Switching in Feedforward Control of Grip Force During Tool-Mediated Interaction With Elastic Force Fields

Switched systems are common in artificial control systems. Here, we suggest that the brain adopts a switched feedforward control of grip forces during manipulation of objects. We measured how participants modulated grip force when interacting with soft and rigid virtual objects when stiffness varied continuously between trials. We identified a sudden phase transition between two forms of feedforward control that differed in the timing of the synchronization between the anticipated load force and the applied grip force. The switch occurred several trials after a threshold stiffness level in the range 100–200 N/m. These results suggest that in the control of grip force, the brain acts as a switching control system. This opens new research questions as to the nature of the discrete state variables that drive the switching

Assessing Performance, Role Sharing, and Control Mechanisms in Human-Human Physical Interaction for Object Manipulation

abstract: Object manipulation is a common sensorimotor task that humans perform to interact with the physical world. The first aim of this dissertation was to characterize and identify the role of feedback and feedforward mechanisms for force control in object manipulation by introducing a new feature based on force trajectories to quantify the interaction between feedback- and feedforward control. This feature was applied on two grasp contexts: grasping the object at either (1) predetermined or (2) self-selected grasp locations (“constrained” and “unconstrained”, respectively), where unconstrained grasping is thought to involve feedback-driven force corrections to a greater extent than constrained grasping. This proposition was confirmed by force feature analysis. The second aim of this dissertation was to quantify whether force control mechanisms differ between dominant and non-dominant hands. The force feature analysis demonstrated that manipulation by the dominant hand relies on feedforward control more than the non-dominant hand. The third aim was to quantify coordination mechanisms underlying physical interaction by dyads in object manipulation. The results revealed that only individuals with worse solo performance benefit from interpersonal coordination through physical couplings, whereas the better individuals do not. This work showed that naturally emerging leader-follower roles, whereby the leader in dyadic manipulation exhibits significant greater force changes than the follower. Furthermore, brain activity measured through electroencephalography (EEG) could discriminate leader and follower roles as indicated power modulation in the alpha frequency band over centro-parietal areas. Lastly, this dissertation suggested that the relation between force and motion (arm impedance) could be an important means for communicating intended movement direction between biological agents.Dissertation/ThesisDoctoral Dissertation Biomedical Engineering 201

Motor Learning and Motor Control Mechanisms in an Haptic Dyad

The word \u201cdyad\u201d defines the interaction between two human or cybernetic organisms. During such interaction, there is an organized flow of information between the two elements of the dyad, in a fully bidirectional manner. With this mutual knowledge they are able to understand the actual state of the dyad as well as the previous states and, in some cases, to predict a response for possible scenarios. In the studies presented in this thesis we aim to understand the kind of information exchanged during dyadic interaction and the way this information is communicated from one individual to another not only in a purely dyadic context but also in a more general social sense, namely dissemination of knowledge via physical and non-physical interpersonal interactions. More specifically, the focus of the experimental activities will be on motor learning and motor control mechanisms, in the general context of embodied motor cognition. Solving a task promotes the creation of an internal representation of the dynamical characteristics of the working environment. An understanding of the environmental characteristics allows the subjects to become proficient in such task. We also intended to evaluate the application of such a model when it is created and applied under different conditions and using different body parts. For example, we investigated how human subjects can generalize the acquired model of a certain task, carried out by means of the wrist, in the sense of mapping the skill from the distal degrees of freedom of the wrist to the proximal degrees of freedom of the arm (elbow & shoulder), under the same dynamical conditions. In the same line of reasoning, namely that individuals solving a certain task need to develop an internal model of the environment, we investigated in which manner different skill levels of the two partners of a dyad interfere with the overall learning/training process. It is known indeed that internal models are essential for allowing dyadic member to apply different motor control strategies for completing the task. Previous studies have shown that the internal model created in a solo performance can be shared and exploited in a dyadic collaboration to solve the same task. In our study we went a step forward by demonstrating that learning an unstable task in a dyad propitiates the creation of a shared internal model of the task, which includes the representation of the mutual forces applied by the partners. Thus when the partners in the dyad have different knowledge levels of the task, the representation created by the less proficient partner can be mistaken since it may include the proficient partner as part of the dynamical conditions of the task instead of as the assistance helping him to complete the experiments. For this reason we implemented a dyadic learning protocol that allows the na\uefve subject to explore and create an accurate internal model, while exploiting, at the same time, the advantage of working with an skilled partner

