Feedforward and Feedback Control Share an Internal Model of the Arm's Dynamics

The independence of impairments in proprioception and visuomotor adaptation after stroke

BACKGROUND

Proprioceptive impairments are common after stroke and are associated with worse motor recovery and poor rehabilitation outcomes. Motor learning may also be an important factor in motor recovery, and some evidence in healthy adults suggests that reduced proprioceptive function is associated with reductions in motor learning. It is unclear how impairments in proprioception and motor learning relate after stroke. Here we used robotics and a traditional clinical assessment to examine the link between impairments in proprioception after stroke and a type of motor learning known as visuomotor adaptation.

METHODS

We recruited participants with first-time unilateral stroke and controls matched for overall age and sex. Proprioceptive impairments in the more affected arm were assessed using robotic arm position- (APM) and movement-matching (AMM) tasks. We also assessed proprioceptive impairments using a clinical scale (Thumb Localization Test; TLT). Visuomotor adaptation was assessed using a task that systematically rotated hand cursor feedback during reaching movements (VMR). We quantified how much participants adapted to the disturbance and how many trials they took to adapt to the same levels as controls. Spearman's rho was used to examine the relationship between proprioception, assessed using robotics and the TLT, and visuomotor adaptation. Data from healthy adults were used to identify participants with stroke who were impaired in proprioception and visuomotor adaptation. The independence of impairments in proprioception and adaptation were examined using Fisher's exact tests.

RESULTS

Impairments in proprioception (58.3%) and adaptation (52.1%) were common in participants with stroke (n = 48; 2.10% acute, 70.8% subacute, 27.1% chronic stroke). Performance on the APM task, AMM task, and TLT scores correlated weakly with measures of visuomotor adaptation. Fisher's exact tests demonstrated that impairments in proprioception, assessed using robotics and the TLT, were independent from impairments in visuomotor adaptation in our sample.

CONCLUSION

Our results suggest impairments in proprioception may be independent from impairments in visuomotor adaptation after stroke. Further studies are needed to understand factors that influence the relationship between motor learning, proprioception and other rehabilitation outcomes throughout stroke recovery.

A neuromechanical model characterizing the motor planning and posture control in the voluntary lean in Parkinson's disease

Parkinson's disease targets patients' cognitive and motor abilities, including postural control. Many studies have been carried out to introduce mathematical models for a better understanding of postural control in such patients and the relation between the model parameters and the clinical assessments. So far, these studies have addressed this connection merely in static tests, such as quiet stance. The aim of this study is to develop a model for voluntary lean, and as such, identify the model parameters for both PD patients and healthy subjects from experimental data. The proposed model comprises planning and control sections. The model parameters for the planning section were extracted from the time response characteristics. Parameters for the control section were identified based on the spatial characteristics of the center-of-pressure (COP) response using an optimization process. 24 PD patients along with 24 matched healthy subjects participated in the study. The results showed a significant difference between the two groups in terms of temporal parameters for the planning section. This difference emphasizes bradykinesia as an essential symptom of PD. Also, differences were found for the postural control section. In all directions, the proportional gain of the feedback controller was significantly larger in PD patients; however, the gain of the feedforward controller was significantly smaller in PD patients. Furthermore, the control gains were strongly correlated with the clinical scales (Functional Reach Test and Unified Parkinson's Disease Rating Scale) in certain directions. In conclusion, the new model helps to better understand and quantify some PD symptoms in voluntary lean tasks.

Human reaching control in dynamic environments

Closed-loop models of movement control have attracted growing interest in how the nervous system transforms sensory information into motor commands, and several brain structures have been identified as neural substrates for these computational operations. Recently, several studies have focused on how these models need to be updated when environmental parameters change. Current evidence suggests that when the task changes, rapid control updates enable flexible modifications of current actions and online decisions. At the same time, when movement dynamics change, humans use different strategies based on a combination of adaptation and modulation of controller sensitivity to exogenous perturbations (robust control). This review proposes a unified framework to capture these results based on online estimation of model parameters with dynamic updates in control. The reviewed studies also identify the time scales of associated behavioral mechanisms to guide future research on the neural basis of movement control.

Interchangeable Role of Motor Cortex and Reafference for the Stable Execution of an Orofacial Action

Animals interact with their environment through mechanically active, mobile sensors. The efficient use of these sensory organs implies the ability to track their position; otherwise, perceptual stability or prehension would be profoundly impeded. The nervous system may keep track of the position of a sensorimotor organ via two complementary feedback mechanisms-peripheral reafference (external, sensory feedback) and efference copy (internal feedback). Yet, the potential contributions of these mechanisms remain largely unexplored. By training male rats to place one of their vibrissae within a predetermined angular range without contact, a task that depends on knowledge of vibrissa position relative to their face, we found that peripheral reafference is not required. The presence of motor cortex is not required either, except in the absence of peripheral reafference to maintain motor stability. Finally, the red nucleus, which receives descending inputs from motor cortex and cerebellum and projects to facial motoneurons, is critically involved in the execution of the vibrissa positioning task. All told, our results point toward the existence of an internal model that requires either peripheral reafference or motor cortex to optimally drive voluntary motion.SIGNIFICANCE STATEMENT How does an animal know where a mechanically active, mobile sensor lies relative to its body? We address this basic question in sensorimotor integration using the motion of the vibrissae in rats. We show that rats can learn to reliably position their vibrissae in the absence of sensory feedback or in the absence of motor cortex. Yet, when both sensory feedback and motor cortex are absent, motor precision is degraded. This suggests the existence of an internal model able to operate in closed- and open-loop modes, requiring either motor cortex or sensory feedback to maintain motor stability.

The nervous system tunes sensorimotor gains when reaching in variable mechanical environments

Humans often move in the presence of mechanical disturbances that can vary in direction and amplitude throughout movement. These disturbances can jeopardize the outcomes of our actions, such as when drinking from a glass of water on a turbulent flight or carrying a cup of coffee while walking on a busy sidewalk. Here, we examine control strategies that allow the nervous system to maintain performance when reaching in the presence of mechanical disturbances that vary randomly throughout movement. Healthy participants altered their control strategies to make movements more robust against disturbances. The change in control was associated with faster reaching movements and increased responses to proprioceptive and visual feedback that were tuned to the variability of the disturbances. Our findings highlight that the nervous system exploits a continuum of control strategies to increase its responsiveness to sensory feedback when reaching in the presence of increasingly variable physical disturbances.

