Cognitive Sciences, vol.18, issue.5, pp.259-267, 2014.
DOI : 10.1016/j.tics.2014.02.009

M. Ullsperger, H. Harsay, J. Wessel, and K. Ridderinkhof, Conscious perception of errors and its relation to the anterior insula, Brain Structure and Function, vol.46, issue.4, pp.629-643, 2010.
DOI : 10.1007/s00429-010-0261-1

M. Ullsperger and D. Y. Von-cramon, Error monitoring using external feedback: Specific roles of the habenular complex, the reward system, and the cingulate motor area revealed by functional magnetic resonance imaging, The Journal of Neuroscience, vol.23, pp.4308-4314, 2003.

M. Ullsperger and D. Y. Von-cramon, Neuroimaging of Performance Monitoring: Error Detection and Beyond, Cortex, vol.40, issue.4-5, pp.593-604, 2004.
DOI : 10.1016/S0010-9452(08)70155-2

C. Vidaurre, A. Schlögl, R. Cabeza, R. Scherer, and G. Pfurtscheller, A Fully On-Line Adaptive BCI, IEEE Transactions on Biomedical Engineering, vol.53, issue.6, pp.1214-1219, 2006.
DOI : 10.1109/TBME.2006.873542

C. Vidaurre, A. Schlögl, R. Cabeza, R. Scherer, and G. Pfurtscheller, Study of On-Line Adaptive Discriminant Analysis for EEG-Based Brain Computer Interfaces, IEEE Transactions on Biomedical Engineering, vol.54, issue.3, pp.550-556, 2007.
DOI : 10.1109/TBME.2006.888836

M. M. Walsh and J. R. Anderson, Learning from delayed feedback: neural responses in temporal credit assignment, Cognitive, Affective, & Behavioral Neuroscience, vol.5, issue.2, pp.131-143, 2011.
DOI : 10.3758/s13415-011-0027-0

M. M. Walsh and J. R. Anderson, Modulation of the feedback-related negativity by instruction and experience, Proceedings of the National Academy of Sciences, vol.108, issue.47, pp.19048-19053, 2011.
DOI : 10.1073/pnas.1117189108

M. M. Walsh and J. R. Anderson, Learning from experience: Event-related potential correlates of reward processing, neural adaptation, and behavioral choice, Neuroscience & Biobehavioral Reviews, vol.36, issue.8, pp.1870-1884, 2012.
DOI : 10.1016/j.neubiorev.2012.05.008

T. Zander and S. Jatzev, Context-aware brain???computer interfaces: exploring the information space of user, technical system and environment, Journal of Neural Engineering, vol.9, issue.1, 2012.
DOI : 10.1088/1741-2560/9/1/016003

T. Zander and C. Kothe, Towards passive brain???computer interfaces: applying brain???computer interface technology to human???machine systems in general, Journal of Neural Engineering, vol.8, issue.2, 2011.
DOI : 10.1088/1741-2560/8/2/025005

T. O. Zander, C. Kothe, S. Jatzev, and M. Gaertner, Enhancing humancomputer interaction with input from active and passive brain-computer interfaces, Brain-Computer Interfaces. Ch. 11, pp.181-199, 2010.