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  • N. Gayraud, A. Rakotomamonjy, M. Clerc,  “Optimal Transport Applied to Transfer Learning For P300 Detection,” 7th Graz Brain-Computer Interface Conference, September 18-23, 2017.
  • V. Guy, M. H. Soriani, M. Bruno, T. Papadopoulo, C. Desnuelle, et al.. Brain computer interface with P300-Speller: usability for disabled patients with Amyotrophic Lateral Sclerosis.. Annals of Physical and Rehabilitation Medicine, Elsevier Masson, 2017.


  • S. Bhattacharyya, M. Clerc, M. Hayashibe, “A study on the effect of electrical stimulation as a user stimuli for motor imagery classification in Brain-Machine Interface“, European Journal of Translational Myology, vol.26, no.2, 2016.
  • S. Bhattacharyya, M. Clerc, M. Hayashibe, “A Study on the Effect of Electrical  Stimulation During Motor Imagery Learning in Brain-Computer Interfacing“, IEEE International Conference on Systems, Man, and Cybernetics, October 9-12. 2016.
  • N. Gayraud, N. Foy, M. Clerc, “A Separability Marker Based on High-Dimensional Statistics for Classification Confidence Assessment“, IEEE International Conference on Systems, Man, and Cybernetics October 9-12. 2016.
  • S. Bhattacharyya, S. Shimoda, M. Hayashibe, “A Synergetic Brain-machine Interfacing Paradigm for Multi-DOF Robot Control”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2016.
  • C. Jeunet, E. Jahanpour, F. Lotte, “Why Standard Brain-Computer Interface (BCI) Training Protocols Should be Changed: An Experimental Study”, Journal of Neural Engineering, 2016
  • C. Jeunet, B. N’Kaoua, F. Lotte, “Advances in User-Training for Mental-Imagery Based BCI Control: Psychological and Cognitive Factors and their Neural Correlates”, Progress in Brain Research, 2016
  • C. Jeunet, F. Lotte, M. Hachet, S. Subramanian, B. N’Kaoua, “Spatial Abilities Play a Major Role in BCI Performance“, International BCI meeting, 2016
  • C. Jeunet, B. N’Kaoua, R. N’Kambou, F. Lotte, “Why and How to Use Intelligent Tutoring Systems to Adapt MI-BCI Training to Each User?”, International BCI meeting
  • L. Bougrain, B. le Golvan, “Les neuroprothèses”, l’Evolution Psychiatrique, Elsevier, à paraître 2016.
  • C. Lindig-León, N. Gayraud, L. Bougrain, M. Clerc. “Hierarchical Classification Using Riemannian Geometry for Motor Imagery Based BCI Systems”, BCI meeting 2016, Asilomar, California, USA.
  • S. Rimbert, L. Bougrain. “Comparison between discrete and continuous motor imageries : toward a faster detection”, International BCI meeting, 2016, Asilomar, California, USA.
  • R. Gervais, J. Frey, A. Gay, F. Lotte, M. Hachet, “TOBE: Tangible Out-of-Body Experience”, Tangible, Embedded and Embodied Interaction (TEI), 2016