The sensorimotor system modulates muscular co-contraction relative to visuomotor feedback responses to regulate movement variability

The naturally occurring variability in our movements often poses a significant challenge when attempting to produce precise and accurate actions, which is readily evident when playing a game of darts. Two differing, yet potentially complementary, control strategies that the sensorimotor system may use to regulate movement variability are impedance control and feedback control. Greater muscular co-contraction leads to greater impedance that acts to stabilize the hand, while visuomotor feedback responses can be used to rapidly correct for unexpected deviations when reaching toward a target. Here, we examined the independent roles and potential interplay of impedance control and visuomotor feedback control when regulating movement variability. Participants were instructed to perform a precise reaching task by moving a cursor through a narrow visual channel. We manipulated cursor feedback by visually amplifying movement variability and/or delaying the visual feedback of the cursor. We found that participants decreased movement variability by increasing muscular co-contraction, aligned with an impedance control strategy. Participants displayed visuomotor feedback responses during the task but, unexpectedly, there was no modulation between conditions. However, we did find a relationship between muscular co-contraction and visuomotor feedback responses, suggesting that participants modulated impedance control relative to feedback control. Taken together, our results highlight that the sensorimotor system modulates muscular co-contraction, relative to visuomotor feedback responses, to regulate movement variability and produce accurate actions.NEW & NOTEWORTHY The sensorimotor system has the constant challenge of dealing with the naturally occurring variability in our movements. Here, we investigated the potential roles of muscular co-contraction and visuomotor feedback responses to regulate movement variability. When we visually amplified movements, we found that the sensorimotor system primarily uses muscular co-contraction to regulate movement variability. Interestingly, we found that muscular co-contraction was modulated relative to inherent visuomotor feedback responses, suggesting an interplay between impedance and feedback control.

Proprioceptive and Visual Feedback Responses in Macaques Exploit Goal Redundancy

A common problem in motor control concerns how to generate patterns of muscle activity when there are redundant solutions to attain a behavioral goal. Optimal feedback control is a theory that has guided many behavioral studies exploring how the motor system incorporates task redundancy. This theory predicts that kinematic errors that deviate the limb should not be corrected if one can still attain the behavioral goal. Studies in humans demonstrate that the motor system can flexibly integrate visual and proprioceptive feedback of the limb with goal redundancy within 90 ms and 70 ms, respectively. Here, we show monkeys (Macaca mulatta) demonstrate similar abilities to exploit goal redundancy. We trained four male monkeys to reach for a goal that was either a narrow square or a wide, spatially redundant rectangle. Monkeys exhibited greater trial-by-trial variability when reaching to the wide goal consistent with exploiting goal redundancy. On random trials we jumped the visual feedback of the hand and found monkeys corrected for the jump when reaching to the narrow goal and largely ignored the jump when reaching for the wide goal. In a separate set of experiments, we applied mechanical loads to the arm of the monkey and found similar corrective responses based on goal shape. Muscle activity reflecting these different corrective responses were detected for the visual and mechanical perturbations starting at ∼90 and ∼70 ms, respectively. Thus, rapid motor responses in macaques can exploit goal redundancy similar to humans, creating a paradigm to study the neural basis of goal-directed motor action and motor redundancy.SIGNIFICANCE STATEMENT Moving in the world requires selecting from an infinite set of possible motor commands. Theories predict that motor commands are selected that exploit redundancies. Corrective responses in humans to either visual or proprioceptive disturbances of the limb can rapidly exploit redundant trajectories to a goal in <100 ms after a disturbance. However, uncovering the neural correlates generating these rapid motor corrections has been hampered by the absence of an animal model. We developed a behavioral paradigm in monkeys that incorporates redundancy in the form of the shape of the goal. Critically, monkeys exhibit corrective responses and timings similar to humans performing the same task. Our paradigm provides a model for investigating the neural correlates of sophisticated rapid motor corrections.

Sensorimotor feedback loops are selectively sensitive to reward

Although it is well established that motivational factors such as earning more money for performing well improve motor performance, how the motor system implements this improvement remains unclear. For instance, feedback-based control, which uses sensory feedback from the body to correct for errors in movement, improves with greater reward. But feedback control encompasses many feedback loops with diverse characteristics such as the brain regions involved and their response time. Which specific loops drive these performance improvements with reward is unknown, even though their diversity makes it unlikely that they are contributing uniformly. We systematically tested the effect of reward on the latency (how long for a corrective response to arise?) and gain (how large is the corrective response?) of seven distinct sensorimotor feedback loops in humans. Only the fastest feedback loops were insensitive to reward, and the earliest reward-driven changes were consistently an increase in feedback gains, not a reduction in latency. Rather, a reduction of response latencies only tended to occur in slower feedback loops. These observations were similar across sensory modalities (vision and proprioception). Our results may have implications regarding feedback control performance in athletic coaching. For instance, coaching methodologies that rely on reinforcement or 'reward shaping' may need to specifically target aspects of movement that rely on reward-sensitive feedback responses.

Multifractal Nonlinearity Moderates Feedforward and Feedback Responses to Suprapostural Perturbations

An adaptive response to unexpected perturbations requires near-term and long-term adjustments over time. We used multifractal analysis to test how nonlinear interactions across timescales might support an adaptive response following an unpredictable perturbation. We reanalyzed torque data from 44 young and 24 older adults who performed a single-leg squat task challenged by an unexpected mechanical perturbation and a secondary visual-cognitive task. We report three findings: (a) multifractal nonlinearity interacted with pre-perturbation torque production and task error to presage greater pre-voluntary feedforward increases and greater voluntary reductions, respectively, in post-perturbation task error; (b) multifractal nonlinearity presaged relatively smaller task error than standard deviations of both pre-perturbation torques and pre-perturbation task error; and (c) increased task demand (e.g., age-related changes in dexterity and dual-task settings) led to multifractal nonlinearity presaging reduced task error. All these results were consistent with our expectations, except that a pre-perturbation knee torque-dependent increase in post-perturbation task error appeared later for older than for younger participants. This correlational multifractal modeling offered theoretical clarity on the possible roles of nonlinear interactions across timescales, moderating both feedforward and feedback processes, and presaging greater stability when the standard deviation is relatively large and task demands are strong. Thus, multifractal nonlinearity usefully describes movement variability even when paired with classical descriptors like the standard deviation. We discuss potential insights from these findings for understanding suprapostural dexterity and developing rehabilitative interventions.

