No / This study investigated the importance of binocular vision to foot placement accuracy when stepping onto a floor-based target during gait initiation. Starting from stationary, participants placed alternate feet onto targets sequentially positioned along a straight travel path with the added constraint that the initial target (target 1) could move in the medio-lateral (M-L) direction. Repeated trials when target 1 remained stationary or moved laterally at the instant of lead-limb toe-off (TO) or 200 ms after TO (early swing) were undertaken under binocular and monocular viewing. Catch trials when target 1 shifted medially were also undertaken. Foot-reach kinematics, foot trajectory corrections and foot placement accuracy for the step onto target 1 were determined via 3D motion analyses. Peak foot-reach velocity and initial foot-reach duration were unaffected by vision condition but terminal foot-reach duration was prolonged under monocular conditions (p = 0.002). Foot trajectory alteration onsets were unaffected by vision condition, but onsets occurred sooner when the target shifted in early swing compared to at TO (p = 0.033). M-L foot placement accuracy decreased (p = 0.025) and variability increased (p = 0.05) under monocular conditions, particularly when stepping onto the moving target. There was no difference between vision conditions in A-P foot placement accuracy. Results indicate that monocular vision provides sufficient information to determine stepping distance and correctly transport the foot towards the target but binocular vision is required to attain a precise M-L foot placement; particularly so when stepping onto a moving target. These findings are in agreement with those found in the reaching and grasping literature, indicating that binocular vision is important for end-point precision. / The Health Foundation, UK. Grant (3991/3322)

Afferent somatosensory inputs ascend from the periphery to the cortex carrying information about touch that is critical for planning motor responses. At the cortical level, this information is subject to modulation from its earliest arrival in somatosensory cortex where factors such as task-relevance begin to shape how the sensory signals are processed. The goal of such modulation is largely to facilitate the extraction of relevant sensory information (and suppression of irrelevant signals) early in the processing stream, and these functions are in part carried out by top-down influences from cortical and sub-cortical structures. Efforts to understand the mechanisms contributing to modulation of sensory-specific cortex have revealed that crossmodal signals (i.e. simultaneously presented stimuli from a different modality) can also influence early sensory processing, but the precise nature of this modulation and what may drive it is largely unknown. It is the purpose of this thesis to investigate the modulation of somatosensory cortex, specifically how task-relevant modulation of somatosensory cortex might be influenced by crossmodal (visual) stimuli, and whether specific task requirements have any bearing on SI excitability. The studies comprising this thesis aim to address these gaps in our mechanistic understanding of the networks involved in modulating somatosensory cortex. Studies 1 and 2 employed functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) to investigate how task-relevant visual and vibrotactile stimuli modulate somatosensory cortex and to probe the role of a frontoparietal network in mediating this modulation. Studies 3 and 4 also used EEG to determine how manipulating the relevance of the stimuli affects the modulation of somatosensory event-related potentials (ERPs), and to probe how task-specific sensory-motor requirements mediate excitability in somatosensory cortex as well as frontal and parietal regions. The results of this thesis provide insight into the factors that modulate somatosensory cortex and the role of a fronto-parietal network in subserving these modulations.

Afferent somatosensory inputs ascend from the periphery to the cortex carrying information about touch that is critical for planning motor responses. At the cortical level, this information is subject to modulation from its earliest arrival in somatosensory cortex where factors such as task-relevance begin to shape how the sensory signals are processed. The goal of such modulation is largely to facilitate the extraction of relevant sensory information (and suppression of irrelevant signals) early in the processing stream, and these functions are in part carried out by top-down influences from cortical and sub-cortical structures. Efforts to understand the mechanisms contributing to modulation of sensory-specific cortex have revealed that crossmodal signals (i.e. simultaneously presented stimuli from a different modality) can also influence early sensory processing, but the precise nature of this modulation and what may drive it is largely unknown. It is the purpose of this thesis to investigate the modulation of somatosensory cortex, specifically how task-relevant modulation of somatosensory cortex might be influenced by crossmodal (visual) stimuli, and whether specific task requirements have any bearing on SI excitability. The studies comprising this thesis aim to address these gaps in our mechanistic understanding of the networks involved in modulating somatosensory cortex. Studies 1 and 2 employed functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) to investigate how task-relevant visual and vibrotactile stimuli modulate somatosensory cortex and to probe the role of a frontoparietal network in mediating this modulation. Studies 3 and 4 also used EEG to determine how manipulating the relevance of the stimuli affects the modulation of somatosensory event-related potentials (ERPs), and to probe how task-specific sensory-motor requirements mediate excitability in somatosensory cortex as well as frontal and parietal regions. The results of this thesis provide insight into the factors that modulate somatosensory cortex and the role of a fronto-parietal network in subserving these modulations.

