Theoretical analysis of xDAWN algorithm: application to an efficient sensor selection in a P300 BCI

International audienceA Brain-Computer Interface (BCI) is a specific type of human-machine interface that enables communication between a subject/patient and a computer by a direct control from the decoding of brain activity. To improve the ergonomics and to minimize the cost of such a BCI, reducing the number of electrodes is mandatory. A theoretical analysis of the subjacent model induced by the BCI paradigm leads to derive a closed form theoretical expression of the spatial filters which maximize the signal to signal-plus-noise ratio. Moreover, this new formulation is useful to improve a previously introduced method to automatically select relevant sensors. Experimental results on 20 subjects show that the proposed method is efficient to select the most relevant sensors: from 32 down to 8 sensors, the loss in classification accuracy is less than 2%. Furthermore, the computational time required to rank the 32 sensors is reduced by a 4.6 speed up factor allowing dynamical monitoring of sensor relevance as a marker of the user's mental state

Analyse discriminante matricielle descriptive. Application a l'\'etude de signaux EEG

We focus on the descriptive approach to linear discriminant analysis for matrix-variate data in the binary case. Under a separability assumption on row and column variability, the most discriminant linear combinations of rows and columns are determined by the singular value decomposition of the difference of the class-averages with the Mahalanobis metric in the row and column spaces. This approach provides data representations of data in two-dimensional or three-dimensional plots and singles out discriminant components. An application to electroencephalographic multi-sensor signals illustrates the relevance of the method.Comment: in French, Journ{\'e}es de statistique de la SFDS, Jun 2015, Lille, Franc

Analyse discriminante matricielle descriptive. Application a l'étude de signaux EEG

National audienceWe focus on the descriptive approach to linear discriminant analysis for matrix-variate data in the binary case. Under a separability assumption on row and column variability, the most discriminant linear combinations of rows and columns are determined by the singular value decomposition of the difference of the class-averages with the Mahalanobis metric in the row and column spaces. This approach provides data representations of data in two-dimensional or three-dimensional plots and singles out discriminant components. An application to electroencephalographic multi-sensor signals illustrates the relevance of the method.Nous nous intéressons à l'approche descriptive de l'analyse discriminante linéaire de données matricielles dans le cas binaire. Sous l'hypothèse de séparabilité de la variabilité des lignes de celle des colonnes, les combinaisons linéaires des lignes et des colonnes les plus discriminantes sont déterminées par la décomposition en valeurs singulières de la différence des moyennes des deux classes en munissant les espaces des lignes et des colonnes de la métrique de Mahalanobis. Cette approche permet d'obtenir des représentations des données dans des plans factoriels et de dégager des composantes discriminantes. Une application a des signaux d'électroencéphalographie multi-capteurs illustre la pertinence de la méthode

Active Inference for Adaptive BCI: application to the P300 Speller

International audienceAdaptive Brain-Computer interfaces (BCIs) have shown to improve performance, however a general and flexible framework to implement adaptive features is still lacking. We appeal to a generic Bayesian approach, called Active Inference (AI), to infer user's intentions or states and act in a way that optimizes performance. In realistic P300-speller simulations, AI outperforms traditional algorithms with an increase in bit rate between 18% and 59%, while offering a possibility of unifying various adaptive implementations within one generic framework

A user-centred approach to unlock the potential of non-invasive BCIs: an unprecedented international translational effort

Non-invasive Mental Task-based Brain-Computer Interfaces (MT-BCIs) enable their users to interact with the environment through their brain activity alone (measured using electroencephalography for example), by performing mental tasks such as mental calculation or motor imagery. Current developments in technology hint at a wide range of possible applications, both in the clinical and non-clinical domains. MT-BCIs can be used to control (neuro)prostheses or interact with video games, among many other applications. They can also be used to restore cognitive and motor abilities for stroke rehabilitation, or even improve athletic performance.Nonetheless, the expected transfer of MT-BCIs from the lab to the marketplace will be greatly impeded if all resources are allocated to technological aspects alone. We cannot neglect the Human End-User that sits in the centre of the loop. Indeed, self-regulating one’s brain activity through mental tasks to interact is an acquired skill that requires appropriate training. Yet several studies have shown that current training procedures do not enable MT-BCI users to reach adequate levels of performance. Therefore, one significant challenge for the community is that of improving end-user training.To do so, another fundamental challenge must be taken into account: we need to understand the processes that underlie MT-BCI performance and user learning. It is currently estimated that 10 to 30% of people cannot control an MT-BCI. These people are often referred to as “BCI inefficient”. But the concept of “BCI inefficiency” is debated. Does it really exist? Or, are low performances due to insufficient training, training procedures that are unsuited to these users or is the BCI data processing not sensitive enough? The currently available literature does not allow for a definitive answer to these questions as most published studies either include a limited number of participants (i.e., 10 to 20 participants) and/or training sessions (i.e., 1 or 2). We still have very little insight into what the MT-BCI learning curve looks like, and into which factors (including both user-related and machine-related factors) influence this learning curve. Finding answers will require a large number of experiments, involving a large number of participants taking part in multiple training sessions. It is not feasible for one research lab or even a small consortium to undertake such experiments alone. Therefore, an unprecedented coordinated effort from the research community is necessary.We are convinced that combining forces will allow us to characterise in detail MT-BCI user learning, and thereby provide a mandatory step toward transferring BCIs “out of the lab”. This is why we gathered an international, interdisciplinary consortium of BCI researchers from more than 20 different labs across Europe and Japan, including pioneers in the field. This collaboration will enable us to collect considerable amounts of data (at least 100 participants for 20 training sessions each) and establish a large open database. Based on this precious resource, we could then lead sound analyses to answer the previously mentioned questions. Using this data, our consortium could offer solutions on how to improve MT-BCI training procedures using innovative approaches (e.g., personalisation using intelligent tutoring systems) and technologies (e.g., virtual reality). The CHIST-ERA programme represents a unique opportunity to conduct this ambitious project, which will foster innovation in our field and strengthen our community

