Explicit and implicit locomotor learning in individuals with chronic hemiparetic stroke.

Motor learning involves both explicit and implicit processes that are fundamental for acquiring and adapting complex motor skills. However, stroke may damage the neural substrates underlying explicit and/or implicit learning, leading to deficits in overall motor performance. While both learning processes are typically used in concert in daily life and rehabilitation, no gait studies have determined how these processes function together after stroke when tested during a task that elicits dissociable contributions from both. Here, we compared explicit and implicit locomotor learning in individuals with chronic stroke to age- and sex-matched neurologically intact controls. We assessed implicit learning using split-belt adaptation (where two treadmill belts move at different speeds). We assessed explicit learning (i.e., strategy-use) using visual feedback during split-belt walking to help individuals explicitly correct for step length errors created by the split-belts. After the first 40 strides of split-belt walking, we removed the visual feedback and instructed individuals to walk comfortably, a manipulation intended to minimize contributions from explicit learning. We utilized a multi-rate state-space model to characterize individual explicit and implicit process contributions to overall behavioral change. The computational and behavioral analyses revealed that, compared to controls, individuals with chronic stroke demonstrated deficits in both explicit and implicit contributions to locomotor learning, a result that runs counter to prior work testing each process individually during gait. Since post-stroke locomotor rehabilitation involves interventions that rely on both explicit and implicit motor learning, future work should determine how locomotor rehabilitation interventions can be structured to optimize overall motor learning.

Reexposure to a sensorimotor perturbation produces opposite effects on explicit and implicit learning processes.

The motor system demonstrates an exquisite ability to adapt to changes in the environment and to quickly reset when these changes prove transient. If similar environmental changes are encountered in the future, learning may be faster, a phenomenon known as savings. In studies of sensorimotor learning, a central component of savings is attributed to the explicit recall of the task structure and appropriate compensatory strategies. Whether implicit adaptation also contributes to savings remains subject to debate. We tackled this question by measuring, in parallel, explicit and implicit adaptive responses in a visuomotor rotation task, employing a protocol that typically elicits savings. While the initial rate of learning was faster in the second exposure to the perturbation, an analysis decomposing the 2 processes showed the benefit to be solely associated with explicit re-aiming. Surprisingly, we found a significant decrease after relearning in aftereffect magnitudes during no-feedback trials, a direct measure of implicit adaptation. In a second experiment, we isolated implicit adaptation using clamped visual feedback, a method known to eliminate the contribution of explicit learning processes. Consistent with the results of the first experiment, participants exhibited a marked reduction in the adaptation function, as well as an attenuated aftereffect when relearning from the clamped feedback. Motivated by these results, we reanalyzed data from prior studies and observed a consistent, yet unappreciated pattern of attenuation of implicit adaptation during relearning. These results indicate that explicit and implicit sensorimotor processes exhibit opposite effects upon relearning: Explicit learning shows savings, while implicit adaptation becomes attenuated.

Interactions between sensory prediction error and task error during implicit motor learning.

Implicit motor recalibration allows us to flexibly move in novel and changing environments. Conventionally, implicit recalibration is thought to be driven by errors in predicting the sensory outcome of movement (i.e., sensory prediction errors). However, recent studies have shown that implicit recalibration is also influenced by errors in achieving the movement goal (i.e., task errors). Exactly how sensory prediction errors and task errors interact to drive implicit recalibration and, in particular, whether task errors alone might be sufficient to drive implicit recalibration remain unknown. To test this, we induced task errors in the absence of sensory prediction errors by displacing the target mid-movement. We found that task errors alone failed to induce implicit recalibration. In additional experiments, we simultaneously varied the size of sensory prediction errors and task errors. We found that implicit recalibration driven by sensory prediction errors could be continuously modulated by task errors, revealing an unappreciated dependency between these two sources of error. Moreover, implicit recalibration was attenuated when the target was simply flickered in its original location, even though this manipulation did not affect task error - an effect likely attributed to attention being directed away from the feedback cursor. Taken as a whole, the results were accounted for by a computational model in which sensory prediction errors and task errors, modulated by attention, interact to determine the extent of implicit recalibration.

Differential Effects of Cerebellar Degeneration on Feedforward versus Feedback Control across Speech and Reaching Movements.

