81 research outputs found

    Corticomuscular co-activation based hybrid brain-computer interface for motor recovery monitoring

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    The effect of corticomuscular coactivation based hybrid brain-computer interface (h-BCI) on post-stroke neurorehabilitation has not been explored yet. A major challenge in this area is to find an appropriate corticomuscular feature which can not only drive an h-BCI but also serve as a biomarker for motor recovery monitoring. Our previous study established the feasibility of a new method of measuring corticomuscular co-activation called correlation of band-limited power time-courses (CBPT) of EEG and EMG signals, outperforming the traditional EEG-EMG coherence in terms of accurately controlling a robotic hand exoskeleton device by the stroke patients. In this paper, we have evaluated the neurophysiological significance of CBPT for motor recovery monitoring by conducting a 5-week long longitudinal pilot trial on 4 chronic hemiparetic stroke patients. Results show that the CBPT variations correlated significantly (p-value< 0.05) with the dynamic changes in motor outcome measures during the therapy for all the patients. As the bandpower based biomarkers are popular in literature, a comparison with such biomarkers has also been made to cross-verify whether the changes in CBPT are indeed neurophysiological. Thus the study concludes that CBPT can serve as a biomarker for motor recovery monitoring while serving as a corticomuscular co-activation feature for h-BCI based neurorehabilitation. Despite an observed significant positive change between pre- and post-intervention motor outcomes, the question of the clinical effectiveness of CBPT is subject to further controlled trial on a larger cohort

    VALIDATION OF A MODEL OF SENSORIMOTOR INTEGRATION WITH CLINICAL BENEFITS

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    Healthy sensorimotor integration – or how our touch influences our movements – is critical to efficiently interact with our environment. Yet, many aspects of this process are still poorly understood. Importantly, several movement disorders are often considered as originating from purely motor impairments, while a sensory origin could also lead to a similar set of symptoms. To alleviate these issues, we hereby propose a novel biologically-based model of the sensorimotor loop, known as the SMILE model. After describing both the functional, and the corresponding neuroanatomical versions of the SMILE, we tested several aspects of its motor component through functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS). Both experimental studies resulted in coherent outcomes with respect to the SMILE predictions, but they also provided novel scientific outcomes about such broad topics as the sub-phases of motor imagery, the neural processing of bodily representations, or the extend of the role of the extrastriate body area. In the final sections of this manuscript, we describe some potential clinical application of the SMILE. The first one presents the identification of plausible neuroanatomical origins for focal hand dystonia, a yet poorly understood sensorimotor disorder. The last chapter then covers possible improvements on brain-machine interfaces, driven by a better understanding of the sensorimotor system. -- La façon dont votre sens du toucher et vos mouvements interagissent est connue sous le nom d’intĂ©gration sensorimotrice. Ce procĂ©dĂ© est essentiel pour une interaction normale avec tout ce qui nous entoure. Cependant, plusieurs aspects de ce processus sont encore mĂ©connus. Plus important encore, l’origine de certaines dĂ©ficiences motrices encore trop peu comprises sont parfois considĂ©rĂ©es comme purement motrice, alors qu’une origine sensorielle pourrait mener Ă  un mĂȘme ensemble de symptĂŽmes. Afin d’amĂ©liorer cette situation, nous proposons ici un nouveau modĂšle d’intĂ©gration sensorimotrice, dĂ©nommĂ© « SMILE », basĂ© sur les connaissances de neurobiologie actuelles. Dans ce manuscrit, nous commençons par dĂ©crire les caractĂ©ristiques fonctionnelles et neuroanatomiques du SMILE. Plusieurs expĂ©riences sont ensuite effectuĂ©es, via l’imagerie par rĂ©sonance magnĂ©tique fonctionnelle (IRMf), et la stimulation magnĂ©tique transcranienne (SMT), afin de tester diffĂ©rents aspects de la composante motrice du SMILE. Si les rĂ©sultats de ces expĂ©riences corroborent les prĂ©dictions du SMILE, elles ont aussi mis en Ă©vidences d’autres rĂ©sultats scientifiques intĂ©ressants et novateurs, dans des domaines aussi divers que les sous-phases de l’imagination motrice, les processus cĂ©rĂ©braux liĂ©s aux reprĂ©sentations corporelles, ou encore l’extension du rĂŽle de l’extrastriate body area. Dans les derniĂšres parties de ce manuscrit, nous dĂ©voilons quelques applications cliniques potentielles de notre modĂšle. Nous utilisons le SMILE afin de proposer deux origines cĂ©rĂ©brales plausibles de la dystonie focale de la main. Le dernier chapitre prĂ©sente comment certaines technologies existantes, telles que les interfaces cerveaux-machines, pourraient bĂ©nĂ©ficier d’une meilleure comprĂ©hension du systĂšme sensorimoteur