Accuracy and effort costs together lead to temporal asynchrony of multiple motor commands

The timing of motor commands is critical for task performance. A well-known example is rapidly raising the arm while standing upright. Here, reaction forces from the arm movement to the body are countered by leg and trunk muscle activity starting before any sensory feedback from the perturbation and often before the onset of arm muscle activity. Despite decades of research on the patterns, modifiability, and neural basis of these "anticipatory postural adjustments," it remains unclear why asynchronous motor commands occur. Simple accuracy considerations appear unlikely since temporally advanced motor commands displace the body from its initial position. Effort is a credible and overlooked factor that has successfully explained coordination patterns of many behaviors including gait and reaching. We provide the first use of optimal control to address this question. Feedforward commands were applied to a body mass mechanically linked to a rapidly moving limb mass. We determined the feedforward actions with the lowest cost according to an explicit criterion, accuracy alone versus accuracy + effort. Accuracy costs alone led to synchronous activation of the body and limb controllers. Adding effort to the cost resulted in body commands preceding limb commands. This sequence takes advantage of the body's momentum in one direction to counter the limb's reaction force in the opposite direction, allowing a lower peak command and lower integral. With a combined accuracy + effort cost, temporal advancement was further impacted by various task goals and plant dynamics, replicating previous findings and suggesting further studies using optimal control principles.NEW & NOTEWORTHY An important goal in the fields of sensorimotor neuroscience and biomechanics is to explain the timing of different muscles during behavior. Here, we propose that energy and accuracy considerations underlie the asynchronous onset of postural and arm muscles during rapid movement. Our novel model-based framework replicates a broad range of observations across varying task demands and plant dynamics and offers a new perspective to study motor timing.

Asymmetrical transfer of adaptation between reaching and tracking: implications for feedforward and feedback processes

Reaching and manual tracking are two very common tasks for studying human sensorimotor processes. Although these motor tasks rely both on feedforward and feedback processes, emphasis is more on feedforward processes for reaching, and more on feedback processes for tracking. The extent to which feedforward and feedback processes are interrelated when being updated is not settled yet. Here, using reaching and tracking as proxies, we examined the bidirectional relationship between the update of feedforward and feedback processes. Forty right-handed participants were asked to move a joystick so as to either track a target moving rather unpredictably (pursuit tracking) or to make fast pointing movements toward a static target (center-out reaching task). Visuomotor adaptation was elicited by introducing a 45° rotation between the joystick motion and the cursor motion. Half of the participants adapted to rotation first via reaching movements, and then with pursuit tracking, while the other half performed both tasks in opposite order. Group comparisons revealed a strong asymmetrical transfer of adaptation between tasks. Namely, although nearly complete transfer of adaptation was observed from reaching to tracking, only modest transfer was found from tracking to reaching. A control experiment (N=10) revealed that making target motion fully predictable did not impact the latter finding. One possible interpretation is that the update of feedforward processes contributes directly to feedback processes, but the update of feedback processes engaged in tracking can be performed in isolation. These results suggest that reaching movements are supported by broader (i.e. more universal) mechanisms than tracking ones.

Contextual cues are not unique for motor learning: Task-dependant switching of feedback controllers

The separation of distinct motor memories by contextual cues is a well known and well studied phenomenon of feedforward human motor control. However, there is no clear evidence of such context-induced separation in feedback control. Here we test both experimentally and computationally if context-dependent switching of feedback controllers is possible in the human motor system. Specifically, we probe visuomotor feedback responses of our human participants in two different tasks—stop and hit—and under two different schedules. The first, blocked schedule, is used to measure the behaviour of stop and hit controllers in isolation, showing that it can only be described by two independent controllers with two different sets of control gains. The second, mixed schedule, is then used to compare how such behaviour evolves when participants regularly switch from one task to the other. Our results support our hypothesis that there is contextual switching of feedback controllers, further extending the accumulating evidence of shared features between feedforward and feedback control.

Extensive evidence has demonstrated that humans can learn distinct motor memories (i.e. independent feedforward controllers) using contextual cues. However, there is little evidence that such contextual cues produce similar separation of feedback controllers. As accumulating evidence highlights the connection between feedforward and feedback control, we propose that context may be used to separate feedback controllers as well. It has not been trivial to test experimentally whether a change in context also modulates the feedback control, as the controller output is affected by other non-contextual factors such as movement kinematics, time-to-target or the properties of the perturbation used to probe the control. Here we present a computational approach based on normative modelling where we separate the effects of the context from other non-contextual effects on the visuomotor feedback system. We then show experimentally that task context independently modulates the feedback control in a particular manner that can be reliably predicted using optimal feedback control.

Task space exploration improves adaptation after incompatible virtual surgeries

Humans have a remarkable capacity to learn new motor skills, a process that requires novel muscle activity patterns. Muscle synergies may simplify the generation of muscle patterns through the selection of a small number of synergy combinations. Learning new motor skills may then be achieved by acquiring novel muscle synergies. In a previous study, we used myoelectric control to construct virtual surgeries that altered the mapping from muscle activity to cursor movements. After compatible virtual surgeries, which could be compensated by recombining subject-specific muscle synergies, participants adapted quickly. In contrast, after incompatible virtual surgeries, which could not be compensated by recombining existing synergies, participants explored new muscle patterns, but failed to adapt. Here, we tested whether task space exploration can promote learning of novel muscle synergies, required to overcome an incompatible surgery. Participants performed the same reaching task as in our previous study, but with more time to complete each trial, thus allowing for exploration. We found an improvement in trial success after incompatible virtual surgeries. Remarkably, improvements in movement direction accuracy after incompatible surgeries occurred faster for corrective movements than for the initial movement, suggesting that learning of new synergies is more effective when used for feedback control. Moreover, reaction time was significantly higher after incompatible than after compatible virtual surgeries, suggesting an increased use of an explicit adaptive strategy to overcome incompatible surgeries. Taken together, these results indicate that exploration is important for skill learning and suggest that human participants, with sufficient time, can learn new muscle synergies.

Involvement of the Rostromedial Prefrontal Cortex in Human-Robot Interaction: fNIRS Evidence From a Robot-Assisted Motor Task

Assistive exoskeleton robots are being widely applied in neurorehabilitation to improve upper-limb motor and somatosensory functions. During robot-assisted exercises, the central nervous system appears to highly attend to external information-processing (IP) to efficiently interact with robotic assistance. However, the neural mechanisms underlying this process remain unclear. The rostromedial prefrontal cortex (rmPFC) may be the core of the executive resource allocation that generates biases in the allocation of processing resources toward an external IP according to current behavioral demands. Here, we used functional near-infrared spectroscopy to investigate the cortical activation associated with executive resource allocation during a robot-assisted motor task. During data acquisition, participants performed a right-arm motor task using elbow flexion-extension movements in three different loading conditions: robotic assistive loading (ROB), resistive loading (RES), and non-loading (NON). Participants were asked to strive for kinematic consistency in their movements. A one-way repeated measures analysis of variance and general linear model-based methods were employed to examine task-related activity. We demonstrated that hemodynamic responses in the ventral and dorsal rmPFC were higher during ROB than during NON. Moreover, greater hemodynamic responses in the ventral rmPFC were observed during ROB than during RES. Increased activation in ventral and dorsal rmPFC subregions may be involved in the executive resource allocation that prioritizes external IP during human-robot interactions. In conclusion, these findings provide novel insights regarding the involvement of executive control during a robot-assisted motor task.

