J. R. Wolpaw and E. W. Wolpaw, Brain-Computer Interfaces: Principles and Practice, 2012.

F. Lotte, F. Larrue, and C. Mühl, Flaws in current human training protocols for spontaneous Brain-Computer Interfaces: lessons learned from instructional design, Frontiers in Human Neuroscience, vol.7, 2013.
DOI : 10.3389/fnhum.2013.00568

URL : https://hal.archives-ouvertes.fr/hal-00862716

J. Hattie and H. Timperley, The Power of Feedback, Review of Educational Research, vol.77, issue.1, pp.81-112, 2007.
DOI : 10.3102/003465430298487

F. Cincotti, L. Kauhanen, F. Aloise, T. Palomäki, N. Caporusso et al., Vibrotactile Feedback for Brain-Computer Interface Operation, Computational Intelligence and Neuroscience, vol.51, issue.6, 2007.
DOI : 10.1093/biomet/82.4.711

M. Gomez-rodriguez, J. Peters, J. Hill, B. Schölkopf, A. Gharabaghi et al., Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery, Journal of Neural Engineering, vol.8, issue.3, 2011.
DOI : 10.1088/1741-2560/8/3/036005

K. A. Mccreadie, D. H. Coyle, and G. Prasad, Is Sensorimotor BCI Performance Influenced Differently by Mono, Stereo, or 3-D Auditory Feedback?, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.22, issue.3, 2014.
DOI : 10.1109/TNSRE.2014.2312270

F. Nijboer, I. Gunst, S. Von-hartlieb, D. Mcfarland, N. Birbaumer et al., A comparison between auditory and visual feedback of sensorimotor rhythms (SMR) for a brain-computer interface (BCI) in healthy participants, Psychophysiology, vol.43, pp.71-71, 2006.

F. Lotte, J. Faller, C. Guger, Y. Renard, G. Pfurtscheller et al., Combining BCI with Virtual Reality: Towards New Applications and Improved BCI, Towards Practical Brain-Computer Interfaces, pp.197-220, 2013.
DOI : 10.1007/978-3-642-29746-5_10

URL : https://hal.archives-ouvertes.fr/hal-00735932

H. Hwang, K. Kwon, and C. Im, Neurofeedback-based motor imagery training for brain???computer interface (BCI), Journal of Neuroscience Methods, vol.179, issue.1, pp.150-156, 2009.
DOI : 10.1016/j.jneumeth.2009.01.015

M. Grosse-wentrup, B. Schölkopf, and J. Hill, Causal influence of gamma oscillations on the sensorimotor rhythm, NeuroImage, vol.56, issue.2, 2011.
DOI : 10.1016/j.neuroimage.2010.04.265

M. Grosse-wentrup and B. Schölkopf, High gamma-power predicts performance in sensorimotor-rhythm brain???computer interfaces, Journal of Neural Engineering, vol.9, issue.4, 2012.
DOI : 10.1088/1741-2560/9/4/046001

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.370.7438

M. Ahn and S. C. Jun, Performance variation in motor imagery brain???computer interface: A brief review, Journal of Neuroscience Methods, vol.243, 2015.
DOI : 10.1016/j.jneumeth.2015.01.033

A. Bamdadian, C. Guan, K. K. Ang, and J. Xu, The predictive role of pre-cue EEG rhythms on MI-based BCI classification performance, Journal of Neuroscience Methods, vol.235, pp.138-144, 2014.
DOI : 10.1016/j.jneumeth.2014.06.011

T. Kaufmann, J. Williamson, E. Hammer, R. Murray-smith, and A. Kübler, Visually multimodal vs. classic unimodal feedback approach for SMR-BCIs: a comparison study, Int. J. Bioelectromagn, 2011.

C. Jeunet, B. N-'kaoua, S. Subramanian, M. Hachet, and F. Lotte, Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns, PLOS ONE, vol.25, issue.1, 2015.
DOI : 10.1371/journal.pone.0143962.g008

URL : https://hal.archives-ouvertes.fr/hal-01177685

E. V. Friedrich, C. Neuper, and R. Scherer, Whatever Works: A Systematic User-Centered Training Protocol to Optimize Brain-Computer Interfacing Individually, PLoS ONE, vol.127, issue.9, p.76214, 2013.
DOI : 10.1371/journal.pone.0076214.t002

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

E. M. Hammer, S. Halder, B. Blankertz, C. Sannelli, T. Dickhaus et al., Psychological predictors of SMR-BCI performance, Biological Psychology, vol.89, issue.1, pp.80-86, 2012.
DOI : 10.1016/j.biopsycho.2011.09.006

M. Grosse-wentrup and B. Schölkopf, A brain???computer interface based on self-regulation of gamma-oscillations in the superior parietal cortex, Journal of Neural Engineering, vol.11, issue.5, p.56015, 2014.
DOI : 10.1088/1741-2560/11/5/056015

S. Weichwald, T. Meyer, O. Ozdenizci, B. Schölkopf, T. Ball et al., Causal interpretation rules for encoding and decoding models in neuroimaging, NeuroImage, vol.110, pp.48-59, 2015.
DOI : 10.1016/j.neuroimage.2015.01.036

I. Goncharova, D. J. Mcfarland, T. M. Vaughan, and J. R. Wolpaw, EMG contamination of EEG: spectral and topographical characteristics, Clinical Neurophysiology, vol.114, issue.9, pp.1580-1593, 2003.
DOI : 10.1016/S1388-2457(03)00093-2