BrainConquest SIGNED
Boosting Brain-Computer Communication with high Quality User Training
Total Cost €
0EC-Contrib. €
0Partnership
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0BrainConquest project word cloud
Explore the words cloud of the BrainConquest project. It provides you a very rough idea of what is the project "BrainConquest" about.
Project "BrainConquest" data sheet
The following table provides information about the project.
| Coordinator |
INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Organization address contact info |
| Coordinator Country | France [FR] |
| Total cost | 1˙498˙751 € |
| EC max contribution | 1˙498˙751 € (100%) |
| Programme |
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC)) |
| Code Call | ERC-2016-STG |
| Funding Scheme | ERC-STG |
| Starting year | 2017 |
| Duration (year-month-day) | from 2017-07-01 to 2022-06-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE | FR (LE CHESNAY CEDEX) | coordinator | 1˙498˙751.00 |
Map
Project objective
Brain-Computer Interfaces (BCIs) are communication systems that enable users to send commands to computers through brain signals only, by measuring and processing these signals. Making computer control possible without any physical activity, BCIs have promised to revolutionize many application areas, notably assistive technologies, e.g., for wheelchair control, and human-machine interaction. Despite this promising potential, BCIs are still barely used outside laboratories, due to their current poor reliability. For instance, BCIs only using two imagined hand movements as mental commands decode, on average, less than 80% of these commands correctly, while 10 to 30% of users cannot control a BCI at all. A BCI should be considered a co-adaptive communication system: its users learn to encode commands in their brain signals (with mental imagery) that the machine learns to decode using signal processing. Most research efforts so far have been dedicated to decoding the commands. However, BCI control is a skill that users have to learn too. Unfortunately how BCI users learn to encode the commands is essential but is barely studied, i.e., fundamental knowledge about how users learn BCI control is lacking. Moreover standard training approaches are only based on heuristics, without satisfying human learning principles. Thus, poor BCI reliability is probably largely due to highly suboptimal user training. In order to obtain a truly reliable BCI we need to completely redefine user training approaches. To do so, I propose to study and statistically model how users learn to encode BCI commands. Then, based on human learning principles and this model, I propose to create a new generation of BCIs which ensure that users learn how to successfully encode commands with high signal-to-noise ratio in their brain signals, hence making BCIs dramatically more reliable. Such a reliable BCI could positively change human-machine interaction as BCIs have promised but failed to do so far.
Deliverables
| Data Management Plan | Open Research Data Pilot | 2020-03-11 14:35:07 |
Take a look to the deliverables list in detail: detailed list of BrainConquest deliverables.
Publications
| year | authors and title | journal | last update |
|---|---|---|---|
| 2020 |
Aurélien Appriou, Andrzej Cichocki, Fabien Lotte Modern machine learning algorithms to classify cognitive and affective states from electroencephalography signals published pages: , ISSN: 2333-942X, DOI: |
IEEE systems, man, and cybernetics magazine | 2020-02-28 |
| 2020 |
Léa Pillette, Camille Jeunet, Boris Mansencal, Roger N’Kambou, Bernard N’Kaoua, Fabien Lotte A physical learning companion for Mental-Imagery BCI User Training published pages: 102380, ISSN: 1071-5819, DOI: 10.1016/j.ijhcs.2019.102380 |
International Journal of Human-Computer Studies 136 | 2020-02-28 |
| 2019 |
Roc, Aline; Pillette, Léa; N\'Kaoua, B.; Lotte, Fabien Would Motor-Imagery based BCI user training benefit from more women experimenters? published pages: , ISSN: , DOI: |
8th Graz Brain-Computer Interface Conference 2019 | 2020-02-28 |
| 2020 |
Khadijeh Sadatnejad, Aline Roc, Léa Pillette, Aurélien Appriou, Thibaut Monseigne, Fabien Lotte Channel selection over riemannian manifold with non-stationarity consideration for brain-computer interface applications published pages: , ISSN: , DOI: |
Proceedings of ICASSP 2020 | 2020-02-28 |
| 2019 |
J.-M. Batail, S. Bioulac, F. Cabestaing, C. Daudet, D. Drapier, M. Fouillen, T. Fovet, A. Hakoun, R. Jardri, C. Jeunet, F. Lotte, E. Maby, J. Mattout, T. Medani, J.-A. Micoulaud-Franchi, J. Mladenovic, L. Perronet, L. Pillette, T. Ros, F. Vialatte EEG neurofeedback research: A fertile ground for psychiatry? published pages: 245-255, ISSN: 0013-7006, DOI: 10.1016/j.encep.2019.02.001 |
