A Functional Taxonomy of Bottom-Up Sensory Feedback Processing for Motor Actions

Task-dependent coarticulation of movement sequences

Combining individual actions into sequences is a hallmark of everyday activities. Classical theories propose that the motor system forms a single specification of the sequence as a whole, leading to the coarticulation of the different elements. In contrast, recent neural recordings challenge this idea and suggest independent execution of each element specified separately. Here, we show that separate or coarticulated sequences can result from the same task-dependent controller, without implying different representations in the brain. Simulations show that planning for multiple reaches simultaneously allows separate or coarticulated sequences depending on instructions about intermediate goals. Human experiments in a two-reach sequence task validated this model. Furthermore, in co-articulated sequences, the second goal influenced long-latency stretch responses to external loads applied during the first reach, demonstrating the involvement of the sensorimotor network supporting fast feedback control. Overall, our study establishes a computational framework for sequence production that highlights the importance of feedback control in this essential motor skill.

Robustness and adaptability of sensorimotor skills in expert piano performance

Skillful sequential action requires the delicate balance of sensorimotor control, encompassing both robustness and adaptability. However, it remains unknown whether both motor and neural responses triggered by sensory perturbation undergo plastic adaptation as a consequence of extensive sensorimotor experience. We assessed the effects of transiently delayed tone production on the subsequent motor actions and event-related potentials (ERPs) during piano performance by comparing pianists and non-musicians. Following the perturbation, the inter-keystroke interval was abnormally prolonged in non-musicians but not in pianists. By contrast, the keystroke velocity following the perturbation was increased only in the pianists. A regression model demonstrated that the change in the inter-keystroke interval covaried with the ERPs, particularly at the frontal and parietal regions. The alteration in the keystroke velocity was associated with the P300 component of the temporal region. These findings suggest that different neural mechanisms underlie robust and adaptive sensorimotor skills across proficiency level.

Adaptation of the gain of the corrective lifting response in object manipulation transfers across the hand

Our ability to skillfully manipulate objects is supported by rapid corrective responses that are initiated when we experience perturbations that interfere with movement goals. For example, the corrective lifting response is triggered when an object is heavier than expected and fails to lift off the surface. In this situation, the absence of expected sensory feedback signalling lift off initiates, within ~ 90 ms, an increase in lifting force. Importantly, when people repeatedly lift an object that, on occasional catch trials, is heavier than expected, the gain of the corrective response, defined as the rate of force increase, adapts to the 'catch' weight. In the present study, we investigated whether this response adaption transfers intermanually. In the training phase, participants used either their left or right hand (counterbalanced) to repeatedly lift a 3 N object that unexpectedly increased to 9 N on catch trials, leading to an increase in the gain of the lifting response across catch trials. Participants then lifted the object with their other hand. On the first catch trial, the gain remained elevated and thus transferred across the hands. This finding suggests that the history of lifts performed by one hand updates the corrective responses for both hands.

Parkinsonian Tremor as Unstable Feedback in a Physiologically Consistent Control Framework

Parkinson's disease (PD) is characterized by decreased dopamine in the basal ganglia that causes excessive tonic inhibition of the thalamus. This excessive inhibition seems to explain inhibitory motor symptoms in PD, but the source of tremor remains unclear. This paper investigates how neural inhibition may change the closed-loop characteristics of the human motor control system to determine how this established pathophysiology could produce tremor. The rate-coding model of neural signals suggests increased inhibition decreases signal amplitude, which could create a mismatch between the closed-loop dynamics and the internal models that overcome proprioceptive feedback delays. This paper aims to identify a candidate model structure with decreased-amplitude-induced tremor in PD that also agrees with previously recorded movements of healthy and cerebellar patients. The optimal feedback control theory of human motor control forms the basis of the model. Key additional elements include gating of undesired movements via the basal ganglia-thalamus-motor cortex circuit and the treatment of the efferent copy of the control input as a measurement in the state estimator. Simulations confirm the model's ability to capture tremor in PD and also demonstrate how disease progression could affect tremor and other motor symptoms, providing insight into the existence of tremor and non-tremor phenotypes. Altogether, the physiological underpinnings of the model structure and the agreement of model predictions with clinical observations provides support for the hypothesis that unstable feedback produces parkinsonian tremor. Consequently, these results also support the associated framework for the neuroanatomy of human motor control.

Motor neurons generate pose-targeted movements via proprioceptive sculpting

Motor neurons are the final common pathway1 through which the brain controls movement of the body, forming the basic elements from which all movement is composed. Yet how a single motor neuron contributes to control during natural movement remains unclear. Here we anatomically and functionally characterize the individual roles of the motor neurons that control head movement in the fly, Drosophila melanogaster. Counterintuitively, we find that activity in a single motor neuron rotates the head in different directions, depending on the starting posture of the head, such that the head converges towards a pose determined by the identity of the stimulated motor neuron. A feedback model predicts that this convergent behaviour results from motor neuron drive interacting with proprioceptive feedback. We identify and genetically2 suppress a single class of proprioceptive neuron3 that changes the motor neuron-induced convergence as predicted by the feedback model. These data suggest a framework for how the brain controls movements: instead of directly generating movement in a given direction by activating a fixed set of motor neurons, the brain controls movements by adding bias to a continuing proprioceptive-motor loop.

Dual-tasking modulates movement speed but not value-based choices during walking

Value-based decision-making often occurs in multitasking scenarios relying on both cognitive and motor processes. Yet, laboratory experiments often isolate these processes, thereby neglecting potential interactions. This isolated approach reveals a dichotomy: the cognitive process by which reward influences decision-making is capacity-limited, whereas the influence of motor cost is free of such constraints. If true, dual-tasking should predominantly impair reward processing but not affect the impact of motor costs. To test this hypothesis, we designed a decision-making task in which participants made choices to walk toward targets for rewards while navigating past an obstacle. The motor cost to reach these rewards varied in real-time. Participants either solely performed the decision-making task, or additionally performed a secondary pitch-recall task. Results revealed that while both reward and motor costs influenced decision-making, the secondary task did not affect these factors. Instead, dual-tasking slowed down participants' walking, thereby reducing the overall reward rate. Hence, contrary to the prediction that the added cognitive demand would affect the weighing of reward or motor cost differentially, these processes seem to be maintained at the expense of slowing down the motor system. This slowdown may be indicative of interference at the locomotor level, thereby underpinning motor-cognitive interactions during decision-making.