Errors that result from a mismatch between predicted movement outcomes and sensory afference are used to correct ongoing movements through feedback control and to adapt feedforward control of future movements. The cerebellum has been identified as a critical part of the neural circuit underlying implicit adaptation across a wide variety of movements (reaching, gait, eye movements, and speech). The contribution of this structure to feedback control is less well understood. Although it has recently been shown in the speech domain that individuals with cerebellar degeneration produce larger online corrections for sensory perturbations than control participants, similar behavior has not been observed in other motor domains. Currently, comparisons across domains are limited by different population samples and potential ceiling effects in existing tasks. To assess the relationship between changes in feedforward and feedback control associated with cerebellar degeneration across motor domains, we evaluated adaptive (feedforward) and compensatory (feedback) responses to sensory perturbations in reaching and speech production in human participants of both sexes with cerebellar degeneration and neurobiologically healthy controls. As expected, the cerebellar group demonstrated impaired adaptation in both reaching and speech. In contrast, the groups did not differ in their compensatory response in either domain. Moreover, compensatory and adaptive responses in the cerebellar group were not correlated within or across motor domains. These results point to a general impairment in feedforward control with spared feedback control in cerebellar degeneration. However, the magnitude of feedforward impairments and potential changes in feedback-based control manifest in a domain-specific manner across individuals.SIGNIFICANCE STATEMENT The cerebellum contributes to feedforward updating of movement in response to sensory errors, but its role in feedback control is less understood. Here, we tested individuals with cerebellar degeneration (CD), using sensory perturbations to assess adaptation of feedforward control and feedback gains during reaching and speech production tasks. The results confirmed that CD leads to reduced adaption in both domains. However, feedback gains were unaffected by CD in either domain. Interestingly, measures of feedforward and feedback control were not correlated across individuals within or across motor domains. Together, these results indicate a general impairment in feedforward control with spared feedback control in CD. However, the magnitude of feedforward impairments manifests in a domain-specific manner across individuals.

Dissociable use-dependent processes for volitional goal-directed reaching.

Repetition of specific movement biases subsequent actions towards the practiced movement, a phenomenon known as use-dependent learning (UDL). Recent experiments that impose strict constraints on planning time have revealed two sources of use-dependent biases, one arising from dynamic changes occurring during motor planning and another reflecting a stable shift in motor execution. Here, we used a distributional analysis to examine the contribution of these biases in reaching. To create the conditions for UDL, the target appeared at a designated 'frequent' location on most trials, and at one of six 'rare' locations on other trials. Strikingly, the heading angles were bimodally distributed, with peaks at both frequent and rare target locations. Despite having no constraints on planning time, participants exhibited a robust bias towards the frequent target when movements were self-initiated quickly, the signature of a planning bias; notably, the peak near the rare target was shifted in the frequently practiced direction, the signature of an execution bias. Furthermore, these execution biases were not only replicated in a delayed-response task but were also insensitive to reward. Taken together, these results extend our understanding of how volitional movements are influenced by recent experience.

The Psychology of Reaching: Action Selection, Movement Implementation, and Sensorimotor Learning.

The study of motor planning and learning in humans has undergone a dramatic transformation in the 20 years since this journal's last review of this topic. The behavioral analysis of movement, the foundational approach for psychology, has been complemented by ideas from control theory, computer science, statistics, and, most notably, neuroscience. The result of this interdisciplinary approach has been a focus on the computational level of analysis, leading to the development of mechanistic models at the psychological level to explain how humans plan, execute, and consolidate skilled reaching movements. This review emphasizes new perspectives on action selection and motor planning, research that stands in contrast to the previously dominant representation-based perspective of motor programming, as well as an emerging literature highlighting the convergent operation of multiple processes in sensorimotor learning.

Individual differences in proprioception predict the extent of implicit sensorimotor adaptation.

Recent studies have revealed an upper bound in motor adaptation, beyond which other learning systems may be recruited. The factors determining this upper bound are poorly understood. The multisensory integration hypothesis states that this limit arises from opposing responses to visual and proprioceptive feedback. As individuals adapt to a visual perturbation, they experience an increasing proprioceptive error in the opposite direction, and the upper bound is the point where these two error signals reach an equilibrium. Assuming that visual and proprioceptive feedback are weighted according to their variability, there should be a correlation between proprioceptive variability and the limits of adaptation. Alternatively, the proprioceptive realignment hypothesis states that the upper bound arises when the (visually biased) sensed hand position realigns with the expected sensed position (target). When a visuo-proprioceptive discrepancy is introduced, the sensed hand position is biased toward the visual cursor, and the adaptive system counteracts this discrepancy by driving the hand away from the target. This hypothesis predicts a correlation between the size of the proprioceptive shift and the upper bound of adaptation. We tested these two hypotheses by considering natural variation in proprioception and motor adaptation across individuals. We observed a modest, yet reliable correlation between the upper bound of adaptation with both proprioceptive measures (variability and shift). Although the results do not clearly favor one hypothesis over the other, they underscore the critical role of proprioception in sensorimotor adaptation.NEW & NOTEWORTHY Although the sensorimotor system uses sensory feedback to remain calibrated, this learning process is constrained, limited by the maximum degree of plasticity. The factors determining this limit remain elusive. Guided by two hypotheses, we show that individual differences in the upper bound of adaptation in response to a visual perturbation can be predicted by the bias and variability in proprioception. These results underscore the critical, but often neglected role of proprioception in human motor learning.