Alpha-band activity in parietofrontal cortex predicts future availability of vibrotactile feedback in prosthesis use

Prosthesis disuse and abandonment is an ongoing issue in upper-limb amputation. In addition to lost structural and motor function, amputation also results in decreased task-specific sensory information. One proposed remedy is augmenting somatosensory information using vibrotactile feedback to provide tactile feedback of grasping objects. While the role of frontal and parietal areas in motor tasks is well established, the neural and kinematic effects of this augmented vibrotactile feedback remain in question. In this study, we sought to understand the neurobehavioral effects of providing augmented feedback during a reach-grasp-transport task. Ten persons with sound limbs performed a motor task while wearing a prosthesis simulator with and without vibrotactile feedback. We hypothesized that providing vibrotactile feedback during prosthesis use would increase activity in frontal and parietal areas and improve grasp-related behavior. Results show that anticipation of upcoming vibrotactile feedback may be encoded in motor and parietal areas during the reach-to-grasp phase of the task. While grasp aperture is unaffected by vibrotactile feedback, the availability of vibrotactile feedback does lead to a reduction in velocity during object transport. These results help shed light on how engineered feedback is utilized by prostheses users and provide methodologies for further assessment in advanced prosthetics research.

Adaptive Feedback Control in Human Reaching Adaptation to Force Fields

Sensorimotor adaptation is a central function of the nervous system, as it allows humans and other animals to flexibly anticipate their interaction with the environment. In the context of human reaching adaptation to force fields, studies have traditionally separated feedforward (FF) and feedback (FB) processes involved in the improvement of behavior. Here, we review computational models of FF adaptation to force fields and discuss them in light of recent evidence highlighting a clear involvement of feedback control. Instead of a model in which FF and FB mechanisms adapt in parallel, we discuss how online adaptation in the feedback control system can explain both trial-by-trial adaptation and improvements in online motor corrections. Importantly, this computational model combines sensorimotor control and short-term adaptation in a single framework, offering novel perspectives for our understanding of human reaching adaptation and control.

Interoception as modeling, allostasis as control

The brain regulates the body by anticipating its needs and attempting to meet them before they arise - a process called allostasis. Allostasis requires a model of the changing sensory conditions within the body, a process called interoception. In this paper, we examine how interoception may provide performance feedback for allostasis. We suggest studying allostasis in terms of control theory, reviewing control theory's applications to related issues in physiology, motor control, and decision making. We synthesize these by relating them to the important properties of allostatic regulation as a control problem. We then sketch a novel formalism for how the brain might perform allostatic control of the viscera by analogy to skeletomotor control, including a mathematical view on how interoception acts as performance feedback for allostasis. Finally, we suggest ways to test implications of our hypotheses.

In vivo effects of two shoulder girdle motor control exercises on acromiohumeral and coracohumeral distances in healthy men

INTRODUCTION

Altered motor control and proprioceptive deficits are associated with kinematics dysfunctions and may cause alterations in subacromial space (SAS) that could lead to shoulder pathologies. Dimensions of the subacromial space, as well as interventions aimed at its normal restitution, can be explored by ultrasound (US).

OBJECTIVE

To describe the effect of two shoulder girdle motor control exercises with cognitive training strategies on SAS dimensions, measured with US.

METHODS

Cognitive movement control strategies, with visual and haptic feedback were applied on 21 healthy participants. SAS dimensions were measured through in vivo variations of acromiohumeral (AHD) and coracohumeral distances (CHD) using US.

RESULTS

Our results show that as exercise repetitions are performed, an increasing trend in both measures can be observed, being wider for AHD (i.e. humeral head descent exercise) than CHD (i.e. scapular retraction exercise).

CONCLUSION

Specific cognitive and motor control exercises improve congruence joint and centering of the humeral head.

Savings in Human Force Field Learning Supported by Feedback Adaptation

Savings have been described as the ability of healthy humans to relearn a previously acquired motor skill faster than the first time, which in the context of motor adaptation suggests that the learning rate in the brain could be adjusted when a perturbation is recognized. Alternatively, it has been argued that apparent savings were the consequence of a distinct process that instead of reflecting a change in the learning rate, revealed an explicit re-aiming strategy. Based on recent evidence that feedback adaptation may be central to both planning and control, we hypothesized that this component could genuinely accelerate relearning in human adaptation to force fields (FFs) during reaching. Consistent with our hypothesis, we observed that on re-exposure to a previously learned FF, the very first movement performed by healthy volunteers in the relearning context was better adapted to the external disturbance, and this occurred without any anticipation or cognitive strategy because the relearning session was started unexpectedly. We conclude that feedback adaptation is a medium by which the nervous system can genuinely accelerate learning across movements.

Neurons in Primary Motor Cortex Encode External Perturbations during an Orientation Reaching Task

When confronting an abrupt external perturbation force during movement, subjects continuously adjust their behaviors to adapt to changes. Such adaptation is of great importance for realizing flexible motor control in varied environments, but the potential cortical neuronal mechanisms behind it have not yet been elucidated. Aiming to reveal potential neural control system compensation for external disturbances, we applied an external orientation perturbation while monkeys performed an orientation reaching task and simultaneously recorded the neural activity in the primary motor cortex (M1). We found that a subpopulation of neurons in the primary motor cortex specially created a time-locked activity in response to a “go” signal in the adaptation phase of the impending orientation perturbation and did not react to a “go” signal under the normal task condition without perturbation. Such neuronal activity was amplified as the alteration was processed and retained in the extinction phase; then, the activity gradually faded out. The increases in activity during the adaptation to the orientation perturbation may prepare the system for the impending response. Our work provides important evidence for understanding how the motor cortex responds to external perturbations and should advance research about the neurophysiological mechanisms underlying motor learning and adaptation.