A Cortical Mechanism Linking Saliency Detection and Motor Reactivity in Rhesus Monkeys

Sudden and surprising sensory events trigger neural processes that swiftly adjust behavior. To study the phylogenesis and the mechanism of this phenomenon, we trained two male rhesus monkeys to keep a cursor inside a visual target by exerting force on an isometric joystick. We examined the effect of surprising auditory stimuli on exerted force, scalp electroencephalographic (EEG) activity, and local field potentials (LFPs) recorded from the dorsolateral prefrontal cortex. Auditory stimuli elicited (1) a biphasic modulation of isometric force, a transient decrease followed by a corrective tonic increase, and (2) EEG and LFP deflections dominated by two large negative-positive waves (N70 and P130). The EEG potential was symmetrical and maximal at the scalp vertex, highly reminiscent of the human "vertex potential." Electrocortical potentials and force were tightly coupled: the P130 amplitude predicted the magnitude of the corrective force increase, particularly in the LFPs recorded from deep rather than superficial cortical layers. These results disclose a phylogenetically preserved corticomotor mechanism supporting adaptive behavior in response to salient sensory events.Significance Statement Survival in the natural world depends on an animal's capacity to adapt ongoing behavior to abrupt unexpected events. To study the neural mechanisms underlying this capacity, we trained monkeys to apply constant force on a joystick while we recorded their brain activity from the scalp and the prefrontal cortex contralateral to the hand holding the joystick. Unexpected auditory stimuli elicited a biphasic force modulation: a transient reduction followed by a corrective adjustment. The same stimuli also elicited EEG and LFP responses, dominated by a biphasic wave that predicted the magnitude of the behavioral adjustment. These results disclose a phylogenetically preserved corticomotor mechanism supporting adaptive behavior in response to unexpected events.

Fast Feedback Responses to Categorical Sensorimotor Errors That Do Not Indicate Error Magnitude Are Optimized Based on Short- and Long-Term Memory

Skilled motor performance depends critically on rapid corrective responses that act to preserve the goal of the movement in the face of perturbations. Although it is well established that the gain of corrective responses elicited while reaching toward objects adapts to different contexts, little is known about the adaptability of corrective responses supporting the manipulation of objects after they are grasped. Here, we investigated the adaptability of the corrective response elicited when an object being lifted is heavier than expected and fails to lift off when predicted. This response involves a monotonic increase in vertical load force triggered, within ∼90 ms, by the absence of expected sensory feedback signaling lift off and terminated when actual lift off occurs. Critically, because the actual weight of the object cannot be directly sensed at the moment the object fails to lift off, any adaptation of the corrective response would have to be based on memory from previous lifts. We show that when humans, including men and women, repeatedly lift an object that on occasional catch trials increases from a baseline weight to a fixed heavier weight, they scale the gain of the response (i.e., the rate of force increase) to the heavier weight within two to three catch trials. We also show that the gain of the response scales, on the first catch trial, with the baseline weight of the object. Thus, the gain of the lifting response can be adapted by both short- and long-term experience. Finally, we demonstrate that this adaptation preserves the efficacy of the response across contexts.SIGNIFICANCE STATEMENT Here, we present the first investigation of the adaptability of the corrective lifting response elicited when an object is heavier than expected and fails to lift off when predicted. A striking feature of the response, which is driven by a sensory prediction error arising from the absence of expected sensory feedback, is that the magnitude of the error is unknown. That is, the motor system only receives a categorical error indicating that the object is heavier than expected but not its actual weight. Although the error magnitude is not known at the moment the response is elicited, we show that the response can be scaled to predictions of error magnitude based on both recent and long-term memories.

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.

How can we apply decision-making theories to wild animal behavior? Predictions arising from dual process theory and Bayesian decision theory

Our understanding of decision-making processes and cognitive biases is ever increasing, thanks to an accumulation of testable models and a large body of research over the last several decades. The vast majority of this work has been done in humans and laboratory animals because these study subjects and situations allow for tightly controlled experiments. However, it raises questions about how this knowledge can be applied to wild animals in their complex environments. Here, we review two prominent decision-making theories, dual process theory and Bayesian decision theory, to assess the similarities in these approaches and consider how they may apply to wild animals living in heterogenous environments within complicated social groupings. In particular, we wanted to assess when wild animals are likely to respond to a situation with a quick heuristic decision and when they are likely to spend more time and energy on the decision-making process. Based on the literature and evidence from our multi-destination routing experiments on primates, we find that individuals are likely to make quick, heuristic decisions when they encounter routine situations, or signals/cues that accurately predict a certain outcome, or easy problems that experience or evolutionary history has prepared them for. Conversely, effortful decision-making is likely in novel or surprising situations, when signals and cues have unpredictable or uncertain relationships to an outcome, and when problems are computationally complex. Though if problems are overly complex, satisficing via heuristics is likely, to avoid costly mental effort. We present hypotheses for how animals with different socio-ecologies may have to distribute their cognitive effort. Finally, we examine the conservation implications and potential cognitive overload for animals experiencing increasingly novel situations caused by current human-induced rapid environmental change.

Evaluation of stretch reflex synergies in the upper limb using principal component analysis (PCA)

The dynamic nature of movement and muscle activation emphasizes the importance of a sound experimental design. To ensure that an experiment determines what we intend, the design must be carefully evaluated. Before analyzing data, it is imperative to limit the number of outliers, biases, and skewness. In the present study, a simple center-out experiment was performed by 16 healthy volunteers. The experiment included three load conditions, two preparatory delays, two perturbations, and four targets placed along a diagonal path on a 2D plane. While the participants performed the tasks, the activity of seven arm muscles were monitored using surface electromyography (EMG). Principal component analysis (PCA) was used to evaluate the study design, identify muscle synergies, and assess the effects of individual quirks. With PCA, we can identify the trials that trigger stretch reflexes and pinpoint muscle synergies. The posterior deltoid, triceps long head, and brachioradialis were engaged when targets were in the direction of muscle shortening and the perturbation was applied in the opposite direction. Similarly, the pectoralis and anterior deltoid were engaged when the targets were in the direction of muscle shortening and the perturbation was applied in the opposite direction. The stretch reflexes were not triggered when the perturbation brought the hand in the direction of, or into the target, except if the muscle was pre-loaded. The use of PCA was also proven valuable when evaluating participant performance. While individual quirks are to be expected, failure to perform trials as expected can adversely affect the study results.