Cortical Sensorimotor Mechanisms for Neural Control of Skilled Manipulation

abstract: The human hand is a complex biological system. Humans have evolved a unique ability to use the hand for a wide range of tasks, including activities of daily living such as successfully grasping and manipulating objects, i.e., lifting a cup of coffee without spilling. Despite the ubiquitous nature of hand use in everyday activities involving object manipulations, there is currently an incomplete understanding of the cortical sensorimotor mechanisms underlying this important behavior. One critical aspect of natural object grasping is the coordination of where the fingers make contact with an object and how much force is applied following contact. Such force-to-position modulation is critical for successful manipulation. However, the neural mechanisms underlying these motor processes remain less understood, as previous experiments have utilized protocols with fixed contact points which likely rely on different neural mechanisms from those involved in grasping at unconstrained contacts. To address this gap in the motor neuroscience field, transcranial magnetic stimulation (TMS) and electroencephalography (EEG) were used to investigate the role of primary motor cortex (M1), as well as other important cortical regions in the grasping network, during the planning and execution of object grasping and manipulation. The results of virtual lesions induced by TMS and EEG revealed grasp context-specific cortical mechanisms underlying digit force-to-position coordination, as well as the spatial and temporal dynamics of cortical activity during planning and execution. Together, the present findings provide the foundation for a novel framework accounting for how the central nervous system controls dexterous manipulation. This new knowledge can potentially benefit research in neuroprosthetics and improve the efficacy of neurorehabilitation techniques for patients affected by sensorimotor impairments.Dissertation/ThesisDoctoral Dissertation Neuroscience 201

Distributed Sensing and Stimulation Systems Towards Sense of Touch Restoration in Prosthetics