Similar stretch reflexes and behavioral patterns are expressed by the dominant and nondominant arms during postural control

Limb dominance is evident in many daily activities, leading to the prominent idea that each hemisphere of the brain specializes in controlling different aspects of movement. Past studies suggest that the dominant arm is primarily controlled via an internal model of limb dynamics that enables the nervous system to produce efficient movements. In contrast, the nondominant arm may be primarily controlled via impedance mechanisms that rely on the strong modulation of sensory feedback from individual joints to control limb posture. We tested whether such differences are evident in behavioral responses and stretch reflexes following sudden displacement of the arm during posture control. Experiment 1 applied specific combinations of elbow-shoulder torque perturbations (the same for all participants). Peak joint displacements, return times, end point accuracy, and the directional tuning and amplitude of stretch reflexes in nearly all muscles were not statistically different between the two arms. Experiment 2 induced specific combinations of joint motion (the same for all participants). Again, peak joint displacements, return times, end point accuracy, and the directional tuning and amplitude of stretch reflexes in nearly all muscles did not differ statistically when countering the imposed loads with each arm. Moderate to strong correlations were found between stretch reflexes and behavioral responses to the perturbations with the two arms across both experiments. Collectively, the results do not support the idea that the dominant arm specializes in exploiting internal models and the nondominant arm in impedance control by increasing reflex gains to counter sudden loads imposed on the arms during posture control.NEW & NOTEWORTHY A prominent hypothesis is that the nervous system controls the dominant arm through predictive internal models and the nondominant arm through impedance mechanisms. We tested whether stretch reflexes of muscles in the two arms also display such specialization during posture control. Nearly all behavioral responses and stretch reflexes did not differ statistically but were strongly correlated between the arms. The results indicate individual signatures of feedback control that are common for the two arms.

Rapid Feedback Responses Parallel the Urgency of Voluntary Reaching Movements

Optimal feedback control is a prominent theory used to interpret human motor behaviour. The theory posits that skilled actions emerge from control policies that link voluntary motor control (feedforward) with flexible feedback corrections (feedback control). It is clear the nervous system can generate flexible motor corrections (reflexes) when performing actions with different goals. We know little, however, about shared features of voluntary actions and feedback control in human movement. Here we reveal a link between the timing demands of voluntary actions and flexible responses to mechanical perturbations. In two experiments, 40 human participants (21 females) made reaching movements with different timing demands. We disturbed the arm with mechanical perturbations at movement onset (Experiment 1) and at locations ranging from movement onset to completion (Experiment 2). We used the resulting muscle responses and limb displacements as a proxy for the control policies that support voluntary reaching movements. We observed an increase in the sensitivity of elbow and shoulder muscle responses and a reduction in limb motion when the task imposed greater urgency to respond to the same perturbations. The results reveal a relationship between voluntary actions and feedback control as the limb was displaced less when moving faster in perturbation trials. Muscle responses scaled with changes in the displacement of the limb in perturbation trials within each timing condition. Across both experiments, human behaviour was captured by simulations based on stochastic optimal feedback control. Taken together, the results highlight flexible control that links sensory processing with features of human reaching movements.

Scaling of Joint Motion and Muscle Activation for 3-Dimensional Control of Reach Extent

This study investigated the scaling of upper arm kinematics, joint motion, and muscle activation for three-dimensional (3D) reaches to targets of increasing distance. Fifteen participants completed 108 total reaches to targets placed 7, 14, and 21 cm across midline. Peak velocity, acceleration, and time to peak velocity scaled to both target and movement distance. Shoulder and elbow excursion scaled to target distance and were highly coordinated. Anterior deltoid activation scaled to both target and movement distance in the early and late phases of reach control. Biceps and triceps activation scaled to movement distance primarily in the late phase. Scaling of these outcome variables provides a model for understanding the control of reach distance in a 3D environment.

Online sensorimotor learning and adaptation for inverse dynamics control

We propose a micro-data (< 10 trials) sensorimotor learning and adaptation (SEED) model for human-like arm inverse dynamics control. The SEED model consists of a feedforward Gaussian motor primitive (GATE) neural network and an adaptive feedback impedance (AIM) mechanism. Sensorimotor weights over trials are learned in the GATE network, while the AIM mechanism is used to online tune impedance gains in a trial. The model was validated by periodic and non-periodic tracking tasks on a two-joint robot arm. As a result, the proposed model enables the arm to stably learn the tasks within 10 trials, compared to thousands of trials required by state-of-art deep learning. This model facilitates the exploration of unknown arm dynamics, in which the elbow joint requires much less active control compared to the shoulder. This control goes below 3% of the overall effort. This finding complies with a proximal-distal control gradient in human arm control. Taken together, the proposed SEED model paves a way for implementing data-efficient sensorimotor learning and adaptation of human-like arm movement.

Same action in different spatial locations induces selective modulation of body metric representation

Recent studies have hypothesized that the stereotypical representation of the body may reflect some functional aspects of routine actions that are performed in specific peripersonal domains. For example, the lower and upper limbs tend to 'act' in different peripersonal spaces and perform different functions. The present study aims to directly investigate the relationship between body representation and the spatial context where actions are performed. By means of a modified version of the body image task, we investigated body representation before and after a sorting task training in two groups of participants who were asked to carry out the same task/actions in two different spaces: on a table or on the floor, while sitting on a chair. Findings showed that a significant recalibration of the perceived upper arms' length occurred when participants were asked to perform a motor task on the floor. These results seem to suggest that the modulation of the body representation reflects an increase action capabilities driven by the contribution of motor training, and importantly, the location in which the action occurs. Furthermore, the modulation was not limited to the body part actively involved in the action (the arms), it extended to other upper body parts (the torso) to maintain, we propose, a functionally coherent representation of the upper body.

Hierarchical motor adaptations negotiate failures during force field learning

Humans have the amazing ability to learn the dynamics of the body and environment to develop motor skills. Traditional motor studies using arm reaching paradigms have viewed this ability as the process of ‘internal model adaptation’. However, the behaviors have not been fully explored in the case when reaches fail to attain the intended target. Here we examined human reaching under two force fields types; one that induces failures (i.e., target errors), and the other that does not. Our results show the presence of a distinct failure-driven adaptation process that enables quick task success after failures, and before completion of internal model adaptation, but that can result in persistent changes to the undisturbed trajectory. These behaviors can be explained by considering a hierarchical interaction between internal model adaptation and the failure-driven adaptation of reach direction. Our findings suggest that movement failure is negotiated using hierarchical motor adaptations by humans.

How do we improve actions after a movement failure? Although negotiating movement failures is obviously crucial, previous motor-control studies have predominantly examined human movement adaptations in the absence of failures, and it remains unclear how failures affect subsequent movement adaptations. Here we examined this issue by developing a novel force field adaptation task where the hand movement during an arm reaching is perturbed by novel forces that induce a large target error, that is a failure. Our experimental observation and computational modeling show that, in addition to the popular ‘internal model learning’ process of motor adaptations, humans also utilize a ‘failure-negotiating’ process, that enables them to quickly improve movements in the presence of failure, even at the expense of increased arm trajectory deflections, which are subsequently reduced gradually with training after the achievement of the task success. Our results suggest that a hierarchical interaction between these two processes is a key for humans to negotiate movement failures.