Objectives: Our thesis is focused on correlation of lateral (side) preferencies of lower limbs and quality of sensorimotor control. Our aim is to figure out whether there is difference in laterality of sensorimotor control of lower limbs and if so, whether there is correlation with side preferency. Methods: Study is made on 18 volunteers. We tested somatosenzoric system, specifically two-point discrimination, graphesthesia, pallesthesia, statesthesia, kinesthesia. We used a questionnare to determine side preferency of lower limbs. We used paired sample t- tests, with level of importance p=0,05. Results: According to t-tests, there are no differencies in sensorimotor control in lower limbs. According to those results, it is not possible to determine the difference in sensorimotor control due to lower limb preferency. Summary: There is no difference in sides in sensorimotor control of lower limbs.

No description available.

Le contrôle sensorimoteur du pied est le fondement des adaptations de l’Homme à son environnement. La station debout et la marche nécessitent l’intervention de toutes les composantes du contrôle sensorimoteur, les mécanorécepteurs plantaires renseignant le système nerveux central sur la position du corps dans l'espace. Notre travail de thèse a consisté en un premier temps à établir un protocole permettant de quantifier la sensation tactile plantaire qui nous a permis de nous intéresser à l’effet des orthèses plantaires sur la perception tactile plantaire. Nos résultats mettent en évidence chez la majorité de nos sujets, que les orthèses appliquées sur les seuls appuis rétrocapitaux augmentent la discrimination des plus faibles charges mécaniques après 30 jours de port de semelles. Ces variations dépendent de la position du pied lors de la station debout et du pattern de marche. Nous avons aussi exploré le contrôle moteur lors du maintien de la station debout et d’un exercice de course à vitesse maximale. Après un effort statique maximal recrutant de façon sélective les muscles inverseurs du pied (tibialis antérior, TA), les surfaces d’appui plantaires et la surface du trajet du barycentre augmentent, il existe une altération du réflexe myotatique dans le seul TA faisant suite à des signes de fatigue électromyographique (réduction de fréquence médiane) après appui maximal. Faisant suite à un effort dynamique maximal (course sur tapis roulant), nous observons les mêmes phénomènes : augmentation des surfaces d’appui plantaire et du trajet du barycentre des pressions, et diminution de la fréquence médiane dans le seul muscle TA aux vitesses de course les plus élevées. / The sensorimotor control of foot placement and motion plays a key role in the adaptive response of human being to his environment. The participation of both sensory and motor components is needed to control the foot placement during gait and posture and mechanoreceptors in the foot sole give major information on the body position. First, we established a protocol to quantify the sensation of foot sole pressure stimulation, which allowed us to examine the effects of metatarsal pads, and heel lifts in healthy subjects. We observed that 30-days of occupational activities with metatarsal pads elicited significant changes in sensation, lowering the threshold for the detection of the lowest pressure loads and, depending on the pattern of foot placement during upright standing and walking, modifying the global gain for the foot sensation. Second, we examined the consequences of fatiguing static contraction of foot invertor muscles (tibialis anterior or TA) and of maximal running exercise on a treadmill on post-test changes in foot placement using a baropodometer, maximal force production by TA. Power spectrum analyses of electromyographic (EMG) events were performed during both static and dynamic efforts and we also explored the myotatic reflexes through the recording of the tonic vibratory response (TVR) in foot muscles. Our results showed significant changes in post-test foot placement in the direction of foot eversion in both situations, significant decrease in maximal inversion force, a leftward shift of EMG spectrum in the sole TA muscle, indicating EMG signs of fatigue, and 4) significant reduction of TVR amplitude in the sole TA muscle after sustained static effort.