Modern prostheses aim at restoring the functional and aesthetic characteristics of the lost limb. To foster prosthesis embodiment and functionality, it is necessary to restitute both volitional control and sensory feedback. Contemporary feedback interfaces presented in research use few sensors and stimulation units to feedback at most two discrete feedback variables (e.g. grasping force and aperture), whereas the human sense of touch relies on a distributed network of mechanoreceptors providing high-fidelity spatial information. To provide this type of feedback in prosthetics, it is necessary to sense tactile information from artificial skin placed on the prosthesis and transmit tactile feedback above the amputation in order to map the interaction between the prosthesis and the environment. This thesis proposes the integration of distributed sensing systems (e-skin) to acquire tactile sensation, and non-invasive multichannel electrotactile feedback and virtual reality to deliver high-bandwidth information to the user. Its core focus addresses the development and testing of close-loop sensory feedback human-machine interface, based on the latest distributed sensing and stimulation techniques for restoring the sense of touch in prosthetics. To this end, the thesis is comprised of two introductory chapters that describe the state of art in the field, the objectives and the used methodology and contributions; as well as three studies distributed over stimulation system level and sensing system level. The first study presents the development of close-loop compensatory tracking system to evaluate the usability and effectiveness of electrotactile sensory feedback in enabling real-time close-loop control in prosthetics. It examines and compares the subject\u2019s adaptive performance and tolerance to random latencies while performing the dynamic control task (i.e. position control) and simultaneously receiving either visual feedback or electrotactile feedback for communicating the momentary tracking error. Moreover, it reported the minimum time delay needed for an abrupt impairment of users\u2019 performance. The experimental results have shown that electrotactile feedback performance is less prone to changes with longer delays. However, visual feedback drops faster than electrotactile with increased time delays. This is a good indication for the effectiveness of electrotactile feedback in enabling close- loop control in prosthetics, since some delays are inevitable. The second study describes the development of a novel non-invasive compact multichannel interface for electrotactile feedback, containing 24 pads electrode matrix, with fully programmable stimulation unit, that investigates the ability of able-bodied human subjects to localize the electrotactile stimulus delivered through the electrode matrix. Furthermore, it designed a novel dual parameter -modulation (interleaved frequency and intensity) and compared it to conventional stimulation (same frequency for all pads). In addition and for the first time, it compared the electrotactile stimulation to mechanical stimulation. More, it exposes the integration of virtual prosthesis with the developed system in order to achieve better user experience and object manipulation through mapping the acquired real-time collected tactile data and feedback it simultaneously to the user. The experimental results demonstrated that the proposed interleaved coding substantially improved the spatial localization compared to same-frequency stimulation. Furthermore, it showed that same-frequency stimulation was equivalent to mechanical stimulation, whereas the performance with dual-parameter modulation was significantly better. The third study presents the realization of a novel, flexible, screen- printed e-skin based on P(VDF-TrFE) piezoelectric polymers, that would cover the fingertips and the palm of the prosthetic hand (particularly the Michelangelo hand by Ottobock) and an assistive sensorized glove for stroke patients. Moreover, it developed a new validation methodology to examine the sensors behavior while being solicited. The characterization results showed compatibility between the expected (modeled) behavior of the electrical response of each sensor to measured mechanical (normal) force at the skin surface, which in turn proved the combination of both fabrication and assembly processes was successful. This paves the way to define a practical, simplified and reproducible characterization protocol for e-skin patches In conclusion, by adopting innovative methodologies in sensing and stimulation systems, this thesis advances the overall development of close-loop sensory feedback human-machine interface used for restoration of sense of touch in prosthetics. Moreover, this research could lead to high-bandwidth high-fidelity transmission of tactile information for modern dexterous prostheses that could ameliorate the end user experience and facilitate it acceptance in the daily life

Neglect-Like Effects on Drawing Symmetry Induced by Adaptation to a Laterally Asymmetric Visuomotor Delay

In daily interactions, our sensorimotor system accounts for spatial and temporal discrepancies between the senses. Functional lateralization between hemispheres causes differences in attention and in the control of action across the left and right workspaces. In addition, differences in transmission delays between modalities affect movement control and internal representations. Studies on motor impairments such as hemispatial neglect syndrome suggested a link between lateral spatial biases and temporal processing. To understand this link, we computationally modeled and experimentally validated the effect of laterally asymmetric delay in visual feedback on motor learning and its transfer to the control of drawing movements without visual feedback. In the behavioral experiments, we asked healthy participants to perform lateral reaching movements while adapting to delayed visual feedback in either left, right, or both workspaces. We found that the adaptation transferred to blind drawing and caused movement elongation, which is consistent with a state representation of the delay. However, the pattern of the spatial effect varied between conditions: whereas adaptation to delay in only the left workspace or in the whole workspace caused selective leftward elongation, adaptation to delay in only the right workspace caused drawing elongation in both directions. We simulated arm movements according to different models of perceptual and motor spatial asymmetry in the representation of delay and found that the best model that accounts for our results combines both perceptual and motor asymmetry between the hemispheres. These results provide direct evidence for an asymmetrical processing of delayed visual feedback that is associated with both perceptual and motor biases that are similar to those observed in hemispatial neglect syndrome

Biomechatronics: Harmonizing Mechatronic Systems with Human Beings

This eBook provides a comprehensive treatise on modern biomechatronic systems centred around human applications. A particular emphasis is given to exoskeleton designs for assistance and training with advanced interfaces in human-machine interaction. Some of these designs are validated with experimental results which the reader will find very informative as building-blocks for designing such systems. This eBook will be ideally suited to those researching in biomechatronic area with bio-feedback applications or those who are involved in high-end research on manmachine interfaces. This may also serve as a textbook for biomechatronic design at post-graduate level