The effect of visual uncertainty on implicit motor adaptation.

Sensorimotor adaptation is influenced by both the size and variance of error information. In the present study, we varied visual uncertainty and error size in a factorial manner and evaluated their joint effect on adaptation, using a feedback method that avoids inherent limitations with standard visuomotor tasks. Uncertainty attenuated adaptation, but only when the error was small. This striking interaction highlights a novel constraint for models of sensorimotor adaptation. Sensorimotor adaptation is driven by sensory prediction errors, the difference between the predicted and actual feedback. When the position of the feedback is made uncertain, motor adaptation is attenuated. This effect, in the context of optimal sensory integration models, has been attributed to the motor system discounting noisy feedback and thus reducing the learning rate. In its simplest form, optimal integration predicts that uncertainty would result in reduced learning for all error sizes. However, these predictions remain untested since manipulations of error size in standard visuomotor tasks introduce confounds in the degree to which performance is influenced by other learning processes such as strategy use. Here, we used a novel visuomotor task that isolates the contribution of implicit adaptation, independent of error size. In two experiments, we varied feedback uncertainty and error size in a factorial manner. At odds with the basic predictions derived from the optimal integration theory, the results show that uncertainty attenuated learning only when the error size was small but had no effect when the error size was large. We discuss possible mechanisms that may account for this interaction, considering how uncertainty may interact with the relevance assigned to the error signal or how the output of the adaptation system in terms of recalibrating the sensorimotor map may be modified by uncertainty.NEW & NOTEWORTHY Sensorimotor adaptation is influenced by both the size and variance of error information. In the present study, we varied visual uncertainty and error size in a factorial manner and evaluated their joint effect on adaptation, using a feedback method that avoids inherent limitations with standard visuomotor tasks. Uncertainty attenuated adaptation but only when the error was small. This striking interaction highlights a novel constraint for models of sensorimotor adaptation.

Beyond Physical Capacity: Factors Associated With Real-world Walking Activity After Stroke.

OBJECTIVE: To identify homogeneous subsets of survivors of chronic stroke who share similar characteristics across several domains and test if these groups differ in real-world walking activity. We hypothesized that variables representing the domains of walking ability, psychosocial, environment, and cognition would be important contributors in differentiating real-world walking activity in survivors of chronic stroke. DESIGN: Cross-sectional, secondary data analysis. SETTING: University/laboratory. PARTICIPANTS: A total of 283 individuals with chronic (≥6mo) stroke (N=238). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Thirteen variables representing 5 domains were included: (1) walking ability: 6-minute walk test (6MWT), self-selected speed (SSS) of gait; (2) psychosocial: Patient Health Questionnaire-9, Activities-specific Balance Confidence (ABC) scale; (3) physical health: low-density lipoprotein cholesterol, body mass index, Charlson Comorbidity Index (CCI); (4) cognition: Montreal Cognitive Assessment (MoCA); and (5) environment: living situation and marital status, work status, Area Deprivation Index (ADI), Walk Score. Mixture modeling was used to identify latent classes of survivors of stroke. After identifying the latent classes, walking activity, measured as steps per day (SPD), was included as a distal outcome to understand if classes were meaningfully different in their real-world walking RESULTS: A model with 3 latent classes was selected. The 6MWT, SSS, ABC scale, and Walk Score were significantly different among all 3 classes. Differences were also seen for the MoCA, ADI, and CCI between 2 of the 3 classes. Importantly, the distal outcome of SPD was significantly different in all classes, indicating that real-world walking activity differs among the groups identified by the mixture model. CONCLUSIONS: Survivors of stroke with lower walking ability, lower self-efficacy, lower cognitive abilities, and greater area deprivation had lower SPD. These results demonstrate that the physical and social environment (including socioeconomic factors) and cognitive function should also be considered when developing interventions to improve real-world walking activity after stroke.

Use-dependent plasticity explains aftereffects in visually guided locomotor learning of a novel step length asymmetry.