Un robot autonome collaborant avec des humains doit être capable d'apprendre à se déplacer et à manipuler des objets dans la même tâche. Dans une approche classique, on considère des modules fonctionnels indépendants gérant les différents aspects de la tâche (navigation, contrôle du bras...). A l'opposé, l'objectif de cette thèse est de montrer que l'apprentissage de tâches de natures différentes peut être abordé comme un problème d'apprentissage d'attracteurs sensorimoteurs à partir d'un petit nombre de structures non spécifiques à une tâche donnée. Nous avons donc proposé une architecture qui permet l'apprentissage et l'encodage d'attracteurs pour réaliser aussi bien des tâches de navigation que de contrôle d'un bras.Comme point de départ, nous nous sommes appuyés sur un modèle inspiré des cellules de lieu pour la navigation d'un robot autonome. Des apprentissages en ligne et interactifs de couples lieu/action sont suffisants pour faire émerger des bassins d'attraction permettant à un robot autonome de suivre une trajectoire. En interagissant avec le robot, on peut corriger ou orienter son comportement. Les corrections successives et leur encodage sensorimoteur permettent de définir le bassin d'attraction de la trajectoire. Ma première contribution a été d'étendre ce principe de construction d'attracteurs sensorimoteurs à un contrôle en impédance pour un bras robotique. Lors du maintien d'une posture proprioceptive, les mouvements du bras peuvent être corrigés par une modification en-ligne des commandes motrices exprimées sous la forme d'activations musculaires. Les attracteurs moteurs résultent alors des associations simples entre l'information proprioceptive du bras et ces commandes motrices. Dans un second temps, j'ai montré que le robot pouvait apprendre des attracteursvisuo-moteurs en combinant les informations proprioceptives et visuelles. Le contrôle visuo-moteur correspond à un homéostat qui essaie de maintenir un équilibre entre ces deux informations. Dans le cas d'une information visuelle ambiguë, le robot peut percevoir un stimulus externe (e.g. la main d'un humain) comme étant sa propre pince. Suivant le principe d'homéostasie, le robot agira pour réduire l'incohérence entre cette information externe et son information proprioceptive. Il exhibera alors un comportement d'imitation immédiate des gestes observés. Ce mécanisme d'homéostasie, complété par une mémoire des séquences observées et l'inhibition des actions durant l'observation, permet au robot de réaliser des imitations différées et d'apprendre par observation. Pour des tâches plus complexes, nous avons aussi montré que l'apprentissage de transitions peut servir de support pour l'apprentissage de séquences de gestes, comme c'était le cas pour l'apprentissage de cartes cognitives en navigation. L'utilisation de contextes motivationnels permet alors le choix entre les différentes séquences apprises.Nous avons ensuite abordé le problème de l'intégration dans une même architecture de comportements impliquant une navigation visuomotrice et le contrôle d'un bras robotique pour la préhension d'objets. La difficulté est de pouvoir synchroniser les différentes actions afin que le robot agisse de manière cohérente. Les comportements erronés du robot sont détectés grâce à l'évaluation des actions proposées par le modèle vis à vis des corrections imposées par le professeur humain. Un apprentissage de ces situations sous la forme de contextes multimodaux modulant la sélection d'action permet alors d'adapter le comportement afin que le robot reproduise la tâche désirée.Pour finir, nous présentons les perspectives de ce travail en terme de contrôle sensorimoteur, pour la navigation comme pour le contrôle d'un bras robotique, et son extension aux questions d'interface homme/robot. Nous insistons sur le fait que différents types d'imitation peuvent être le fruit des propriétés émergentes d'une architecture de contrôle sensorimotrice. / An autonomous robot collaborating with humans should be able to learn how to navigate and manipulate objects in the same task. In a classical approach, independent functional modules are considered to manage the different aspects of the task (navigation, arm control,...) . To the contrary, the goal of this thesis is to show that learning tasks of different kinds can be tackled by learning sensorimotor attractors from a few task nonspecific structures. We thus proposed an architecture which can learn and encode attractors to perform navigation tasks as well as arm control.We started by considering a model inspired from place-cells for navigation of autonomous robots. On-line and interactive learning of place-action couples can let attraction basins emerge, allowing an autonomous robot to follow a trajectory. The robot behavior can be corrected and guided by interacting with it. The successive corrections and their sensorimotor coding enables to define the attraction basin of the trajectory. My first