Aging increases proprioceptive error for a broad range of movement speed and distance estimates in the upper limb

Previous work has identified age-related declines in proprioception within a narrow range of limb movements. It is unclear whether these declines are consistent across a broad range of movement characteristics that more closely represent daily living. Here we aim to characterize upper limb error in younger and older adults across a range of movement speeds and distances. The objective of this study was to determine how proprioceptive matching accuracy changes as a function of movement speed and distance, as well as understand the effects of aging on these accuracies. We used an upper limb robotic test of proprioception to vary the speed and distance of movement in two groups: younger (n = 20, 24.25 ± 3.34 years) and older adults (n = 21, 63 ± 10.74 years). The robot moved one arm and the participant was instructed to mirror-match the movement with their opposite arm. Participants matched seven different movement speeds (0.1-0.4 m/s) and five distances (7.5-17.5 cm) over 350 trials. Spatial (e.g., End Point Error) and temporal (e.g., Peak Speed Ratio) outcomes were used to quantify proprioceptive accuracy. Regardless of the speed or distance of movement, we found that older controls had significantly reduced proprioceptive matching accuracy compared to younger control participants (p ≤ 0.05). When movement speed was varied, we observed that errors in proprioceptive matching estimates of spatial and temporal measures were significantly higher for older adults for all but the slowest tested speed (0.1 m/s) for the majority of parameters. When movement distance was varied, we observed that errors in proprioceptive matching estimates were significantly higher for all distances, except for the longest distance (17.5 cm) for older adults compared to younger adults. We found that the magnitude of proprioceptive matching errors was dependent on the characteristics of the reference movement, and that these errors scaled increasingly with age. Our results suggest that aging significantly negatively impacts proprioceptive matching accuracy and that proprioceptive matching errors made by both groups lies along a continuum that depends on movement characteristics and that these errors are amplified due to the typical aging process.

A robot-based interception task to quantify upper limb impairments in proprioceptive and visual feedback after stroke

BACKGROUND

A key motor skill is the ability to rapidly interact with our dynamic environment. Humans can generate goal-directed motor actions in response to sensory stimulus within ~ 60-200ms. This ability can be impaired after stroke, but most clinical tools lack any measures of rapid feedback processing. Reaching tasks have been used as a framework to quantify impairments in generating motor corrections for individuals with stroke. However, reaching may be inadequate as an assessment tool as repeated reaching can be fatiguing for individuals with stroke. Further, reaching requires many trials to be completed including trials with and without disturbances, and thus, exacerbate fatigue. Here, we describe a novel robotic task to quantify rapid feedback processing in healthy controls and compare this performance with individuals with stroke to (more) efficiently identify impairments in rapid feedback processing.

METHODS

We assessed a cohort of healthy controls (n = 135) and individuals with stroke (n = 40; Mean 41 days from stroke) in the Fast Feedback Interception Task (FFIT) using the Kinarm Exoskeleton robot. Participants were instructed to intercept a circular white target moving towards them with their hand represented as a virtual paddle. On some trials, the arm could be physically perturbed, the target or paddle could abruptly change location, or the target could change colour requiring the individual to now avoid the target.

RESULTS

Most participants with stroke were impaired in reaction time (85%) and end-point accuracy (83%) in at least one of the task conditions, most commonly with target or paddle shifts. Of note, this impairment was also evident in most individuals with stroke when performing the task using their unaffected arm (75%). Comparison with upper limb clinical measures identified moderate correlations with the FFIT.

CONCLUSION

The FFIT was able to identify a high proportion of individuals with stroke as impaired in rapid feedback processing using either the affected or unaffected arms. The task allows many different types of feedback responses to be efficiently assessed in a short amount of time.

Brain-machine interface learning is facilitated by specific patterning of distributed cortical feedback

Neuroprosthetics offer great hope for motor-impaired patients. One obstacle is that fine motor control requires near-instantaneous, rich somatosensory feedback. Such distributed feedback may be recreated in a brain-machine interface using distributed artificial stimulation across the cortical surface. Here, we hypothesized that neuronal stimulation must be contiguous in its spatiotemporal dynamics to be efficiently integrated by sensorimotor circuits. Using a closed-loop brain-machine interface, we trained head-fixed mice to control a virtual cursor by modulating the activity of motor cortex neurons. We provided artificial feedback in real time with distributed optogenetic stimulation patterns in the primary somatosensory cortex. Mice developed a specific motor strategy and succeeded to learn the task only when the optogenetic feedback pattern was spatially and temporally contiguous while it moved across the topography of the somatosensory cortex. These results reveal spatiotemporal properties of the sensorimotor cortical integration that set constraints on the design of neuroprosthetics.

Task Instructions and the Need for Feedback Correction Influence the Contribution of Visual Errors to Reach Adaptation

Previous research has questioned whether motor adaptation is shaped by an optimal combination of multisensory error signals. Here, we expanded on this work by investigating how the use of visual and somatosensory error signals during online correction influences single-trial adaptation. To this end, we exposed participants to a random sequence of force-field perturbations and recorded their corrective responses as well as the after-effects exhibited during the subsequent unperturbed movement. In addition to the force perturbation, we artificially decreased or increased visual errors by multiplying hand deviations by a gain smaller or larger than one. Corrective responses to the force perturbation clearly scaled with the size of the visual error, but this scaling did not transfer one-to-one to motor adaptation and we observed no consistent interaction between limb and visual errors on adaptation. However, reducing visual errors during perturbation led to a small reduction of after-effects and this residual influence of visual feedback was eliminated when we instructed participants to control their hidden hand instead of the visual hand cursor. Taken together, our results demonstrate that task instructions and the need to correct for errors during perturbation are important factors to consider if we want to understand how the sensorimotor system uses and combines multimodal error signals to adapt movements.

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.

Somatosensory Information in Skilled Motor Performance: A Narrative Review

Historically, research aimed at improving motor performance has largely focused on the neural processes involved in motor execution due to their role in muscle activation. However, accompanying somatosensory and proprioceptive sensory information is also vitally involved in performing motor skills. Here we review research from interdisciplinary fields to provide a description for how somatosensation informs the successful performance of motor skills as well as emphasize the need for careful selection of study methods to isolate the neural processes involved in somatosensory perception. We also discuss upcoming strategies of intervention that have been used to improve performance via somatosensory targets. We believe that a greater appreciation for somatosensation's role in motor learning and control will enable researchers and practitioners to develop and apply methods for the enhancement of human performance that will benefit clinical, healthy, and elite populations alike.