Information Rate in Humans during Visuomotor Tracking

Previous investigations concluded that the human brain’s information processing rate remains fundamentally constant, irrespective of task demands. However, their conclusion rested in analyses of simple discrete-choice tasks. The present contribution recasts the question of human information rate within the context of visuomotor tasks, which provides a more ecologically relevant arena, albeit a more complex one. We argue that, while predictable aspects of inputs can be encoded virtually free of charge, real-time information transfer should be identified with the processing of surprises. We formalise this intuition by deriving from first principles a decomposition of the total information shared by inputs and outputs into a feedforward, predictive component and a feedback, error-correcting component. We find that the information measured by the feedback component, a proxy for the brain’s information processing rate, scales with the difficulty of the task at hand, in agreement with cost-benefit models of cognitive effort.

Using asymmetry to your advantage: learning to acquire and accept external assistance during prolonged split-belt walking

People can learn to exploit external assistance during walking to reduce energetic cost. For example, walking on a split-belt treadmill affords the opportunity for people to redistribute the mechanical work performed by the legs to gain assistance from the difference in belts' speed and reduce energetic cost. Though we know what people should do to acquire this assistance, this strategy is not observed during typical adaptation studies. We hypothesized that extending the time allotted for adaptation would result in participants adopting asymmetric step lengths to increase the assistance they can acquire from the treadmill. Here, participants walked on a split-belt treadmill for 45 min while we measured spatiotemporal gait variables, metabolic cost, and mechanical work. We show that when people are given sufficient time to adapt, they naturally learn to step further forward on the fast belt, acquire positive mechanical work from the treadmill, and reduce the positive work performed by the legs. We also show that spatiotemporal adaptation and energy optimization operate over different timescales: people continue to reduce energetic cost even after spatiotemporal changes have plateaued. Our findings support the idea that walking with symmetric step lengths, which is traditionally thought of as the endpoint of adaptation, is only a point in the process by which people learn to take advantage of the assistance provided by the treadmill. These results provide further evidence that reducing energetic cost is central in shaping adaptive locomotion, but this process occurs over more extended timescales than those used in typical studies.NEW & NOTEWORTHY Split-belt treadmill adaptation can be seen as a process where people learn to acquire positive work from the treadmill to reduce energetic cost. Though we know what people should do to reduce energetic cost, this strategy is not observed during adaptation studies. We extended the duration of adaptation and show that people continuously adapt their gait to acquire positive work from the treadmill to reduce energetic cost. This process requires longer exposure than traditionally allotted.

Somatosensory deafferentation reveals lateralized roles of proprioception in feedback and adaptive feedforward control of movement and posture

Proprioception provides crucial information necessary for determining limb position and movement, and plausibly also for updating internal models that might underlie the control of movement and posture. Seminal studies of upper-limb movements in individuals living with chronic, large fiber deafferentation have provided evidence for the role of proprioceptive information in the hypothetical formation and maintenance of internal models to produce accurate motor commands. Vision also contributes to sensorimotor functions but cannot fully compensate for proprioceptive deficits. More recent work has shown that posture and movement control processes are lateralized in the brain, and that proprioception plays a fundamental role in coordinating the contributions of these processes to the control of goal-directed actions. In fact, the behavior of each limb in a deafferented individual resembles the action of a controller in isolation. Proprioception, thus, provides state estimates necessary for the nervous system to efficiently coordinate multiple motor control processes.

Rapid Changes in Movement Representations during Human Reaching Could Be Preserved in Memory for at Least 850 ms

Humans adapt to mechanical perturbations such as forcefields (FFs) during reaching within tens of trials. However, recent findings suggested that this adaptation may start within one single trial, i.e., online corrective movements can become tuned to the unanticipated perturbations within a trial. This was highlighted in previous works with a reaching experiment in which participants had to stop at a via-point (VP) located between the start and the goal. An FF was applied during the first and second parts of the movement and then occasionally unexpectedly switched off at the VP during catch trials. The results showed an after-effect during the second part of the movement when participants exited the VP. This behavioral result was interpreted as a standard after-effect, but it remained unclear how it was related to conventional trial-by-trial learning. The current study aimed to investigate how long do such changes in movement representations last in memory. For this, we have studied the same reaching task with VP in two situations: one with very short residing time in the VP and the second with an imposed minimum 500 ms dwell time in the VP. In both situations, during the unexpected absence of the FF after VP, after-effects were observed. This suggests that online corrections to the internal representation of reach dynamics can be preserved in memory for around 850 ms of resting time on average. Therefore, rapid changes occurring within movements can thus be preserved in memory long enough to influence trial-by-trial motor adaptation.

Shared internal models for feedforward and feedback control of arm dynamics in non-human primates

Previous work has shown that humans account for and learn novel properties or the arm's dynamics, and that such learning causes changes in both the predictive (i.e., feedforward) control of reaching and reflex (i.e., feedback) responses to mechanical perturbations. Here we show that similar observations hold in old-world monkeys (Macaca fascicularis). Two monkeys were trained to use an exoskeleton to perform a single-joint elbow reaching and to respond to mechanical perturbations that created pure elbow motion. Both of these tasks engaged robust shoulder muscle activity as required to account for the torques that typically arise at the shoulder when the forearm rotates around the elbow joint (i.e., intersegmental dynamics). We altered these intersegmental arm dynamics by having the monkeys generate the same elbow movements with the shoulder joint either free to rotate, as normal, or fixed by the robotic manipulandum, which eliminates the shoulder torques caused by forearm rotation. After fixing the shoulder joint, we found a systematic reduction in shoulder muscle activity. In addition, after releasing the shoulder joint again, we found evidence of kinematic aftereffects (i.e., reach errors) in the direction predicted if failing to compensate for normal arm dynamics. We also tested whether such learning transfers to feedback responses evoked by mechanical perturbations and found a reduction in shoulder feedback responses, as appropriate for these altered arm intersegmental dynamics. Demonstrating this learning and transfer in non-human primates will allow the investigation of the neural mechanisms involved in feedforward and feedback control of the arm's dynamics.