L\'Encéphale 45/3 | 2020-02-28 |
| 2019 |
Benaroch, Camille; Jeunet, Camille; Lotte, Fabien Are users\' traits informative enough to predict/explain their mental-imagery based BCI performances ? published pages: , ISSN: , DOI: |
8th Graz BCI Conference 2019, Sep 2019, Graz, Austria | 2020-02-28 |
| 2020 |
Jelena Mladenovic, Jeremy Frey, Mateus Joffily, Emmanuel Maby, Fabien Lotte, Jeremie Mattout Active inference as a unifying, generic and adaptive framework for a P300-based BCI published pages: 16054, ISSN: 1741-2552, DOI: 10.1088/1741-2552/ab5d5c |
Journal of Neural Engineering 17/1 | 2020-02-28 |
| 2020 |
Fabien Lotte, Camille Jeunet, Ricardo Chavarriaga, Laurent Bougrain, Dave E. Thompson, Reinhold Scherer, Md Rakibul Mowla, Andrea Kübler, Moritz Grosse-Wentrup, Karen Dijkstra, Natalie Dayan Turning negative into positives! Exploiting ‘negative’ results in Brain–Machine Interface (BMI) research published pages: 1-12, ISSN: 2326-263X, DOI: 10.1080/2326263x.2019.1697143 |
Brain-Computer Interfaces | 2020-02-28 |
| 2018 |
Fabien Lotte, Camille Jeunet Defining and quantifying users’ mental imagery-based BCI skills: a first step published pages: 46030, ISSN: 1741-2560, DOI: 10.1088/1741-2552/aac577 |
Journal of Neural Engineering 15/4 | 2019-09-02 |
| 2018 |
Andreas Meinel, Sebastián Castaño-Candamil, Benjamin Blankertz, Fabien Lotte, Michael Tangermann Characterizing Regularization Techniques for Spatial Filter Optimization in Oscillatory EEG Regression Problems published pages: , ISSN: 1539-2791, DOI: 10.1007/s12021-018-9396-7 |
Neuroinformatics | 2019-09-02 |
| 2018 |
Léa Pillette, Aurélien Appriou, Andrzej Cichocki, Bernard N\'Kaoua, Fabien Lotte Classification of attention types in EEG signals published pages: , ISSN: , DOI: |
International BCI Meeting | 2019-09-02 |
| 2018 |
Appriou , Aurélien; Pillette , Léa; Cichocki , Andrzej; Lotte , Fabien BCPy, an open-source python platform for offline EEG signals decoding and analysis published pages: , ISSN: , DOI: |
International BCI Meeting, May 2018, Pacific Grove, United States 1 | 2019-09-02 |
| 2018 |
Camille Jeunet, Fabien Lotte, Jean-Marie Batail, Pierre Philip, Jean-Arthur Micoulaud Franchi Using Recent BCI Literature to Deepen our Understanding of Clinical Neurofeedback: A Short Review published pages: 225-233, ISSN: 0306-4522, DOI: 10.1016/j.neuroscience.2018.03.013 |
Neuroscience 378 | 2019-09-02 |
| 2018 |
Laurens R. Krol, Juliane Pawlitzki, Fabien Lotte, Klaus Gramann, Thorsten O. Zander SEREEGA: Simulating event-related EEG activity published pages: 13-24, ISSN: 0165-0270, DOI: 10.1016/j.jneumeth.2018.08.001 |
Journal of Neuroscience Methods 309 | 2019-09-02 |
| 2018 |
Felix Putze, Christian Mühl, Fabien Lotte, Stephen Fairclough, Christian Herff Editorial: Detection and Estimation of Working Memory States and Cognitive Functions Based on Neurophysiological Measures published pages: , ISSN: 1662-5161, DOI: 10.3389/fnhum.2018.00440 |
Frontiers in Human Neuroscience 12 | 2019-09-02 |
| 2018 |
Lotte , Fabien; Jeunet , Camille; Mladenovic , Jelena; N \'kaoua , Bernard; Pillette , Léa A BCI challenge for the signal processing community: considering the user in the loop published pages: , ISSN: , DOI: |
https://www.theiet.org/resources/books/control/brain-machine-interface.cfm 1 | 2019-09-02 |
| 2018 |
F Lotte, L Bougrain, A Cichocki, M Clerc, M Congedo, A Rakotomamonjy, F Yger A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update published pages: 31005, ISSN: 1741-2560, DOI: 10.1088/1741-2552/aab2f2 |
Journal of Neural Engineering 15/3 | 2019-09-02 |
| 2018 |
Pillette , Léa; Jeunet , Camille; N \'kambou , R; N\'Kaoua , Bernard; Lotte , Fabien Towards Artificial Learning Companions for Mental Imagery-based Brain-Computer Interfaces published pages: , ISSN: , DOI: |
WACAI 2018 | 2019-09-02 |
| 2017 |
Lotte , Fabien; Cichocki , Andrzej What are the best motor tasks to use and calibrate SensoriMotor Rhythm Neurofeedback and Brain-Computer Interfaces? A preliminary case study published pages: , ISSN: , DOI: |
rtFIN 2017 - Real-time functional Imaging and Neurofeedback conference 1 | 2019-09-02 |
| 2018 |
Lotte , Fabien; Cichocki , Andrzej Can transfer learning across motor tasks improve motor imagery BCI? published pages: , ISSN: , DOI: |
International BCI Meeting 2018 1 | 2019-09-02 |
| 2019 |
Satyam Kumar, Florian Yger, Fabien Lotte Towards Adaptive Classification using Riemannian Geometry approaches in Brain-Computer Interfaces published pages: , ISSN: , DOI: |
IEEE International Winter Conference on Brain-Computer Interfaces | 2019-09-02 |
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The information about "BRAINCONQUEST" are provided by the European Opendata Portal: CORDIS opendata.