Linking cortex and contraction-Integrating models along the corticomuscular pathway

Computational models of the neuromusculoskeletal system provide a deterministic approach to investigate input-output relationships in the human motor system. Neuromusculoskeletal models are typically used to estimate muscle activations and forces that are consistent with observed motion under healthy and pathological conditions. However, many movement pathologies originate in the brain, including stroke, cerebral palsy, and Parkinson's disease, while most neuromusculoskeletal models deal exclusively with the peripheral nervous system and do not incorporate models of the motor cortex, cerebellum, or spinal cord. An integrated understanding of motor control is necessary to reveal underlying neural-input and motor-output relationships. To facilitate the development of integrated corticomuscular motor pathway models, we provide an overview of the neuromusculoskeletal modelling landscape with a focus on integrating computational models of the motor cortex, spinal cord circuitry, α-motoneurons  and skeletal muscle in regard to their role in generating voluntary muscle contraction. Further, we highlight the challenges and opportunities associated with an integrated corticomuscular pathway model, such as challenges in defining neuron connectivities, modelling standardisation, and opportunities in applying models to study emergent behaviour. Integrated corticomuscular pathway models have applications in brain-machine-interaction, education, and our understanding of neurological disease.

How the timing of visual feedback influences goal-directed arm movements: delays and presentation rates

Visual feedback normally helps guide movements to their goal. When moving one's hand, such guidance has to deal with a sensorimotor delay of about 100 ms. When moving a cursor, it also has to deal with a delay of tens of milliseconds that arises between the hand moving the mouse and the cursor moving on the screen. Moreover, the cursor is presented at a certain rate, so only positions corresponding with the position of the mouse at certain moments are presented. How does the additional delay and the rate at which cursor positions are updated influence how well the cursor can be guided to the goal? We asked participants to move a cursor to consecutive targets as quickly as they could. They did so for various additional delays and presentation rates. It took longer for the mouse to reach the target when the additional delay was longer. It also took longer when a lower presentation rate was achieved by not presenting the cursor all the time. The fraction of the time during which the cursor was present was more important than the rate at which the cursor's position was updated. We conclude that the way human arm movements are guided benefits from continuous access to recent visual feedback.

Single-Trial Dynamics of Competing Reach Plans in the Human Motor Periphery

Contemporary motor control theories propose competition between multiple motor plans before the winning command is executed. While most competitions are completed before movement onset, movements are often initiated before the competition has been resolved. An example of this is saccadic averaging, wherein the eyes land at an intermediate location between two visual targets. Behavioral and neurophysiological signatures of competing motor commands have also been reported for reaching movements, but debate remains about whether such signatures attest to an unresolved competition, arise from averaging across many trials, or reflect a strategy to optimize behavior given task constraints. Here, we recorded EMG activity from an upper limb muscle (m. pectoralis) while 12 (8 female) participants performed an immediate response reach task, freely choosing between one of two identical and suddenly presented visual targets. On each trial, muscle recruitment showed two distinct phases of directionally tuned activity. In the first wave, time-locked ∼100 ms of target presentation, muscle activity was clearly influenced by the nonchosen target, reflecting a competition between reach commands that was biased in favor of the ultimately chosen target. This resulted in an initial movement intermediate between the two targets. In contrast, the second wave, time-locked to voluntary reach onset, was not biased toward the nonchosen target, showing that the competition between targets was resolved. Instead, this wave of activity compensated for the averaging induced by the first wave. Thus, single-trial analysis reveals an evolution in how the nonchosen target differentially influences the first and second wave of muscle activity.SIGNIFICANCE STATEMENT Contemporary theories of motor control suggest that multiple motor plans compete for selection before the winning command is executed. Evidence for this is found in intermediate reach movements toward two potential target locations, but recent findings have challenged this notion by arguing that intermediate reaching movements reflect an optimal response strategy. By examining upper limb muscle recruitment during a free-choice reach task, we show early recruitment of a suboptimal averaged motor command to the two targets that subsequently transitions to a single motor command that compensates for the initially averaged motor command. Recording limb muscle activity permits single-trial resolution of the dynamic influence of the nonchosen target through time.

Capacity Limits Lead to Information Bottlenecks in Ongoing Rapid Motor Behaviors

Studies of ongoing, rapid motor behaviors have often focused on the decision-making implicit in the task. Here, we instead study how decision-making integrates with the perceptual and motor systems and propose a framework of limited-capacity, pipelined processing with flexible resources to understand rapid motor behaviors. Results from three experiments show that human performance is consistent with our framework: participants perform objectively worse as task difficulty increases, and, surprisingly, this drop in performance is largest for the most skilled performers. As well, our analysis shows that the worst-performing participants can perform equally well under increased task demands, which is consistent with flexible neural resources being allocated to reduce bottleneck effects and improve overall performance. We conclude that capacity limits lead to information bottlenecks and that processes like attention help reduce the effects that these bottlenecks have on maximal performance.

Movement characteristics impact decision-making and vice versa

Previous studies suggest that humans are capable of coregulating the speed of decisions and movements if promoted by task incentives. It is unclear however whether such behavior is inherent to the process of translating decisional information into movements, beyond posing a valid strategy in some task contexts. Therefore, in a behavioral online study we imposed time constraints to either decision- or movement phases of a sensorimotor task, ensuring that coregulating decisions and movements was not promoted by task incentives. We found that participants indeed moved faster when fast decisions were promoted and decided faster when subsequent finger tapping movements had to be executed swiftly. These results were further supported by drift diffusion modelling and inspection of psychophysical kernels: Sensorimotor delays related to initiating the finger tapping sequence were shorter in fast-decision as compared to slow-decision blocks. Likewise, the decisional speed-accuracy tradeoff shifted in favor of faster decisions in fast-tapping as compared to slow-tapping blocks. These findings suggest that decisions not only impact movement characteristics, but that properties of movement impact the time taken to decide. We interpret these behavioral results in the context of embodied decision-making, whereby shared neural mechanisms may modulate decisions and movements in a joint fashion.

Assistive Loading Promotes Goal-Directed Tuning of Stretch Reflex Gains

Voluntary movements are prepared before they are executed. Preparatory activity has been observed across the CNS and recently documented in first-order neurons of the human PNS (i.e., in muscle spindles). Changes seen in sensory organs suggest that independent modulation of stretch reflex gains may represent an important component of movement preparation. The aim of the current study was to further investigate the preparatory modulation of short-latency stretch reflex responses (SLRs) and long-latency stretch reflex responses (LLRs) of the dominant upper limb of human subjects. Specifically, we investigated how different target parameters (target distance and direction) affect the preparatory tuning of stretch reflex gains in the context of goal-directed reaching, and whether any such tuning depends on preparation duration and the direction of background loads. We found that target distance produced only small variations in reflex gains. In contrast, both SLR and LLR gains were strongly modulated as a function of target direction, in a manner that facilitated the upcoming voluntary movement. This goal-directed tuning of SLR and LLR gains was present or enhanced when the preparatory delay was sufficiently long (>250 ms) and the homonymous muscle was unloaded [i.e., when a background load was first applied in the direction of homonymous muscle action (assistive loading)]. The results extend further support for a relatively slow-evolving process in reach preparation that functions to modulate reflexive muscle stiffness, likely via the independent control of fusimotor neurons. Such control can augment voluntary goal-directed movement and is triggered or enhanced when the homonymous muscle is unloaded.