    Cognitive Assessment and Rehabilitation of subjects with Traumatic Brain Injury

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    This thesis regards the study and the development of new cognitive assessment and rehabilitation techniques of subjects with traumatic brain injury (TBI). In particular, this thesis i) provides an overview about the state of art of this new assessment and rehabilitation technologies, ii) suggests new methods for the assessment and rehabilitation and iii) contributes to the explanation of the neurophysiological mechanism that is involved in a rehabilitation treatment. Some chapters provide useful information to contextualize TBI and its outcome; they describe the methods used for its assessment/rehabilitation. The other chapters illustrate a series of experimental studies conducted in healthy subjects and TBI patients that suggest new approaches to assessment and rehabilitation. The new proposed approaches have in common the use of electroencefalografy (EEG). EEG was used in all the experimental studies with a different purpose, such as diagnostic tool, signal to command a BCI-system, outcome measure to evaluate the effects of a treatment, etc. The main achieved results are about: i) the study and the development of a system for the communication with patients with disorders of consciousness. It was possible to identify a paradigm of reliable activation during two imagery task using EEG signal or EEG and NIRS signal; ii) the study of the effects of a neuromodulation technique (tDCS) on EEG pattern. This topic is of great importance and interest. The emerged founding showed that the tDCS can manipulate the cortical network activity and through the research of optimal stimulation parameters, it is possible move the working point of a neural network and bring it in a condition of maximum learning. In this way could be possible improved the performance of a BCI system or to improve the efficacy of a rehabilitation treatment, like neurofeedback

    Influence of Auditory Cues on the Neuronal Response to Naturalistic Visual Stimuli in a Virtual Reality Setting

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    Virtual reality environments offer great opportunities to study the performance of brain-computer interfaces (BCIs) in real-world contexts. As real-world stimuli are typically multimodal, their neuronal integration elicits complex response patterns. To investigate the effect of additional auditory cues on the processing of visual information, we used virtual reality to mimic safety-related events in an industrial environment while we concomitantly recorded electroencephalography (EEG) signals. We simulated a box traveling on a conveyor belt system where two types of stimuli – an exploding and a burning box – interrupt regular operation. The recordings from 16 subjects were divided into two subsets, a visual-only and an audio-visual experiment. In the visual-only experiment, the response patterns for both stimuli elicited a similar pattern – a visual evoked potential (VEP) followed by an event-related potential (ERP) over the occipital-parietal lobe. Moreover, we found the perceived severity of the event to be reflected in the signal amplitude. Interestingly, the additional auditory cues had a twofold effect on the previous findings: The P1 component was significantly suppressed in the case of the exploding box stimulus, whereas the N2c showed an enhancement for the burning box stimulus. This result highlights the impact of multisensory integration on the performance of realistic BCI applications. Indeed, we observed alterations in the offline classification accuracy for a detection task based on a mixed feature extraction (variance, power spectral density, and discrete wavelet transform) and a support vector machine classifier. In the case of the explosion, the accuracy slightly decreased by –1.64% p. in an audio-visual experiment compared to the visual-only. Contrarily, the classification accuracy for the burning box increased by 5.58% p. when additional auditory cues were present. Hence, we conclude, that especially in challenging detection tasks, it is favorable to consider the potential of multisensory integration when BCIs are supposed to operate under (multimodal) real-world conditions
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