contribution was to adapt this principle of sensorimotor attractor building for the impedance control of a robot arm. While a proprioceptive posture is maintained, the arm movements can be corrected by modifying on-line the motor command expressed as muscular activations. The resulting motor attractors are simple associations between the proprioceptive information of the arm and these motor commands. I then showed that the robot could learn visuomotor attractors by combining the proprioceptive and visual information with the motor attractors. The visuomotor control corresponds to a homeostatic system trying to maintain an equilibrium between the two kinds of information. In the case of ambiguous visual information, the robot may perceive an external stimulus (e.g. a human hand) as its own hand. According to the principle of homeostasis, the robot will act to reduce the incoherence between this external information and its proprioceptive information. It then displays a behavior of immediately observed gestures imitation. This mechanism of homeostasis, completed by a memory of the observed sequences and action inhibition capability during the observation phase, enables a robot to perform deferred imitation and learn by observation. In the case of more complex tasks, we also showed that learning transitions can be the basis for learning sequences of gestures, like in the case of cognitive map learning in navigation. The use of motivational contexts then enables to choose between different learned sequences.We then addressed the issue of integrating in the same architecture behaviors involving visuomotor navigation and robotic arm control to grab objects. The difficulty is to be able to synchronize the different actions so the robot act coherently. Erroneous behaviors of the robot are detected by evaluating the actions predicted by the model with respect to corrections forced by the human teacher. These situations can be learned as multimodal contexts modulating the action selection process in order to adapt the behavior so the robot reproduces the desired task.Finally, we will present the perspectives of this work in terms of sensorimotor control, for both navigation and robotic arm control, and its link to human robot interface issues. We will also insist on the fact that different kinds of imitation behavior can result from the emergent properties of a sensorimotor control architecture.

Regarder ou saisir un objet constituent, à première vue, des actes simples et triviaux. De tels mouvements nécessitent, entre autres, l’existence de complexes processus entre entrées sensorielles et sorties motrices afin de compenser l’effet de la variabilité sensorimotrice inhérente au système. Un concept clé décrit ces processus de contrôle : les modèles internes. Il s’agit de représentations dynamiques de l’état de nos appareils sensorimoteurs, inscrites au sein d’un réseau d’aires cérébrales, permettant la comparaison entre un mouvement désiré (parfait) et le mouvement réalisé (bruité). Lorsqu’une différence est perçue suite à cette comparaison, un signal d’erreur motrice (EM) serait envoyé afin d’ajuster le mouvement en cours d’exécution. Nous avons réalisé une première étude chez l’Homme afin de définir le rôle des modèles internes lors d’un acte sensorimoteur simple: la saccade oculaire. Une tâche originale nous a permis d’introduire du bruit moteur artificiel (saut de cible intrasaccadique) durant une séquence saccadique. Les résultats valident l’existence d’un mécanisme de contrôle sensorimoteur optimal et confirme la prédiction d’un modèle basé sur la théorie des filtres de Kalman, pondérant la «confiance» accordée aux mouvements désirés versus réalisés en fonction de leur fiabilité (l’inverse de leur variance). Nous nous sommes alors attachés à rechercher les substrats cérébraux du calcul de l’EM en adaptant nos paradigmes chez le macaque rhésus. Nous avons enregistré l’activité électrophysiologique neuronale unitaire puis réalisé des inactivations réversibles au sein de l’aire latérale intrapariétale (LIP), région clé pour l’intégration visuo-saccadique. Nos résultats suggèrent que le cortex pariétal serait impliqué dans l’ajustement moteur du système saccadique. Le cortex pariètal pourrait ainsi accumuler des évidences (signaux d’erreur donnés par la copie d’efférence et les retours sensoriels) quant à la présence d’erreur oculomotrice puis inciter le reste du réseau saccadique à corriger cette dernière. Ce mécanisme permettrait alors d’optimiser la plupart des actions motrices réalisées dans des contextes sensorimoteurs constamment bruités / Looking at or grasping an object are simple and trivial actions. However, these types of movements require complex processing of sensory and motor information in order to compensate for the natural variability within the sensorimotor system. A key concept describes these control processes: internal models. These models are dynamical representations