Online reach correction in 6- and 11-month-old infants

The current study investigated the development of online reach control. Six- and 11-month-old infants reached for a toy while their hand position was tracked. The toy either remained stationary (baseline trials) or unexpectedly displaced left- or rightward during the reach (perturbation trials). To obtain a measure of online reach correction, we compared reaches in the perturbation trials to reaches in baseline trials using autoregression analysis. Infants of both age groups adjusted their reach trajectories in the direction of the displacement. Moreover, we divided the reaching movements into movement units, defined as the submovements of a reach between local minima in hand speed. Eleven-month-old infants adjusted their reach within the span of a single movement unit; corrections in 6-month-olds spanned multiple movement units. These results suggest that the reach control system has a rudimentary replanning capacity by 6 months of age, which, with age, further develops to a more sophisticated online control mechanism for ongoing reaches.

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.

A bicycle can be balanced by stochastic optimal feedback control but only with accurate speed estimates

Balancing a bicycle is typical for the balance control humans perform as a part of a whole range of behaviors (walking, running, skating, skiing, etc.). This paper presents a general model of balance control and applies it to the balancing of a bicycle. Balance control has both a physics (mechanics) and a neurobiological component. The physics component pertains to the laws that govern the movements of the rider and his bicycle, and the neurobiological component pertains to the mechanisms via which the central nervous system (CNS) uses these laws for balance control. This paper presents a computational model of this neurobiological component, based on the theory of stochastic optimal feedback control (OFC). The central concept in this model is a computational system, implemented in the CNS, that controls a mechanical system outside the CNS. This computational system uses an internal model to calculate optimal control actions as specified by the theory of stochastic OFC. For the computational model to be plausible, it must be robust to at least two inevitable inaccuracies: (1) model parameters that the CNS learns slowly from interactions with the CNS-attached body and bicycle (i.e., the internal noise covariance matrices), and (2) model parameters that depend on unreliable sensory input (i.e., movement speed). By means of simulations, I demonstrate that this model can balance a bicycle under realistic conditions and is robust to inaccuracies in the learned sensorimotor noise characteristics. However, the model is not robust to inaccuracies in the movement speed estimates. This has important implications for the plausibility of stochastic OFC as a model for motor control.

Body and visual instabilities functionally modulate implicit reaching corrections

Hierarchical brain-information-processing schemes have frequently assumed that the flexible but slow voluntary action modulates a direct sensorimotor process that can quickly generate a reaction in dynamical interaction. Here we show that the quick visuomotor process for manual movement is modulated by postural and visual instability contexts that are related but remote and prior states to manual movements. A preceding unstable postural context significantly enhanced the reflexive manual response induced by a large-field visual motion during hand reaching while the response was evidently weakened by imposing a preceding random-visual-motion context. These modulations are successfully explained by the Bayesian optimal formulation in which the manual response elicited by visual motion is ascribed to the compensatory response to the estimated self-motion affected by the preceding contextual situations. Our findings suggest an implicit and functional mechanism that links the variability and uncertainty of remote states to the quick sensorimotor transformation.

Parietofrontal oscillations show hand-specific interactions with top-down movement plans

To generate a hand-specific reach plan, the brain must integrate hand-specific signals with the desired movement strategy. Although various neurophysiology/imaging studies have investigated hand-target interactions in simple reach-to-target tasks, the whole brain timing and distribution of this process remain unclear, especially for more complex, instruction-dependent motor strategies. Previously, we showed that a pro/anti pointing instruction influences magnetoencephalographic (MEG) signals in frontal cortex that then propagate recurrently through parietal cortex (Blohm G, Alikhanian H, Gaetz W, Goltz HC, DeSouza JF, Cheyne DO, Crawford JD. NeuroImage 197: 306-319, 2019). Here, we contrasted left versus right hand pointing in the same task to investigate 1) which cortical regions of interest show hand specificity and 2) which of those areas interact with the instructed motor plan. Eight bilateral areas, the parietooccipital junction (POJ), superior parietooccipital cortex (SPOC), supramarginal gyrus (SMG), medial/anterior interparietal sulcus (mIPS/aIPS), primary somatosensory/motor cortex (S1/M1), and dorsal premotor cortex (PMd), showed hand-specific changes in beta band power, with four of these (M1, S1, SMG, aIPS) showing robust activation before movement onset. M1, SMG, SPOC, and aIPS showed significant interactions between contralateral hand specificity and the instructed motor plan but not with bottom-up target signals. Separate hand/motor signals emerged relatively early and lasted through execution, whereas hand-motor interactions only occurred close to movement onset. Taken together with our previous results, these findings show that instruction-dependent motor plans emerge in frontal cortex and interact recurrently with hand-specific parietofrontal signals before movement onset to produce hand-specific motor behaviors.NEW & NOTEWORTHY The brain must generate different motor signals depending on which hand is used. The distribution and timing of hand use/instructed motor plan integration are not understood at the whole brain level. Using MEG we show that different action planning subnetworks code for hand usage and integrating hand use into a hand-specific motor plan. The timing indicates that frontal cortex first creates a general motor plan and then integrates hand specificity to produce a hand-specific motor plan.

Pressure pain threshold and somatosensory abnormalities in different ages and functional conditions of post-stroke elderly

Background

Somatosensory deficits and abnormal pain sensitivity are highly prevalent among stroke survivors, which negatively impacts their quality of life and recovery process. However, the factors for pressure pain threshold (PPT) and somatosensory abnormalities in post-stroke elderly remain unknown. The aim of this study was to explore the effects of age, side and other functional conditions, such as spasticity and motor functions, on PPT and sensory abnormalities among elderly after stroke.

Methods

The cross-sectional study finally included 43 post-stroke elderly aged over 60 and assessed the PPT of 14 bilateral muscles widely located in the whole body by using a digital force gage. Meanwhile, spasticity, motor function, joint pain and activity of daily living (ADL) were evaluated by the Modified Ashworth scale, Fugl-Meyer, and Barthel Index, respectively. All participants were divided into higher-aged and lower-aged groups based on the median age of all of them.