Online corrective responses following target jump in altered gravitoinertial force field point to nested feedforward and feedback control

Studies on goal-directed arm movements have shown a close link between feedforward and feedback control in protocols where both planning and online control processes faced a similar type of perturbation, either mechanical or visual. This particular context might have facilitated the use of an adapted internal model by feedforward and feedback control. Here, we considered this link in a context where, after feedforward control was adapted through proprioception-based processes, feedback control was tested under visual perturbation. We analyzed the response of the reaching hand to target displacements following adaptation to an altered force field induced by rotating participants at constant velocity. Reaching corrections were assessed through variables related to the accuracy (lateral and longitudinal end point errors) and kinematics (movement time, peak velocity) of the corrective movements. The electromyographic activity of different arm muscles (pectoralis, posterior deltoid, biceps brachii, and triceps brachii) was analyzed. Statistical analyses revealed that accuracy and kinematics of corrective movements were strikingly alike between normal and altered gravitoinertial force fields. However, pectoralis and biceps muscle activities recorded during corrective movements were significantly modified to counteract the effect of rotation-induced Coriolis and centrifugal forces on the arm. Remarkably, feedback control was functional from the very first time participants encountered a target jump in the altered force field. Overall, the present results demonstrate that feedforward control enables immediate functional feedback control even when applied to distinct sensorimotor processes.NEW & NOTEWORTHY We investigated the link between feedforward and feedback control when applying a double-step perturbation (visual target jump) during reaching movements performed in modified gravitoinertial environments. Altogether, kinematics and EMG analyses showed that movement corrections were highly effective in the different force fields, suggesting that, although feedforward and feedback control were driven by different sensory inputs, feedback control was remarkably functional from the very first time participants encountered a target jump in the altered force field.

Optimal Control Perspective on Parkinson's Disease: Increased Delay Between State Estimator and Controller Produces Tremor

Parkinson's disease produces tremor in a large subset of patients despite generally inhibiting movement. The pathophysiology of parkinsonian tremor is unclear, leading to uncertainty in how and why treatments reduce tremor with varying effectiveness. Models for parkinsonian tremor attempt to explain the underlying principles of tremor generation in the central nervous system, often focusing on neural activity of specific substructures. In contrast, control system approaches to modeling the human motor system provide qualitative results that help inform conclusions from clinical studies. This article uses an optimal control approach to investigate the hypothesis that an increased delay in the central nervous system-unaccounted by delay compensation mechanisms-produces parkinsonian tremor. This hypothesis is motivated by the excessive inhibition projected from the basal ganglia to the thalamus in Parkinson's disease. The thalamus relays signals from the cerebellum to the primary motor cortex: previous mapping of optimal control components indicates this prospective delay exists between the estimator (cerebellum) and controller (primary motor cortex). Simulations demonstrate realistic tremor in a neuromuscular model of the wrist. In addition, changes to effort sensitivity in the optimal controller may account for some clinical features of parkinsonian tremor, including the characteristics of re-emergent tremor and the time-varying amplitude and frequency of tremor. Contextualization of the optimal control model with physiological models and clinical observations provides insight into the potential role of the basal ganglia and cerebello-thalamo-cortical circuit and how treatments like dopaminergic medications and deep brain stimulation reduce tremor.

Time course of changes in the long-latency feedback response parallels the fast process of short-term motor adaptation

Adapting to novel dynamics involves modifying both feedforward and feedback control. We investigated whether the motor system alters feedback responses during adaptation to a novel force field in a manner similar to adjustments in feedforward control. We simultaneously tracked the time course of both feedforward and feedback systems via independent probes during a force field adaptation task. Participants (n = 35) grasped the handle of a robotic manipulandum and performed reaches to a visual target while the hand and arm were occluded. We introduced an abrupt counterclockwise velocity-dependent force field during a block of reaching trials. We measured movement kinematics and shoulder and elbow muscle activity with surface EMG electrodes. We tracked the feedback stretch response throughout the task. Using force channel trials, we measured overall learning, which was later decomposed into a fast and slow process. We found that the long-latency feedback response (LLFR) was upregulated in the early stages of learning and was correlated with the fast component of feedforward adaptation. The change in feedback response was specific to the long-latency epoch (50-100 ms after muscle stretch) and was observed only in the triceps muscle, which was the muscle required to counter the force field during adaptation. The similarity in time course for the LLFR and the estimated time course of the fast process suggests both are supported by common neural circuits. While some propose that the fast process reflects an explicit strategy, we argue instead that it may be a proxy for the feedback controller.NEW & NOTEWORTHY We investigated whether changes in the feedback stretch response were related to the proposed fast and slow processes of motor adaptation. We found that the long-latency component of the feedback stretch response was upregulated in the early stages of learning and the time course was correlated with the fast process. While some propose that the fast process reflects an explicit strategy, we argue instead that it may be a proxy for the feedback controller.

Feedback Adaptation to Unpredictable Force Fields in 250 ms

Motor learning and adaptation are important functions of the nervous system. Classical studies have characterized how humans adapt to changes in the environment during tasks such as reaching, and have documented improvements in behavior across movements. However, little is known about how quickly the nervous system adapts to such disturbances. In particular, recent work has suggested that adaptation could be sufficiently fast to alter the control strategies of an ongoing movement. To further address the possibility that learning occurred within a single movement, we designed a series of human reaching experiments to extract from muscles recordings the latency of feedback adaptation. Our results confirmed that participants adapted their feedback responses to unanticipated force fields applied randomly. In addition, our analyses revealed that the feedback response was specifically and finely tuned to the ongoing perturbation not only across trials with the same force field, but also across different kinds of force fields. Finally, changes in muscle activity consistent with feedback adaptation occurred in ∼250 ms following reach onset. The adaptation that we observed across trials presented in a random context was similar to the one observed when the force fields could be anticipated, suggesting that these two adaptive processes may be closely linked to each other. In such case, our measurement of 250 ms may correspond to the latency of motor adaptation in the nervous system.

Learning New Feedforward Motor Commands Based on Feedback Responses

Learning a new motor task modifies feedforward (i.e., voluntary) motor commands and such learning also changes the sensitivity of feedback responses (i.e., reflexes) to mechanical perturbations [1-9]. For example, after people learn to generate straight reaching movements in the presence of an external force field or learn to reduce shoulder muscle activity when generating pure elbow movements with shoulder fixation, evoked stretch reflex responses to mechanical perturbations reflect the learning expressed during self-initiated reaching. Such a transfer from feedforward motor commands to feedback responses is thought to take place because of shared neural circuits at the level of the spinal cord, brainstem, and cerebral cortex [10-13]. The presence of shared neural resources also predicts the transfer from feedback responses to feedforward motor commands. Little is known about such a transfer presumably because it is relatively hard to elicit learning in reflexes without engaging associated voluntary responses following mechanical perturbations. Here, we demonstrate such transfer by leveraging two approaches to elicit stretch reflexes while minimizing engagement of voluntary motor responses in the learning process: applying very short mechanical perturbations [14-19] and instructing participants to not respond to them [20-26]. Taken together, our work shows that transfer between feedforward and feedback control is bidirectional, furthering the notion that these processes share common neural circuits that underlie motor learning and transfer.

