P8 - Brain Computer Interaction: control and learning
- CERMEP-MEG, VSM-CTF company
The objective of this transversal project is to setup a new field of applications for MEG, EEG and intracranial EEG recording techniques, based on the real-time analysis of these signals
. Until now, EEG/MEG signals have always been analyzed off-line (i.e. cleaned, averaged, compared across experimental sessions). The search for correlations between the brain signals and the subject's mental activity and performance is always done after the experiment. Our aim is to reveal those correlations as the subject's brain is producing the signals. One situation, that we plan to study, is the electrophysiological correlates of the attention level of a subject anticipating the occurrence of an upcoming target. If calculated on-line, such a correlate could be validated either by dynamically manipulating the difficulty of the task
according to its value, of by modulating in real-time a sensory information presented to the subject
and asking him for possible correlation with his self-estimated level of selective attention (following a bio-feedback approach). Those procedures can be easily adjusted to study various cognitive functions (memory, perception, emotion). This explains why the present project is transversal and will obviously interact with the other ones. It will be financed (2005-2008) by a collaboration contract with the VSM company (Canada) which manufactured the MEG system installed in Lyon. It involves a significant amount of technological and methodological development to adapt the current signal analysis and neural source localization techniques to the real-time framework
: ICA-based artifact rejection, oscillatory activity and synchronization detection, adaptive methods for source localization, and appropriate statistical tests. This project has numerous potential applications in both fundamental and clinical research; For instance:
- Real-time dynamic brain imaging, as in the aforementioned example.
- Optimization of functional rehabilitation procedures via electrophysiological neurofeedback (perceptual learning, attention control, ....),
- Design of Brain-Computer Interfaces (BCI) allowing for instance a subject to control a computer device with his brain activity.
Thanks to the computing power of today's computers and to the development of new techniques for analyzing the on-going brain activity, the field of real-time neuroimaging is now booming on the international scene (BCI2000 project in the US, Germany, Austria, and Finland). However, the MEG approach that we want to emphasize has not been explored yet.
Publications since 2010
- Perrin M, Maby E, Daligault S, Bertrand O, and Mattout J (2012) Objective and subjective evaluation of online error correction during P300-based spelling, Advances in Human-Computer Interaction 0(2012): 578295
- Maby E, Perrin M, Bertrand O, Sanchez G, and Mattout J (2012) BCI could make old two-player games even more fun: a proof of concept with Connect Four, Advances in Human-Computer Interaction 2012: 124728
- Cecotti H, Rivet B, Congedo M, Jutten C, Bertrand O, Maby E, Mattout J. (2011) A robust sensor-selection method for P300 brain-computer interfaces., J Neural Eng. 8(1): 016001
- Rivet B, Cecotti H, Maby E, Mattout J. (2011) Impact of Spatial Filters During Sensor Selection in a Visual P300 Brain-Computer Interface., Brain Topogr 0:
- Rivet B, Cecotti H, Perrin M, Maby E, Mattout J. (2011) Adaptive training session for a P300 speller brain–computer interface, Journal of Physiology - Paris 105: 123-129
- Rivet B, Cecotti H, Phlypo R, Bertrand O, Maby E, Mattout J. (2010) EEG sensor selection by sparse spatial filtering in P300 speller brain-computer interface., Conf Proc IEEE Eng Med Biol Soc. 1: 5379-82.
- Renard Y., Lotte F., Gibert G., Congedo M., Maby E., Delannoy V., Bertrand O., Lecuyer A. (2010) OpenViBE: An Open-Source Software Platform to Design, Test and Use Brain-Computer Interfaces in Real and Virtual Environments?, Presence : teleoperators and virtual environments 19(1): 35-53