Results

Higher age tended to be associated with higher sensitivity but not significant except for one upper limb muscle, and the affected side showed significantly higher PPTs than the unaffected side in three out of seven muscles (p < 0.05). Furthermore, the somatosensory abnormalities in the affected side, particularly hypoalgesia, were more frequent in higher-aged than lower-aged patients in most assessed muscles. Meanwhile, patients with spasticity showed more increment of PPTs in affected muscles around the knee joint than patients without spasticity (p < 0.05). Patients with better motor functions, less joint pain and higher ADL performed less bilateral differences of PPTs than other patients in some muscles (p < 0.05).

Conclusions

The age and side differences of mechanical pain sensitivity were found among post-stroke elderly. Older patients show higher sensitivity in both sides compared with the younger ones, and the affected side of the elder shows more somatosensory abnormalities, particularly hypoalgesia, than that of the younger ones. Post-stroke elderly in good functional conditions, such as normal muscle tone, better physical function and daily activities, and less joint pain, seems to have more equal pain sensitivity between both sides than those in poor conditions.

Quantitatively assessing aging effects in rapid motor behaviours: a cross-sectional study

BACKGROUND

An individual's rapid motor skills allow them to perform many daily activities and are a hallmark of physical health. Although age and sex are both known to affect motor performance, standardized methods for assessing their impact on upper limb function are limited.

METHODS

Here we perform a cross-sectional study of 643 healthy human participants in two interactive motor tasks developed to quantify sensorimotor abilities, Object-Hit (OH) and Object-Hit-and-Avoid (OHA). The tasks required participants to hit virtual objects with and without the presence of distractor objects. Velocities and positions of hands and objects were recorded by a robotic exoskeleton, allowing a variety of parameters to be calculated for each trial. We verified that these tasks are viable for measuring performance in healthy humans and we examined whether any of our recorded parameters were related to age or sex.

RESULTS

Our analysis shows that both OH and OHA can assess rapid motor behaviours in healthy human participants. It also shows that while some parameters in these tasks decline with age, those most associated with the motor system do not. Three parameters show significant sex-related effects in OH, but these effects disappear in OHA.

CONCLUSIONS

This study suggests that the underlying effect of aging on rapid motor behaviours is not on the capabilities of the motor system, but on the brain's capacity for processing inputs into motor actions. Additionally, this study provides a baseline description of healthy human performance in OH and OHA when using these tasks to investigate age-related declines in sensorimotor ability.

Human muscle spindles are wired to function as controllable signal-processing devices

Muscle spindles are encapsulated sensory organs found in most of our muscles. Prevalent models of sensorimotor control assume the role of spindles is to reliably encode limb posture and movement. Here, I argue that the traditional view of spindles is outdated. Spindle organs can be tuned by spinal γ motor neurons that receive top-down and peripheral input, including from cutaneous afferents. A new model is presented, viewing γ motor activity as an intermediate coordinate transformation that allows multimodal information to converge on spindles, creating flexible coordinate representations at the level of the peripheral nervous system. That is, I propose that spindles play a unique overarching role in the nervous system: that of a peripheral signal-processing device that flexibly facilitates sensorimotor performance, according to task characteristics. This role is compatible with previous findings and supported by recent studies with naturalistically active humans. Such studies have so far shown that spindle tuning enables the independent preparatory control of reflex muscle stiffness, the selective extraction of information during implicit motor adaptation, and for segmental stretch reflexes to operate in joint space. Incorporation of advanced signal-processing at the periphery may well prove a critical step in the evolution of sensorimotor control theories.

Vagus nerve stimulation drives selective circuit modulation through cholinergic reinforcement

Vagus nerve stimulation (VNS) is a neuromodulation therapy for a broad and expanding set of neurologic conditions. However, the mechanism through which VNS influences central nervous system circuitry is not well described, limiting therapeutic optimization. VNS leads to widespread brain activation, but the effects on behavior are remarkably specific, indicating plasticity unique to behaviorally engaged neural circuits. To understand how VNS can lead to specific circuit modulation, we leveraged genetic tools including optogenetics and in vivo calcium imaging in mice learning a skilled reach task. We find that VNS enhances skilled motor learning in healthy animals via a cholinergic reinforcement mechanism, producing a rapid consolidation of an expert reach trajectory. In primary motor cortex (M1), VNS drives precise temporal modulation of neurons that respond to behavioral outcome. This suggests that VNS may accelerate motor refinement in M1 via cholinergic signaling, opening new avenues for optimizing VNS to target specific disease-relevant circuitry.

The influence of the motor command accuracy on the prediction error and the automatic corrective response

The online control system allows for automatic corrective response to unexpected perturbation. This corrective response may involve a prediction error between the sensory prediction by the motor command and the actual feedback signal. Therefore, we attempted to investigate the effect of motor command accuracy on the automatic corrective response. Participants were asked to move a cursor displayed on a monitor and required to reach the center of a Gaussian blob target as accurately as possible for small and large Gaussian blob conditions. The accuracy of the motor command was manipulated by the size of the Gaussian blob. In half of the trials, a perturbation occurred in which the cursor position jumped 10 mm to either the left or right from the actual position, which induced an automatic corrective response. This corrective response was detected by the acceleration signal on the lateral axis. In addition, the prediction error was estimated by the amplitude of the N1 event-related potential (ERP) of the EEG signal. We found that the automatic response and N1 ERP were significantly larger in the small Gaussian blob conditions than in the large one. This result indicates that the automatic corrective response is affected by the certainty of the motor command manipulated by the Gaussian blob. Furthermore, the linear mixed-effect model (LME) indicated that the response is associated with the N1 ERP. Therefore, we suggest that the motor command accuracy affects the prediction error, which in turn modulates the automatic corrective response.

Joint Specificity and Lateralization of Upper Limb Proprioceptive Perception

Proprioception is the sense of position and movement of body segments. The widespread distribution of proprioceptors in human anatomy raises questions about proprioceptive uniformity across different body parts. For the upper limbs, previous research, using mostly active and/or contralateral matching tasks, has suggested better proprioception of the non-preferred arm, and at the elbow rather than the wrist. Here we assessed proprioceptive perception through an ipsilateral passive matching task by comparing the elbow and wrist joints of the preferred and non-preferred arms. We hypothesized that upper limb proprioception would be better at the elbow of the non-preferred arm. We found signed errors to be less variable at the non-preferred elbow than at the preferred elbow and both wrists. Signed errors at the elbow were also more stable than at the wrist. Across individuals, signed errors at the preferred and non-preferred elbows were correlated. Also, variable signed errors at the preferred wrist, non-preferred wrist, and preferred elbow were correlated. These correlations suggest that an individual with relatively consistent matching errors at one joint may have relatively consistent matching errors at another joint. Our findings also support the view that proprioceptive perception varies across upper limb joints, meaning that a single joint assessment is insufficient to provide a general assessment of an individual's proprioception.

