Maîtrise de soi | EPFL Graph Search

La maîtrise de soi, un aspect du contrôle inhibiteur, est la capacité de réguler ses émotions, ses pensées et son comportement face aux tentations et aux impulsions. En tant que fonction exécutive, la maîtrise de soi est un processus cognitif nécessaire pour réguler son comportement afin d'atteindre des objectifs spécifiques. Un concept connexe en psychologie est l'autorégulation émotionnelle. Le fonctionnement de la maîtrise de soi, est analogue à un muscle. Selon les études, l'autorégulation, qu'elle soit émotionnelle ou comportementale, s'est avérée être une ressource limitée qui fonctionne comme de l'énergie. A court terme, un recours excessif à la maîtrise de soi conduira à l'épuisement. Cependant, à long terme, le recours à la maîtrise de soi peut se renforcer et s'améliorer avec le temps. La maîtrise de soi est également un concept clé de la théorie générale du crime, une théorie majeure en criminologie. La théorie a été dével

Motor state transitions and Breathing in Brain Machine Interfaces

Bastien Orset

Brain-Machine interfaces aim to create a direct neural link between user's brain and machines. This goal has pushed scientists to investigate a large spectrum of applications in the realm of assistive and rehabilitation technologies. However, despite great progress, the possibility of being in full control of a device with our brain is still far to be reached. One of the primary limitations of BMIs is the notion of self-paced control, which states that a user should be able to activate or deactivate such interface by mere modulation of brain activity. Many studies have investigated this question, focusing notably on the use of endogenous signals (such as Event-Related Desynchronization/Synchronization, ERD/S) to control the activation of these interfaces in natural interaction scenarios. This question is, however, largely ignored when looking at their interruption. Hence, in this first part of the thesis, my work was devoted to investigate how a BMI user would be able to control the interruption of non-invasive BMIs based on Motor Imagery (MI), a paradigm promoting natural and endogenous signals that can be used for BMI control. I investigated the decoding of motor termination as well as its correlates characterized by the post-movement ERS phenomenon. Specifically, this part of the thesis aimed to study (i) the feasibility to decode motor termination from a specific neural correlate as well as the adaptation from the user in closed-loop scenarios, (ii) the benefits of using motor termination correlates to detect the stopping process, and (iii) the effect of BMI effectors such as an exoskeleton on the detection of motor termination correlates. The obtained results provide new insights into closed-loop decoding of motor termination. In particular, I show that BMI users exhibit an adaptation of their EEG correlates enabling them to have a reliable control when switching off a BMI in closed-loop scenarios. Second, I show that the decoding of motor termination is a particular process different from a resting state and, hence, should be decoded independently so as to achieve a faster and more robust detection. Finally, I investigate the use of BMI effectors with respect to the decoding of motor termination showing an effect of the effectors on the correlates of motor termination. However, due to the nature of these correlates, motor termination can still be reliably decoded with a similar latency. In the second part of my thesis, I also investigate how the interoceptive system affects BMI and particularly how breathing signals affect BMI based on MI. Breathing has been shown to have a key effect on numerous human functions, including, perceptual, cognitive and motor functions. However, currently not much is known about the role of respiratory signals in BMI and such signals have rather been considered as physiological noise. In my thesis, I evaluated how the breathing process affects the correlates of MI (ERD in mu and beta bands) as well as actual BMI performance. The results provide an extensive analysis regarding the effect of the breathing cycle specifically on mu-ERDs, showing stronger ERD during the late expiration phase. Moreover, I identified a link between breathing and BMI performance and propose that breathing signals are a valuable predictor for BMI performance highlighting the importance of monitoring such signals and, more generally, present the interoceptive system as a key component of motor preparation and motor imagery

EPFL2021

Influence of Facial Feedback and Mind Perception During a Cooperative Human-Robot Task in Schizophrenia

Aude Billard, Laura Bénédicte Marine Cohen, Mahdi Khoramshahi

Rapid progress in the area of humanoid robots offers tremendous possibilities for investigating and improving social competences in people with social deficits, but remains yet unexplored in schizophrenia. In this study, we examined the influence of social feedbacks elicited by a humanoid robot on motor coordination during a human-robot interaction. Twenty-two schizophrenia patients and twenty-two matched healthy controls underwent a collaborative motor synchrony task with the iCub humanoid robot. Results revealed that positive social feedback had a facilitatory effect on motor coordination in the control participants compared to non-social positive feedback. This facilitatory effect was not present in schizophrenia patients, whose social-motor coordination was similarly impaired in social and non-social feedback conditions. Furthermore, patients’ cognitive flexibility impairment and antipsychotic dosing were negatively correlated with patients’ ability to synchronize hand movements with iCub. Overall, our findings reveal that patients have marked difficulties to exploit facial social cues elicited by a humanoid robot to modulate their motor coordination during human-robot interaction, partly accounted for by cognitive deficits and medication. This study opens new perspectives for comprehension of social deficits in this mental disorder.

2017

Virtual reality improves embodiment and neuropathic pain caused by spinal cord injury

Olaf Blanke, Estelle Palluel, Polona Pozeg, Roberta Ronchi, Marco Solcà

Objective: To investigate changes in body ownership and chronic neuropathic pain in patients with spinal cord injury (SCI) using multisensory own body illusions and virtual reality (VR). Methods: Twenty patients with SCI with paraplegia and 20 healthy control participants (HC) participated in 2 factorial, randomized, repeated-measures design studies. In the virtual leg illusion (VLI), we applied asynchronous or synchronous visuotactile stimulation to the participant's back (either immediately above the lesion level or at the shoulder) and to the virtual legs as seen on a VR head-mounted display. We tested the effect of the VLI on the sense of leg ownership (questionnaires) and on perceived neuropathic pain (visual analogue scale pain ratings). We compared illusory leg ownership with illusory global body ownership (induced in the full body illusion [FBI]), by applying asynchronous or synchronous visuotactile stimulation to the participant's back and the back of a virtual body as seen on a head-mounted display. Results: Our data show that patients with SCI are less sensitive to multisensory stimulations inducing illusory leg ownership (as compared to HC) and that leg ownership decreased with time since SCI. In contrast, we found no differences between groups in global body ownership as tested in the FBI. VLI and FBI were both associated with mild analgesia that was only during the VLI specific for synchronous visuotactile stimulation and the lower back position. Conclusions: The present findings show that VR exposure using multisensory stimulation differently affected leg vs body ownership, and is associated with mild analgesia with potential for SCI neurorehabilitation protocols.

Lippincott Williams & Wilkins2017

Motor state transitions and Breathing in Brain Machine Interfaces

Bastien Orset

EPFL2021