Increasing Transparency and Presence of Teleoperation Systems Through Human-Centered Design

Teleoperation allows a human to control a robot to perform dexterous tasks in remote, dangerous, or unreachable environments. A perfect teleoperation system would enable the operator to complete such tasks at least as easily as if he or she was to complete them by hand. This ideal teleoperator must be perceptually transparent, meaning that the interface appears to be nearly nonexistent to the operator, allowing him or her to focus solely on the task environment, rather than on the teleoperation system itself. Furthermore, the ideal teleoperation system must give the operator a high sense of presence, meaning that the operator feels as though he or she is physically immersed in the remote task environment. This dissertation seeks to improve the transparency and presence of robot-arm-based teleoperation systems through a human-centered design approach, specifically by leveraging scientific knowledge about the human motor and sensory systems. First, this dissertation aims to improve the forward (efferent) teleoperation control channel, which carries information from the human operator to the robot. The traditional method of calculating the desired position of the robot\u27s hand simply scales the measured position of the human\u27s hand. This commonly used motion mapping erroneously assumes that the human\u27s produced motion identically matches his or her intended movement. Given that humans make systematic directional errors when moving the hand under conditions similar to those imposed by teleoperation, I propose a new paradigm of data-driven human-robot motion mappings for teleoperation. The mappings are determined by having the human operator mimic the target robot as it autonomously moves its arm through a variety of trajectories in the horizontal plane. Three data-driven motion mapping models are described and evaluated for their ability to correct for the systematic motion errors made in the mimicking task. Individually-fit and population-fit versions of the most promising motion mapping model are then tested in a teleoperation system that allows the operator to control a virtual robot. Results of a user study involving nine subjects indicate that the newly developed motion mapping model significantly increases the transparency of the teleoperation system. Second, this dissertation seeks to improve the feedback (afferent) teleoperation control channel, which carries information from the robot to the human operator. We aim to improve a teleoperation system a teleoperation system by providing the operator with multiple novel modalities of haptic (touch-based) feedback. We describe the design and control of a wearable haptic device that provides kinesthetic grip-force feedback through a geared DC motor and tactile fingertip-contact-and-pressure and high-frequency acceleration feedback through a pair of voice-coil actuators mounted at the tips of the thumb and index finger. Each included haptic feedback modality is known to be fundamental to direct task completion and can be implemented without great cost or complexity. A user study involving thirty subjects investigated how these three modalities of haptic feedback affect an operator\u27s ability to control a real remote robot in a teleoperated pick-and-place task. This study\u27s results strongly support the utility of grip-force and high-frequency acceleration feedback in teleoperation systems and show more mixed effects of fingertip-contact-and-pressure feedback

Haptics Rendering and Applications

There has been significant progress in haptic technologies but the incorporation of haptics into virtual environments is still in its infancy. A wide range of the new society's human activities including communication, education, art, entertainment, commerce and science would forever change if we learned how to capture, manipulate and reproduce haptic sensory stimuli that are nearly indistinguishable from reality. For the field to move forward, many commercial and technological barriers need to be overcome. By rendering how objects feel through haptic technology, we communicate information that might reflect a desire to speak a physically- based language that has never been explored before. Due to constant improvement in haptics technology and increasing levels of research into and development of haptics-related algorithms, protocols and devices, there is a belief that haptics technology has a promising future

Mécanismes psychophysiques et neuronaux de la compensation dynamique de multiples champs de force : facilitation et anticipation liée à des indices de couleur