The role of feedback in the production of skilled finger sequences

Actions involving fine control of the hand, for example, grasping an object, rely heavily on sensory information from the fingertips. Although the integration of feedback during the execution of individual movements is well understood, less is known about the use of sensory feedback in the control of skilled movement sequences. To address this gap, we trained participants to produce sequences of finger movements on a keyboard-like device over a 4-day training period. Participants received haptic, visual, and auditory feedback indicating the occurrence of each finger press. We then either transiently delayed or advanced the feedback for a single press by a small amount of time (30 or 60 ms). We observed that participants rapidly adjusted their ongoing finger press by either accelerating or prolonging the ongoing press, in accordance with the direction of the perturbation. Furthermore, we could show that this rapid behavioral modulation was driven by haptic feedback. Although these feedback-driven adjustments reduced in size with practice, they were still clearly present at the end of training. In contrast to the directionally specific effect we observed on the perturbed press, a feedback perturbation resulted in a delayed onset of the subsequent presses irrespective of perturbation direction or feedback modality. This observation is consistent with a hierarchical organization of even very skilled and fast movement sequences, with different levels reacting distinctly to sensory perturbations.NEW & NOTEWORTHY Sensory feedback is important during the execution of a movement. However, little is known about how sensory feedback is used during the production of movement sequences. Here, we show two distinct feedback processes in the execution of fast finger movement sequences. By transiently delaying or advancing the feedback of a single press within a sequence, we observed a directionally specific effect on the perturbed press and a directionally non-specific effect on the subsequent presses.

Reward-Dependent Selection of Feedback Gains Impacts Rapid Motor Decisions

Target reward influences motor planning strategies through modulation of movement vigor. Considering current theories of sensorimotor control suggesting that movement planning consists in selecting a goal-directed control strategy, we sought to investigate the influence of reward on feedback control. Here, we explored this question in three human reaching experiments. First, we altered the explicit reward associated with the goal target and found an overall increase in feedback gains for higher target rewards, highlighted by larger velocities, feedback responses to external loads, and background muscle activity. Then, we investigated whether the differences in target rewards across multiple goals impacted rapid motor decisions during movement. We observed idiosyncratic switching strategies dependent on both target rewards and, surprisingly, the feedback gains at perturbation onset: the more vigorous movements were less likely to switch to a new goal following perturbations. To gain further insight into a causal influence of the feedback gains on rapid motor decisions, we demonstrated that biasing the baseline activity and reflex gains by means of a background load evoked a larger proportion of target switches in the direction opposite to the background load associated with lower muscle activity. Together, our results demonstrate an impact of target reward on feedback control and highlight the competition between movement vigor and flexibility.

The influences of target size and recent experience on the vigour of adjustments to ongoing movements

People adjust their on-going movements to changes in the environment. It takes about 100 ms to respond to an abrupt change in a target’s position. Does the vigour of such responses depend on the extent to which responding is beneficial? We asked participants to tap on targets that jumped laterally once their finger started to move. In separate blocks of trials the target either remained at the new position so that it was beneficial to respond to the jump, or jumped back almost immediately so that it was disadvantageous to do so. We also varied the target’s size, because a smaller, less vigorous adjustment is enough to place the finger within a larger target. There was a systematic relationship between the vigour of the response and the remaining time until the tap: the shorter the remaining time the more vigorous the response. This relationship did not depend on the target’s size or whether or not the target jumped back. It was already known that the vigour of responses to target jumps depends on the magnitude of the jump and on the time available for adjusting the movement to that jump. We show that the vigour of the response is precisely tuned to the time available for making the required adjustment irrespective of whether responding in this manner is beneficial.

Hybrid FPGA–CPU-Based Architecture for Object Recognition in Visual Servoing of Arm Prosthesis

The present paper proposes an implementation of a hybrid hardware–software system for the visual servoing of prosthetic arms. We focus on the most critical vision analysis part of the system. The prosthetic system comprises a glass-worn eye tracker and a video camera, and the task is to recognize the object to grasp. The lightweight architecture for gaze-driven object recognition has to be implemented as a wearable device with low power consumption (less than 5.6 W). The algorithmic chain comprises gaze fixations estimation and filtering, generation of candidates, and recognition, with two backbone convolutional neural networks (CNN). The time-consuming parts of the system, such as SIFT (Scale Invariant Feature Transform) detector and the backbone CNN feature extractor, are implemented in FPGA, and a new reduction layer is introduced in the object-recognition CNN to reduce the computational burden. The proposed implementation is compatible with the real-time control of the prosthetic arm.

Hierarchical Integration of Communicative and Spatial Perspective‐Taking Demands in Sensorimotor Control of Referential Pointing

Recognized as a simple communicative behavior, referential pointing is cognitively complex because it invites a communicator to consider an addressee's knowledge. Although we know referential pointing is affected by addressees’ physical location, it remains unclear whether and how communicators’ inferences about addressees’ mental representation of the interaction space influence sensorimotor control of referential pointing. The communicative perspective‐taking task requires a communicator to point at one out of multiple referents either to instruct an addressee which one should be selected (communicative, COM) or to predict which one the addressee will select (non‐communicative, NCOM), based on either which referents can be seen (Level‐1 perspective‐taking, PT1) or how the referents were perceived (Level‐2 perspective‐taking, PT2) by the addressee. Communicators took longer to initiate the movements in PT2 than PT1 trials, and they held their pointing fingers for longer at the referent in COM than NCOM trials. The novel findings of this study pertain to trajectory control of the pointing movements. Increasing both communicative and perspective‐taking demands led to longer pointing trajectories, with an under‐additive interaction between those two experimental factors. This finding suggests that participants generate communicative behaviors that are as informative as required rather than overly exaggerated displays, by integrating communicative and perspective‐taking information hierarchically during sensorimotor control. This observation has consequences for models of human communication. It implies that the format of communicative and perspective‐taking knowledge needs to be commensurate with the movement dynamics controlled by the sensorimotor system.

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.