Incorporation of recent waking-life experiences in dreams correlates with frontal theta activity in REM sleep

Rapid eye movement (REM) sleep and its main oscillatory feature, frontal theta, have been related to the processing of recent emotional memories. As memories constitute much of the source material for our dreams, we explored the link between REM frontal theta and the memory sources of dreaming, so as to elucidate the brain activities behind the formation of dream content. Twenty participants were woken for dream reports in REM and slow wave sleep (SWS) while monitored using electroencephalography. Eighteen participants reported at least one REM dream and 14 at least one SWS dream, and they, and independent judges, subsequently compared their dream reports with log records of their previous daily experiences. The number of references to recent waking-life experiences in REM dreams was positively correlated with frontal theta activity in the REM sleep period. No such correlation was observed for older memories, nor for SWS dreams. The emotional intensity of recent waking-life experiences incorporated into dreams was higher than the emotional intensity of experiences that were not incorporated. These results suggest that the formation of wakefulness-related dream content is associated with REM theta activity, and accords with theories that dreaming reflects emotional memory processing taking place in REM sleep

Influence des radiofréquences émises par le téléphone mobile GSM sur l'activité corticale auditive chez l'homme

Membres du jury : Mohamed Najim (président), Jean-Marc Boucher (rapporteur), Catherine Marque (rapporteur), Catherine Liégeois-Chauvel, Alain Bardou (membre invité)This thesis contributes to the studies conducted on the biological and sanitary effects of radiofrequencies associated with mobile telephony. The aim of this work is to evaluate the influence of radiofrequencies emitted by the mobile phone on the human auditory cortical activity. A state of the art on the biological and medical effects induced by this mobile phone is drawn up. After a description of the auditory evoked potentials (AEP) acquisition protocol and the selection of the electrodes which record the most characteristic signals of AEPs, variables are extracted from these signals and are statistically analyzed. A selection, based on classification using Support Vector Machines, makes it possible to identify the most disturbed variables by RF and the analysis per electrode allows to locate their effects. A study on electroencephalographic (EEG) signals is also conducted on spectral correlation coefficients and power spectral density. It comes out that the RF emitted by the mobile telephone affect the AEP and the EEG signals. On the other hand, no causality link between these biological effects and the harmful effects on human health can be shown today.Cette thèse s'inscrit dans le cadre des études menées sur les effets biologiques et sanitaires des radiofréquences associées à la téléphonie mobile. Le but de ce travail est d'évaluer l'influence des radiofréquences émises par le téléphone mobile sur l'activité corticale chez l'homme. Tout d'abord, un état des connaissances scientifiques relatives aux effets biologiques et sanitaires des radiofréquences associées à la téléphonie mobile a été dressé. Ensuite, on effectue une description du matériel et des méthodes d'acquisition des potentiels évoqués auditifs (PEA) caractéristiques de l'activité corticale auditive. De plus, on a sélectionné les électrodes qui recueillent les signaux les plus caractéristiques de PEA. Des variables dont certaines caractéristiques électrophysiologiques des PEA sont extraites et font l'objet d'une analyse statistique. Une sélection, basée sur la classification par Support Vector Machines, met en exergue les variables plus perturbées par les radiofréquences. Enfin, l'analyse statistique par électrode permet de localiser les effets des radiofréquences. On se consacre enfin à l'étude des signaux électroencéphalographiques en étudiant les coefficients de corrélations entre spectres et les densités spectrales de puissance par bande de fréquences. En conclusion, les radiofréquences émises par le téléphone mobile semblent montrer une incidence sur les potentiels évoqués auditifs et les signaux électroencéphalographiques. Cependant, aucun apport de causalité entre ces effets biologiques sur l'activité corticale et les effets néfastes sur la santé humaine ne peut être démontré à ce jour

Y a-t-il une place pour les interfaces cerveaux-machines dans l'évaluation de patients non-répondant ?

International audienceBrain computer interfaces (BCI) are often presented as a solution to restore communication for patients in cognitive motor dissociation. We review here the current state of the art, we compare BCI with current active EEG paradigms and discuss some translational limits and ethical risks

Locked-in syndrome, eyes and laws for embodied cognition ?

International audienc

What is missing for physicians to prescribe a BCI ?

International audienceSince the early development of BCI, several decades ago, clinical applications were presented as a major objective. However, despite notable progress, they struggle to enter the clinical routine. Besides technological limits, we notice that most of the BCI studies are realized with healthy subjects, and when applied to patients, they are mainly proof-of-concept studies. Recent « replace » or « restore » BCI studies showed noticeable changes in the BCI study design, in the aim of optimizing clinical translation. We will highlight some of these pragmatic turns. We will also compare these new strategies with general clinical guidelines and practices to highlight what is still missing to allow a rehabilitation physician to prescribe a BCI