Studies of upper extremity reaching show that use-dependent plasticity, or learning from repetition, plays an important role in shaping motor behaviors. Yet the impact of repetition on locomotor learning is unclear, despite the fact that gait is developed and practiced over millions of repetitions. To test whether repetition alone can induce storage of a novel walking pattern, we instructed two groups of young healthy subjects to learn an asymmetric walking pattern through two distinct learning paradigms. The first group learned a new pattern through an established visual distortion paradigm, which provided both sensory prediction error and repetition of movement patterns to induce walking aftereffects, and the second received veridical feedback with a target change, which provided only repetition (use-dependent plasticity) to induce aftereffects. When feedback was removed, both groups demonstrated aftereffects in the primary outcome, step asymmetry index. Surprisingly, despite the different task demands, both groups produced similar aftereffect magnitudes, which also had similar rates of decay, suggesting that the addition of sensory prediction errors did not improve storage of learning beyond that induced by the use-dependent process alone. To further characterize the use-dependent process, we conducted a second experiment to quantify aftereffect size in a third group who practiced double the asymmetry magnitude. This new group showed a proportionately greater magnitude of the use-dependent aftereffect. Together, these findings show that the primary driver of storage of a new step length asymmetry during visually guided locomotor learning is repetition, not sensory prediction error, and this effect scales with the learning magnitude.NEW & NOTEWORTHY Use-dependent plasticity, or learning from repetition, is an important process for upper extremity reaching tasks, but its contribution to walking is not well established. Here, we demonstrate the existence of a dose-dependent, use-dependent process during visually guided treadmill walking. We also show that sensory prediction errors, previously thought to drive aftereffects in similar locomotor learning paradigms, do not appear to play a significant role in visually driven learning of a novel step asymmetry during treadmill walking.

A single exercise bout and locomotor learning after stroke: physiological, behavioural, and computational outcomes.

KEY POINTS: Previous work demonstrated an effect of a single high-intensity exercise bout coupled with motor practice on the retention of a newly acquired skilled arm movement, in both neurologically intact and impaired adults. In the present study, using behavioural and computational analyses we demonstrated that a single exercise bout, regardless of its intensity and timing, did not increase the retention of a novel locomotor task after stroke. Considering both present and previous work, we postulate that the benefits of exercise effect may depend on the type of motor learning (e.g. skill learning, sensorimotor adaptation) and/or task (e.g. arm accuracy-tracking task, walking). ABSTRACT: Acute high-intensity exercise coupled with motor practice improves the retention of motor learning in neurologically intact adults. However, whether exercise could improve the retention of locomotor learning after stroke is still unknown. Here, we investigated the effect of exercise intensity and timing on the retention of a novel locomotor learning task (i.e. split-belt treadmill walking) after stroke. Thirty-seven people post stroke participated in two sessions, 24 h apart, and were allocated to active control (CON), treadmill walking (TMW), or total body exercise on a cycle ergometer (TBE). In session 1, all groups exercised for a short bout (∼5 min) at low (CON) or high (TMW and TBE) intensity and before (CON and TMW) or after (TBE) the locomotor learning task. In both sessions, the locomotor learning task was to walk on a split-belt treadmill in a 2:1 speed ratio (100% and 50% fast-comfortable walking speed) for 15 min. To test the effect of exercise on 24 h retention, we applied behavioural and computational analyses. Behavioural data showed that neither high-intensity group showed greater 24 h retention compared to CON, and computational data showed that 24 h retention was attributable to a slow learning process for sensorimotor adaptation. Our findings demonstrated that acute exercise coupled with a locomotor adaptation task, regardless of its intensity and timing, does not improve retention of the novel locomotor task after stroke. We postulate that exercise effects on motor learning may be context specific (e.g. type of motor learning and/or task) and interact with the presence of genetic variant (BDNF Val66Met).

Strategies to augment volitional and reflex function may improve locomotor capacity following incomplete spinal cord injury.

Many studies highlight the remarkable plasticity demonstrated by spinal circuits following an incomplete spinal cord injury (SCI). Such plasticity can contribute to improvements in volitional motor recovery, such as walking function, although similar mechanisms underlying this recovery may also contribute to the manifestation of exaggerated responses to afferent input, or spastic behaviors. Rehabilitation interventions directed toward augmenting spinal excitability have shown some initial success in improving locomotor function. However, the potential effects of these strategies on involuntary motor behaviors may be of concern. In this article, we provide a brief review of the mechanisms underlying recovery of volitional function and exaggerated reflexes, and the potential overlap between these changes. We then highlight findings from studies that explore changes in spinal excitability during volitional movement in controlled conditions, as well as altered kinematic and behavioral performance during functional tasks. The initial focus will be directed toward recovery of reflex and volitional behaviors following incomplete SCI, followed by recent work elucidating neurophysiological mechanisms underlying patterns of static and dynamic muscle activation following chronic incomplete SCI during primarily single-joint movements. We will then transition to studies of locomotor function and the role of altered spinal integration following incomplete SCI, including enhanced excitability of specific spinal circuits with physical and pharmacological interventions that can modulate locomotor output. The effects of previous and newly developed strategies will need to focus on changes in both volitional function and involuntary spastic reflexes for the successful translation of effective therapies to the clinical setting.