Rotational dynamics in motor cortex are consistent with a feedback controller

Recent studies have identified rotational dynamics in motor cortex (MC), which many assume arise from intrinsic connections in MC. However, behavioral and neurophysiological studies suggest that MC behaves like a feedback controller where continuous sensory feedback and interactions with other brain areas contribute substantially to MC processing. We investigated these apparently conflicting theories by building recurrent neural networks that controlled a model arm and received sensory feedback from the limb. Networks were trained to counteract perturbations to the limb and to reach toward spatial targets. Network activities and sensory feedback signals to the network exhibited rotational structure even when the recurrent connections were removed. Furthermore, neural recordings in monkeys performing similar tasks also exhibited rotational structure not only in MC but also in somatosensory cortex. Our results argue that rotational structure may also reflect dynamics throughout the voluntary motor system involved in online control of motor actions.

The effects of physical training versus combined action observation and motor imagery in conjunction with physical training on upper-extremity performance

INTRODUCTION

Combined action observation and motor imagery training (AO+MI training), which involves motor imagery during action observation and physical training, has been attracting attention as an effective strategy for learning motor skills. However, little has been reported on the effects of AO+MI training. In the present study, we compared the effects of AO+MI training to the effects of physical training on upper-extremity performance.

MATERIALS AND METHODS

Ninety-six healthy participants were randomly assigned to either the control group or the experimental group. Sport stacking, which is often used to evaluate upper-extremity performance, was adopted for the task. The experiment was scheduled for three days. The training was 20 min per day. The control group performed only physical training, while the experimental group performed four 5-min AO+MI training sessions. Time taken to complete a sport stacking try (task completion time) was defined as the index of speed of upper-extremity performance and number of fallen cups as the index of its accuracy. The outcomes within each group and between the two groups were compared.

RESULTS

Both AO+MI training and physical training showed reduced task completion time and increased number of fallen cups. There were no significant differences in the degree of changes between the groups.

CONCLUSION

Results from the present study showed that AO+MI training and physical training had almost the same influence on upper-extremity performance in the early stages of learning sport stacking. This result suggests that AO+MI training may be an effective and low-burden training method for participants.

Modulation of tactile feedback for the execution of dexterous movement

[Figure: see text].

Measuring age differences in executive control using rapid motor decisions in a robotic object hit and avoid task

Age-related declines in executive control are commonly assessed with neuropsychological tests that also rely on sensory and motor processes that are not typically measured in those tasks. It is therefore difficult to isolate the cognitive contributions from sensorimotor contributions to performance impairments. Rapid motor decision-making tasks may also be sensitive to age differences in executive control but allow for the measurement of sensorimotor contributors to task performance. Recently developed object hit (OH) and object hit and avoid (OHA) tasks using a robotic manipulandum are sensitive to motor and cognitive aspects of performance in stroke and Parkinson's disease. However, the impact of healthy aging, and the specific cognitive mechanisms involved in these tasks has not been assessed. We administered the OH and OHA tasks to 77 younger and 59 healthy older adults to evaluate the relative age differences in the perceptual-motor/sensory, movement coordination, and cognitive measures of performance. The Trail Making Test (TMT) Parts A and B were administered to assess the extent to which the cognitive contributors to OHA task performance are associated with executive functioning. After controlling for hand movement speed, age differences were largest for cognitive measures, with smaller differences in perceptual-motor speed and sensory measures, and little differences in bimanual and spatial coordination measures of performance. The cognitive measures were associated with executive functioning measures from the TMT task. These findings provide evidence that rapid motor decision-making tasks are sensitive to age differences in executive control and can isolate the cognitive from the sensorimotor contributions to task performance. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Towards a unified neural mechanism for reactive adaptive behaviour

Surviving in natural environments requires animals to sense sudden events and swiftly adapt behaviour accordingly. The study of such Reactive Adaptive Behaviour (RAB) has been central to a number of research streams, all orbiting around movement science but progressing in parallel, with little cross-field fertilization. We first provide a concise review of these research streams, independently describing four types of RAB: (1) cortico-muscular resonance, (2) stimulus locked response, (3) online motor correction and (4) action stopping. We then highlight remarkable similarities across these four RABs, suggesting that they might be subserved by the same neural mechanism, and propose directions for future research on this topic.

Two types of sensorimotor strategies for whole-body movement in individuals with stroke: a pilot study

PURPOSE

This study compared the sensory-motor interactions and strategies for whole-body movement in individuals with stroke who had damaged motor system area or sensory system area in the brain.

METHODS

Participants with hemiparesis were asked to perform sit-to-stand movements while their vision was restricted, which can affect completion of the task. The participants were divided into two groups. The first group had no history of lesions in the sensory system area but did have a history of lesions in the motor system area (no damaged sensory-system: NDS). The second group had a history of lesions in the sensory system area of the brain (damaged sensory-system: DS). Center-of-pressure (COP) trajectories were measured to evaluate balance control in participants with and without vision, and numbers of sub-movements (i.e. numbers of segmented movements which reflect the degree of use of the feedback loops) were measured to evaluate feedforward and feedback control. Movement times were also measured.

RESULTS

When vision was restricted, NDS participants showed increased variability in mediolateral COP trajectories during movement and utilized mainly feedforward control. In contrast, DS participants showed reduced variability in mediolateral COP trajectories during movement and utilized additional feedback control.

CONCLUSIONS

These results demonstrate two types of strategies for whole-body movements in individuals with stroke. These differences may be attributed to whether the individual can compensate for vision with somatic senses and whether appropriate processing of somatosensory information has been lost. Individuals with hemiparesis created dexterous and flexible strategies to execute tasks successfully, depending on the characteristics of their sensorimotor disorders.

Stretch reflexes

Many of us know about stretch reflexes from the doctor's office, when a physician taps the tendon near our kneecap to elicit a quick knee extension. This procedure is used as a diagnostic tool to determine the integrity of the spinal cord and the extension response it elicits may seem otherwise useless. In fact, the tendon tap taps into one aspect of a critical building block of mammalian motor control, the stretch reflexes. Stretch reflexes are often thought to quickly resist unexpected changes in muscle length via a very simple circuit in the spinal cord, and this is one circuit that the tendon tap engages. It turns out, however, that stretch reflexes support a myriad of functions and are highly flexible. Under naturalistic conditions, stretch reflexes are shaped by peripheral physiology and engage neural circuits spanning the spinal cord, brainstem and cerebral cortex. In this Primer, we outline what is currently known about stretch reflex function and its underlying mechanisms, with a specific focus on how the cascade of nested responses collectively known as stretch reflexes interact with and build off of one another to support real-world motor behavior.

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.

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.