Dans cette thèse, nous abordons le contrôle moteur du mouvement du coude à travers deux approches expérimentales : une première étude psychophysique a été effectuée chez les sujets humains, et une seconde implique des enregistrements neurophysiologiques chez le singe. Nous avons recensé plusieurs aspects non résolus jusqu’à présent dans l’apprentissage moteur, particulièrement concernant l’interférence survenant lors de l’adaptation à deux ou plusieurs champs de force anti-corrélés. Nous avons conçu un paradigme où des stimuli de couleur aident les sujets à prédire la nature du champ de force externe actuel avant qu’ils ne l’expérimentent physiquement durant des mouvements d’atteinte. Ces connaissances contextuelles faciliteraient l’adaptation à des champs de forces en diminuant l’interférence. Selon le modèle computationnel de l’apprentissage moteur MOSAIC (MOdular Selection And Identification model for Control), les stimuli de couleur aident les sujets à former « un modèle interne » de chaque champ de forces, à s’en rappeler et à faire la transition entre deux champs de force différents, sans interférence. Dans l’expérience psychophysique, quatre groupes de sujets humains ont exécuté des mouvements de flexion/extension du coude contre deux champs de forces. Chaque force visqueuse était associée à une couleur de l’écran de l’ordinateur et les deux forces étaient anti-corrélées : une force résistante (Vr) a été associée à la couleur rouge de l’écran et l’autre, assistante (Va), à la couleur verte de l’écran. Les deux premiers groupes de sujets étaient des groupes témoins : la couleur de l’écran changeait à chaque bloc de 4 essais, tandis que le champ de force ne changeait pas. Les sujets du groupe témoin Va ne rencontraient que la force assistante Va et les sujets du groupe témoin Vr performaient leurs mouvements uniquement contre une force résistante Vr. Ainsi, dans ces deux groupes témoins, les stimuli de couleur n’étaient pas pertinents pour adapter le mouvement et les sujets ne s’adaptaient qu’à une seule force (Va ou Vr). Dans les deux groupes expérimentaux, cependant, les sujets expérimentaient deux champs de forces différents dans les différents blocs d’essais (4 par bloc), associés à ces couleurs. Dans le premier groupe expérimental (groupe « indice certain », IC), la relation entre le champ de force et le stimulus (couleur de l’écran) était constante. La couleur rouge signalait toujours la force Vr tandis que la force Va était signalée par la couleur verte. L’adaptation aux deux forces anti-corrélées pour le groupe IC s’est avérée significative au cours des 10 jours d’entraînement et leurs mouvements étaient presque aussi bien ajustés que ceux des deux groupes témoins qui n’avaient expérimenté qu’une seule des deux forces. De plus, les sujets du groupe IC ont rapidement démontré des changements adaptatifs prédictifs dans leurs sorties motrices à chaque changement de couleur de l’écran, et ceci même durant leur première journée d’entraînement. Ceci démontre qu’ils pouvaient utiliser les stimuli de couleur afin de se rappeler de la commande motrice adéquate. Dans le deuxième groupe expérimental, la couleur de l’écran changeait régulièrement de vert à rouge à chaque transition de blocs d’essais, mais le changement des champs de forces était randomisé par rapport aux changements de couleur (groupe « indice-incertain », II). Ces sujets ont pris plus de temps à s’adapter aux champs de forces que les 3 autres groupes et ne pouvaient pas utiliser les stimuli de couleurs, qui n’étaient pas fiables puisque non systématiquement reliés aux champs de forces, pour faire des changements prédictifs dans leurs sorties motrices. Toutefois, tous les sujets de ce groupe ont développé une stratégie ingénieuse leur permettant d’émettre une réponse motrice « par défaut » afin de palper ou de sentir le type de la force qu’ils allaient rencontrer dans le premier essai de chaque bloc, à chaque changement de couleur. En effet, ils utilisaient la rétroaction proprioceptive liée à la nature du champ de force afin de prédire la sortie motrice appropriée pour les essais qui suivent, jusqu’au prochain changement de couleur d’écran qui signifiait la possibilité de changement de force. Cette stratégie était efficace puisque la force demeurait la même dans chaque bloc, pendant lequel la couleur de l’écran restait inchangée. Cette étude a démontré que les sujets du groupe II étaient capables d’utiliser les stimuli de couleur pour extraire des informations implicites et explicites nécessaires à la réalisation des mouvements, et qu’ils pouvaient utiliser ces informations pour diminuer l’interférence lors de l’adaptation aux forces anti-corrélées. Les résultats de cette