of the state of our effectors, supported by a network of cerebral areas, which allow the comparison between the desired movement (perfect) and the realised movement (noisy). When a difference is perceived, a motor error (ME) signal is sent in order to adjust the ongoing movement. We performed a first study with human subjects to define the role of internal models during a simple sensorimotor action: a saccade. We developed an original task in order to introduce artificial motor noise (intrasaccadic target jump) during a sequence of saccades. These results validates the existence of an optimal sensorimotor control mechanism and confirms the predictions of a model based on the Kalman filter theory. This optimal control implies a balance between the reliability given to the desired movements versus the executed movements as a function of their uncertaincy (correlate to their variability). We then investigated the neural substrates of the ME estimation by adapting our protocols for use with rhesus monkeys. We recorded the electrophysiological activity of unitary neurons and performed reversible inactivations in the lateral intraparietal area (LIP), a key area for visuo-saccadic integration. Our results suggest, therefore, that the parietal cortex plays a role in the motor adjustment of the saccadic system. We postulate that parietal cortex could accumulate evidence (i.e. error signal given by efferent copy and sensorial feedback) on the necessity to perform a corrective saccade. When the amount of evidence exceeds an error threshold, the decision to trigger a correction could be made. This process could allow the optimization of these motor actions within noisy sensorimotor context

L'amputation du membre supérieur, dont la prévalence est comparable à celle des maladies orphelines, induit chez les patients une perte considérable d'autonomie dans la majorité des tâches simples de la vie quotidienne. Pour pallier ces difficultés, les prothèses myoélectriques actuelles proposent une multitude de mouvements possibles. Cependant, leur contrôle non intuitif et lourd cognitivement requiert un apprentissage long et difficile, qui pousse une proportion importante de patients amputés à l'abandon de la prothèse. Dans cette thèse, nous avons cherché à identifier l'origine des difficultés et les manques du contrôle myoélectrique en comparaison au contrôle sensorimoteur naturel, dans le but à terme de proposer de meilleures solutions de restitution et de suppléance. Pour cela, nous avons manipulé diverses conditions expérimentales dans un contexte d'interface homme-machine simplifié où des sujets non amputés contrôlent un curseur sur un écran à partir de contractions isométriques, i.e. des contractions qui n'engendrent pas de mouvement. Cette condition isométrique nous a permis de nous approcher de la condition de la personne amputée contrôlant sa prothèse à partir de l'activité électrique (EMG) de ses muscles résiduels, en absence de mouvement articulaire. Durant une tâche d'atteinte de cible, nous avons entre autre démontré le bénéfice d'une adaptation conjointe du décodeur qui traduit les activités EMG en mouvement du curseur, venant s'ajouter à la propre adaptation du plan de mouvement des sujets en réponse à des perturbations orientées. De plus, il a été mis en évidence que ce bénéfice est d'autant plus important que la dynamique d'adaptation artificielle du décodeur s'inspire de celle de l'Homme. Dans des tâches d'acquisition et de poursuite de cible, impliquant davantage les mécanismes de régulation en ligne du mouvement, nous avons mis en évidence l'importance d'une congruence immédiate entre les informations sensorimotrices et la position du curseur à l'écran pour permettre des corrections rapides et efficaces. Dans une condition où le niveau de bruit du système est relativement faible, comme avec l'utilisation du signal de forces plus stable que l'habituel signal EMG, cette congruence explique, en partie, la supériorité d'un contrôle d'ordre 0 (i.e. position) sur un contrôle d'ordre 1 (i.e.} vitesse). Cependant, dès lors que le niveau de bruit est trop important, ce qui est le cas avec le signal EMG, le filtrage induit par l'intégration nécessaire au contrôle vitesse fait que celui-ci devient plus performant que le contrôle position. L'ensemble de ces résultats suggèrent qu'un décodeur adaptatif et intuitif, respectant et suppléant au mieux les boucles du contrôle sensorimoteur naturel, est le plus à même de faciliter le contrôle des futures prothèses. / Upper limb amputation, although quite rare, induces enormous loss of autonomy for patients in most daily life activities. To overcome this loss, current myoelectric prosthesis offers a multitude of possible movements. However, current controls of these movements are typically non-intuitive and cognitively demanding, leading to a high abandon rate in response to the long and tedious learning involved. In this thesis, we aimed at identifying