Open-Source Joystick Manipulandum for Decision-Making, Reaching, and Motor Control Studies in Mice

To make full use of optogenetic and molecular techniques in the study of motor control, rich behavioral paradigms for rodents must rise to the same level of sophistication and applicability. We describe the layout, construction, use and analysis of data from joystick-based reaching in a head-fixed mouse. The step-by-step guide is designed for both experienced rodent motor labs and new groups looking to enter into this research space. Using this platform, mice learn to consistently perform large, easily-quantified reaches, including during a two-armed bandit probabilistic learning task. The metrics of performance (reach trajectory, amplitude, speed, duration, and inter-reach interval) can be used to quantify behavior or administer stimulation in closed loop with behavior. We provide a highly customizable, low cost and reproducible open-source behavior training platform for studying motor control, decision-making, and reaching reaction time. The development of this software and hardware platform enables behavioral work to complement recent advances in rodents, while remaining accessible to smaller institutions and labs, thus providing a high-throughput method to study unexplored features of action selection, motivation, and value-based decisions.

Generalizing movement patterns following shoulder fixation

Generalizing newly learned movement patterns beyond the training context is challenging for most motor learning situations. Here we tested whether learning of a new physical property of the arm during self-initiated reaching generalizes to new arm configurations. Human participants performed a single-joint elbow reaching task and/or countered mechanical perturbations that created pure elbow motion with the shoulder joint free to rotate or locked by the manipulandum. With the shoulder free, we found activation of shoulder extensor muscles for pure elbow extension trials, appropriate for countering torques that arise at the shoulder due to forearm rotation. After locking the shoulder joint, we found a partial reduction in shoulder muscle activity, appropriate because locking the shoulder joint cancels the torques that arise at the shoulder due to forearm rotation. In our first three experiments, we tested whether and to what extent this partial reduction in shoulder muscle activity generalizes when reaching in different situations: 1) different initial shoulder orientation, 2) different initial elbow orientation, and 3) different reach distance/speed. We found generalization for the different shoulder orientation and reach distance/speed as measured by a reliable reduction in shoulder activity in these situations but no generalization for the different elbow orientation. In our fourth experiment, we found that generalization is also transferred to feedback control by applying mechanical perturbations and observing reflex responses in a distinct shoulder orientation. These results indicate that partial learning of new intersegmental dynamics is not sufficient for modifying a general internal model of arm dynamics.NEW & NOTEWORTHY Here we show that partially learning to reduce shoulder muscle activity following shoulder fixation generalizes to other movement conditions, but it does not generalize globally. These findings suggest that the partial learning of new intersegmental dynamics is not sufficient for modifying a general internal model of the arm's dynamics.

Cerebral Contribution to the Execution, But Not Recalibration, of Motor Commands in a Novel Walking Environment

Human movements are flexible as they continuously adapt to changes in the environment. The recalibration of corrective responses to sustained perturbations (e.g., constant force) altering one’s movement contributes to this flexibility. We asked whether the recalibration of corrective actions involve cerebral structures using stroke as a disease model. We characterized changes in muscle activity in stroke survivors and control subjects before, during, and after walking on a split-belt treadmill moving the legs at different speeds. The recalibration of corrective muscle activity was comparable between stroke survivors and control subjects, which was unexpected given the known deficits in feedback responses poststroke. Also, the intact recalibration in stroke survivors contrasted their limited ability to adjust their muscle activity during steady-state split-belt walking. Our results suggest that the recalibration and execution of motor commands are partially dissociable: cerebral lesions interfere with the execution, but not the recalibration, of motor commands on novel movement demands.

Automatic postural responses are scaled from the association between online feedback and feedforward control

Generation of automatic postural responses (APRs) scaled to magnitude of unanticipated postural perturbations is required to recover upright body stability. In the current experiment, we aimed to evaluate the effect of previous postural perturbations on APR scaling under conditions in which the current perturbation is equal to or different from the previous perturbation load inducing unanticipated forward body sway. We hypothesized that the APR is scaled from the association of the current perturbation magnitude and postural responses to preceding perturbations. Evaluation was made by comparing postural responses in the contexts of progressive increasing versus decreasing magnitudes of perturbation loads. Perturbation was applied by unanticipatedly releasing a cable pulling the body backwards, with loads corresponding to 6%, 8% and 10% of body mass. We found that the increasing as compared to the decreasing load sequence led to lower values of (a) displacement and (b) velocity of center of pressure, and of activation rate of the muscle gastrocnemius medialis across loads. Muscular activation onset latency decreased as a function increasing loads, but no significant effects of load sequence were found. These results lead to the conclusion that APRs to unanticipated perturbations are scaled from the association of somatosensory feedback signaling balance instability with feedforward control from postural responses to previous perturbations.

Gain control in the sensorimotor system

Coordinated movement depends on constant interaction between neural circuits that produce motor output and those that report sensory consequences. Fundamental to this process are mechanisms for controlling the influence that sensory signals have on motor pathways - for example, reducing feedback gains when they are disruptive and increasing gains when advantageous. Sensory gain control comes in many forms and serves diverse purposes - in some cases sensory input is attenuated to maintain movement stability and filter out irrelevant or self-generated signals, or enhanced to facilitate salient signals for improved movement execution and adaptation. The ubiquitous presence of sensory gain control across species at multiple levels of the nervous system reflects the importance of tuning the impact that feedback information has on behavioral output.

Distinct types of neural reorganization during long-term learning

What are the neural mechanisms of skill acquisition? Many studies find that long-term practice is associated with a functional reorganization of cortical neural activity. However, the link between these changes in neural activity and the behavioral improvements that occur is not well understood, especially for long-term learning that takes place over several weeks. To probe this link in detail, we leveraged a brain-computer interface (BCI) paradigm in which rhesus monkeys learned to master nonintuitive mappings between neural spiking in primary motor cortex and computer cursor movement. Critically, these BCI mappings were designed to disambiguate several different possible types of neural reorganization. We found that during the initial phase of learning, lasting minutes to hours, rapid changes in neural activity common to all neurons led to a fast suppression of motor error. In parallel, local changes to individual neurons gradually accrued over several weeks of training. This slower timescale cortical reorganization persisted long after the movement errors had decreased to asymptote and was associated with more efficient control of movement. We conclude that long-term practice evokes two distinct neural reorganization processes with vastly different timescales, leading to different aspects of improvement in motor behavior. NEW & NOTEWORTHY We leveraged a brain-computer interface learning paradigm to track the neural reorganization occurring throughout the full time course of motor skill learning lasting several weeks. We report on two distinct types of neural reorganization that mirror distinct phases of behavioral improvement: a fast phase, in which global reorganization of neural recruitment leads to a quick suppression of motor error, and a slow phase, in which local changes in individual tuning lead to improvements in movement efficiency.