première étude nous ont encouragés à étudier les mécanismes permettant aux sujets de se rappeler d’habiletés motrices multiples jumelées à des stimuli contextuels de couleur. Dans le cadre de notre deuxième étude, nos expériences ont été effectuées au niveau neuronal chez le singe. Notre but était alors d’élucider à quel point les neurones du cortex moteur primaire (M1) peuvent contribuer à la compensation d’un large éventail de différentes forces externes durant un mouvement de flexion/extension du coude. Par cette étude, nous avons testé l’hypothèse liée au modèle MOSAIC, selon laquelle il existe plusieurs modules contrôleurs dans le cervelet qui peuvent prédire chaque contexte et produire un signal de sortie motrice approprié pour un nombre restreint de conditions. Selon ce modèle, les neurones de M1 recevraient des entrées de la part de plusieurs contrôleurs cérébelleux spécialisés et montreraient ensuite une modulation appropriée de la réponse pour une large variété de conditions. Nous avons entraîné deux singes à adapter leurs mouvements de flexion/extension du coude dans le cadre de 5 champs de force différents : un champ nul ne présentant aucune perturbation, deux forces visqueuses anti-corrélées (assistante et résistante) qui dépendaient de la vitesse du mouvement et qui ressemblaient à celles utilisées dans notre étude psychophysique chez l’homme, une force élastique résistante qui dépendait de la position de l’articulation du coude et, finalement, un champ viscoélastique comportant une sommation linéaire de la force élastique et de la force visqueuse. Chaque champ de force était couplé à une couleur d’écran de l’ordinateur, donc nous avions un total de 5 couleurs différentes associées chacune à un champ de force (relation fixe). Les singes étaient bien adaptés aux 5 conditions de champs de forces et utilisaient les stimuli contextuels de couleur pour se rappeler de la sortie motrice appropriée au contexte de forces associé à chaque couleur, prédisant ainsi leur sortie motrice avant de sentir les effets du champ de force. Les enregistrements d’EMG ont permis d’éliminer la possibilité de co-contractions sous-tendant ces adaptations, étant donné que le patron des EMG était approprié pour compenser chaque condition de champ de force. En parallèle, les neurones de M1 ont montré des changements systématiques dans leurs activités, sur le plan unitaire et populationnel, dans chaque condition de champ de force, signalant les changements requis dans la direction, l’amplitude et le décours temporel de la sortie de force musculaire nécessaire pour compenser les 5 conditions de champs de force. Les changements dans le patron de réponse pour chaque champ de force étaient assez cohérents entre les divers neurones de M1, ce qui suggère que la plupart des neurones de M1 contribuent à la compensation de toutes les conditions de champs de force, conformément aux prédictions du modèle MOSAIC. Aussi, cette modulation de l’activité neuronale ne supporte pas l’hypothèse d’une organisation fortement modulaire de M1.In this thesis, we addressed motor control by two experimental approaches: psychophysical studies in human subjects and neurophysiological recordings in non-human primates. We identified unresolved issues concerning interference in motor learning during adaptation of subjects to two or more anti-correlated force fields. We designed paradigms in which arbitrary color stimuli provided contextual cues that allowed subjects to predict the nature of impending external force fields before encountering them physically during arm movements. This contextual knowledge helped to facilitate adaptation to the force fields by reducing this interference. According to one computational model of motor learning (MOdular Selection And Identification model for Control; MOSAIC), the color context cues made it easier for subjects to build “internal models” of each force field, to recall them and to switch between them with minimal interference. In our first experiment, four groups of human subjects performed elbow flexion/extension movements against two anti-correlated viscous force fields. We combined two different colors for the computer monitor background with two forces: resistive (Vr) and assistive (Va). The first two groups were control subjects. In those subjects, the color of the computer monitor changed at regular intervals but the force field remained constant; Vr was presented to the first group while the second group only experienced Va. As a result, the color cues were irrelevant in the two control groups. All control subjects adapted well to the single experienced force field (Vr or Va). In the two experimental groups, in contrast, the anti-correlated