difficulties and gaps associated with myoelectric controls when compared to natural sensorimotor control, with the long term goal of informing the design of better solutions for prosthesis control. To do so, we manipulated several experimental conditions in a simplified human-machine interface, where non-amputated subjects controlled a cursor on a computer screen from isometric contractions, i.e. muscle contractions produced in the absence of joint movement. This isometric condition was designed to get closer to a situation in which an amputee controls a myoelectric prosthesis using electrical activity (EMG) of his/her residual muscles, without movement of the missing limb. During aiming movements, we demonstrated the benefits of adapting the decoder that translate muscle activities into cursor movement in conjunction with the own subject’s adaptation of the planned movement direction in response to oriented perturbations. Furthermore, these benefits were showed to be even more important as the artificial decoder adaptation was inspired by the modeled adaptation of a human. In reaching and tracking movements toward fixed and moving targets, which increasingly involve online movement regulations, we revealed the importance of an immediate congruency between sensorimotor information and the cursor position on the screen for timely and efficient corrections. For conditions in which the level of noise associated with the control signal is relatively low, such as when using force that is more stable than the usual EMG signal used, this congruency partly explains the better performance obtained with zero order control (i.e. position) when compared to first order control (i.e. velocity). However, when the noise level increases, as is the case with EMG signals, the filtering property associated with the integration involved in a velocity control elicits better performances than with a position control. Taken together, these results suggest that intuitive and adaptive decoder, that supplies and judiciously complements natural sensorimotor feedback loops, is promising to facilitate future prosthesis controls.

During dexterous manipulation with the fingertips, forces are applied to objects' surfaces. To achieve grasp stability, these forces must be appropriate given the properties of the objects and the skin of the fingertips, and the nature of the task. It has been demonstrated that tactile sensors in the fingertips provide crucial information about both object properties and mechanical events critical for the control of fingertip forces, while in certain tasks vision may also contribute to predictions of required fingertip actions. This thesis focuses on two specific aspects of the sensory control of manipulation: (i) how individual fingers are controlled for grasp stability when people restrain objects subjected to unpredictable forces tangential to the grasped surfaces, and (ii) how tactile sensors in the fingertips encode direction of fingertip forces and shape of surfaces contacted by the fingertips. When restraining objects with two fingers, subjects adjust the fingertip forces to the local friction at each digit-object interface for grasp stability. This is accomplished primarily by partitioning the tangential force between the digits in a way that reflects the local friction whereas the normal forces at the involved digits are scaled by the average friction and the total load. The neural control mechanisms in this task rely on tactile information pertaining to both the friction at each digit-object interface and the development of tangential load. Moreover, these mechanisms controlled the force application at individual digits while at the same time integrating sensory inputs from all digits involved in the task. Microneurographical recordings in awake humans shows that most SA-I, SA-II and FA-I sensors in the distal phalanx are excited when forces similar to those observed during actual manipulation are applied to the fingertip. Moreover, the direction of the fingertip force influences the impulse rates in most afferents and their responses are broadly tuned to a preferred direction. The preferred direction varies among the afferents and, accordingly, ensembles of afferents can encode the direction of fingertip forces. The local curvature of the object in contact with the fingertip also influenced the impulse rates in most afferents, providing a curvature contrast signals within the afferent populations. Marked interactions were observed in the afferents' responses to object curvature and force direction. Similar findings were obtained for the onset latency in individual afferents. Accordingly, for ensembles of afferents, the order by which individual afferents initially discharge to fingertip events effectively represents parameters of fingertip stimulation. This neural code probably represents the fastest possible code for transmission of parameters of fingertip stimuli to the CNS.