  • S. Rimbert, L. Bougrain, C.Lindig-León, G. Serrière, F.  Giovannini, A. Hutt, Amplitude and latency of EEG Beta activity during real movements, discrete and continuous motor imageries, IEE Bernstein conference, 2015.
  • C. Lindig-León, L. Bougrain. Correlation of EEG signal during simple and combined motor imageries. Bernstein conference 2015, Heidelberg/Meinheim, Germany.
  • C. Lindig-León, L. Bougrain, S. Rimbert. On-line identification of the end of motor imageries based on the alpha rebound detection. CNS annual meeting 2015,Prague, Czech Republic.
  • C. Lindig-León, L. Bougrain. A multilabel classification method for detection of combined motor imageries. 2015 IEEE international conference on systems, man, and cybernetics, Hong Kong.
  • C. Lindig-León, L. Bougrain. Comparison of sensorimotor rhythms in EEG signals during simple and combined motor imageries over the contra and ipsilateral hemispheres. 37th Annual international conference of the IEEE-EMBS engineering in medicine and biology society 2015, Milan, Italy.
  • C. Lindig-León, L. Bougrain, S. Rimbert,. Alpha rebound improves on-line detection of the end of motor imageries. 7th International IEEE-EMBS conference on neural engineering 2015, Montpellier, France.
  • F. Lecaignard, O. Bertrand, G. Gimenez, J. Mattout, and A. Caclin, “Implicit learning of predictable sound sequences modulates human brain responses at different levels of the auditory hierarchy,” Frontiers in Human Neuroscience, vol. 9, Sep. 2015.
  • C. Jeunet, B. N’Kaoua, S. Subramanian, M. Hachet, F. Lotte, “Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns”, PLoS ONE, 2015.
  • R. Trachel, M. Clerc, T. Brochier, Decoding covert shifts of attention induced by ambiguous visuospatial cues”, Frontiers in Human Neuroscience, DOI:10.3389/fnhum.2015.00358, 2015.
  • F. Lotte, L. Bougrain, M. Clerc, “EEG-based Brain-Computer Interfaces“, Wiley Encyclopedia on Electrical and Electronics Engineering, 2015.
  • J. Schumacher, C. Jeunet, F. Lotte, “Towards Explanatory Feedback for User Training in Brain-Computer Interfaces”, IEEE International Conference on Systems Man and Cybernetics (IEEE SMC), 2015
  • F. Yger, F. Lotte, M. Sugiyama, “Averaging covariance matrices for EEG signal classification based on the CSP: an empirical study“, EUSIPCO 2015.
  • F. Lotte, “Signal processing approaches to minimize or suppress calibration time in oscillatory activity-based Brain-Computer Interfaces”, Proceedings of the IEEE, 2015.
  • C. Jeunet, C. Vi, D. Spelmezan, B. N’Kaoua, F. Lotte, S. Subramanian, “Continuous Tactile Feedback for Motor-Imagery based Brain-Computer Interaction in a Multitasking Context”, Interact 2015.
  • F. Lotte, C. Jeunet, “Towards Improved BCI based on Human Learning Principles”, 3rd International Winter Conference on Brain-Computer Interfaces, invited paper, pp. 37-40, 2015.
  • C. Jeunet, B. N’Kaoua, M. Hachet, F. Lotte, “Predicting Mental-Imagery Based Brain-Computer Interface Performance from Psychometric Questionnaires”, WomEncourage, 2015.
  • J. Mattout, M. Perrin, O. Bertrand, and E. Maby, “Improving BCI performance through co-adaptation: Applications to the P300-speller,” Annals of Physical and Rehabilitation Medicine, vol. 58, no. 1, pp. 23–28, Feb. 2015.
  •  J. Luauté, D. Morlet, and J. Mattout, “BCI in patients with disorders of consciousness: Clinical perspectives,” Annals of Physical and Rehabilitation Medicine, vol. 58, no. 1, pp. 29–34, Feb. 2015.


  • C. Lindig-León, L. Bougrain. A comparison between different multiclass Common Spatial Pattern approaches for identification of motor imagery tasks. 6th International brain-computer interface conference 2014, Graz, Austria.
  • C. Jeunet, A. Cellard, S. Subramanian, M. Hachet, B. N’Kaoua and F. Lotte, “How Well Can We Learn With Standard BCI Training Approaches? A Pilot Study”, 6th International BCI conference, DOI:10.3217/978-3-85125-378-8-83, pp 332-335, 2014.
  • E. Thomas, E. Daucé, D. Devlaminck, L. Mahé, A. Carpentier, R. Munos, M. Perrin, E. Maby, J. Mattout, T. Papadopoulo and M. Clerc, “CoAdapt P300 speller: optimized flashing sequences and online learning”, 6th International BCI conference, DOI:10.3217/978-3-85125-378-8-51, 2014.
  • G. Sanchez, J. Daunizeau, E. Maby, O. Bertrand, A. Bompas, and J. Mattout, “Toward a New Application of Real-Time Electrophysiology: Online Optimization of Cognitive Neurosciences Hypothesis Testing,” Brain Sciences, vol. 4, no. 1, pp. 49–72, Jan. 2014.
  • M. Perrin, E. Maby, O. Bertrand, and J. Mattout, “A virtuous BCI loop: adaptive decision making improves P300-spelling in two ways,” Proceeding of the 6th International Brain-Computer Interface Conference, Graz 2014.