force fields and the monitor colors changed repeatedly between short blocks of trials. In the first experimental group (Reliable-cue subjects), there was a consistent relationship between the force and the stimulus (color of the monitor) - the red colour always signalled the resistive force while the green colour always signalled the assistive force. Adaptation to the two anti-correlated forces for the Reliable-cue group was significant during 10 days of training and almost as good as in the Irrelevant-cue groups who only experienced one of the two force fields. Furthermore, the Reliable-cue subjects quickly demonstrated predictive adaptive changes in their motor output whenever the monitor color changed, even during their first day of training, showing that they could use the reliable color context cues to recall the appropriate motor skills. In contrast, the monitor color also changed regularly between red and green in the second experimental group, but the force fields were not consistently associated with the color cue (Unreliable-cue group). These subjects took longer to adapt to the two force fields than the other three groups, and could not use the unreliable color cue change to make predictive changes to their motor output. Nevertheless, all Unreliable-cue subjects developed an ingenious strategy of making a specific “default” arm movement to probe the type of force field they would encounter in the first trial after the monitor color changed and used the proprioceptive feedback about the nature of the field to make appropriate predictive changes to their motor output for the next few trials, until the monitor color changed again, signifying the possibility of a change in force fields. This strategy was effective since the force remained constant in each short block of trials while the monitor color remained unchanged. This showed that the Unreliable-cue subjects were able to extract implicit and explicit information about the structure of the task from the color stimuli and use that knowledge to reduce interference when adapting to anti-correlated forces. The results of this first study encouraged us to advance our understanding of how subjects can recall multiple motor skills coupled to color context stimuli can be recalled, and how this phenomenon can be reflected by the neuronal activity in monkeys. Our aim was to elucidate how neurons of primary motor cortex (M1) can contribute to adaptive compensation for a wide range of different external forces during single-joint elbow flexion/extension movements. At the same time, we aimed to test the hypothesis evoked in the MOSAIC model, whereby multiple controller modules located in the cerebellum may predict each context and produce appropriate adaptive output signals for a small range of task conditions. Also, according to this hypothesis, M1 neurons may receive inputs from many specialized cerebellar controllers and show appropriate response modulations for a wide range of task conditions. We trained two monkeys to adapt their flexion/extension elbow movements against 5 different force-field conditions: null field without any external force disturbance, two anti-correlated viscous forces (assistive and resistive), which depended on movement speed and resembled that used in the human psychophysical study, a resistive elastic force which depended on elbow-joint position and finally, a visco-elastic field that was the linear sum of the elastic and viscous forces field. Each force field was reliably coupled to 5 different computer monitor background colors. The monkeys properly adapted to the 5 different force-field conditions and used the color context cues to recall the corresponding motor skill for the force field associated with each color, so that they could make predictive changes to their motor output before they physically encountered the force fields. EMG recordings eliminated the possibility that a co-contraction strategy was used by the monkeys to adapt to the force fields, since the EMG patterns were appropriate to compensate for each force-field condition. In parallel, M1 neurons showed systematic changes in their activity at the single-neuron and population level in each force-field condition that could signal the required changes in the direction, magnitude and time course of muscle force output required to compensate for the 5 force-field conditions. The patterns of response changes in each force field were consistent enough across M1 neurons to suggest that most M1 neurons contributed to the compensation for all force field conditions, in line with the predictions of the MOSAIC model. Also, these response changes do not support a strongly modular organization for M1