Increased spinal reflex excitability is associated with enhanced central activation during voluntary lengthening contractions in human spinal cord injury.

This study of chronic incomplete spinal cord injury (SCI) subjects investigated patterns of central motor drive (i.e., central activation) of the plantar flexors using interpolated twitches, and modulation of soleus H-reflexes during lengthening, isometric, and shortening muscle actions. In a recent study of the knee extensors, SCI subjects demonstrated greater central activation ratio (CAR) values during lengthening (i.e., eccentric) maximal voluntary contractions (MVCs), compared with during isometric or shortening (i.e., concentric) MVCs. In contrast, healthy controls demonstrated lower lengthening CAR values compared with their isometric and shortening CARs. For the present investigation, we hypothesized SCI subjects would again produce their highest CAR values during lengthening MVCs, and that these increases in central activation were partially attributable to greater efficacy of Ia-α motoneuron transmission during muscle lengthening following SCI. Results show SCI subjects produced higher CAR values during lengthening vs. isometric or shortening MVCs (all P < 0.001). H-reflex testing revealed normalized H-reflexes (maximal SOL H-reflex-to-maximal M-wave ratios) were greater for SCI than controls during passive (P = 0.023) and active (i.e., 75% MVC; P = 0.017) lengthening, suggesting facilitation of Ia transmission post-SCI. Additionally, measures of spinal reflex excitability (passive lengthening maximal SOL H-reflex-to-maximal M-wave ratio) in SCI were positively correlated with soleus electromyographic activity and CAR values during lengthening MVCs (both P < 0.05). The present study presents evidence that patterns of dynamic muscle activation are altered following SCI, and that greater central activation during lengthening contractions is partly due to enhanced efficacy of Ia-α motoneuron transmission.

Muscle activation varies with contraction mode in human spinal cord injury.

INTRODUCTION: To better understand volitional force generation after chronic incomplete spinal cord injury (SCI), we examined muscle activation during single and repeated isometric, concentric, and eccentric knee extensor (KE) maximal voluntary contractions (MVCs). METHODS: Torque and electromyographic (EMG) activity were recorded during single and repeated isometric and dynamic KE MVCs in 11 SCI subjects. Central activation ratios (CARs) were calculated for all contraction modes in SCI subjects and 11 healthy controls. RESULTS: SCI subjects generated greater torque, KE EMG, and CARs during single eccentric vs. isometric and concentric MVCs (all P < 0.05). Torque and EMG remained similar during repeated eccentric MVCs; however, both increased during repeated isometric (>25%) and concentric (>30%) MVCs. CONCLUSIONS: SCI subjects demonstrated greater muscle activation during eccentric MVCs vs. isometric and concentric MVCs. This pattern of activation contrasts with the decreased eccentric activation demonstrated by healthy controls. Such information may aid development of novel rehabilitation interventions.

Reinforcement Learning during Locomotion.

When learning a new motor skill, people often must use trial and error to discover which movement is best. In the reinforcement learning framework, this concept is known as exploration and has been linked to increased movement variability in motor tasks. For locomotor tasks, however, increased variability decreases upright stability. As such, exploration during gait may jeopardize balance and safety, making reinforcement learning less effective. Therefore, we set out to determine if humans could acquire and retain a novel locomotor pattern using reinforcement learning alone. Young healthy male and female participants walked on a treadmill and were provided with binary reward feedback (indicated by a green checkmark on the screen) that was tied to a fixed monetary bonus, to learn a novel stepping pattern. We also recruited a comparison group who walked with the same novel stepping pattern but did so by correcting for target error, induced by providing real-time veridical visual feedback of steps and a target. In two experiments, we compared learning, motor variability, and two forms of motor memories between the groups. We found that individuals in the binary reward group did, in fact, acquire the new walking pattern by exploring (increasing motor variability). Additionally, while reinforcement learning did not increase implicit motor memories, it resulted in more accurate explicit motor memories compared with the target error group. Overall, these results demonstrate that humans can acquire new walking patterns with reinforcement learning and retain much of the learning over 24 h.

Explicit and implicit locomotor learning in individuals with chronic hemiparetic stroke.

Motor learning involves both explicit and implicit processes that are fundamental for acquiring and adapting complex motor skills. However, stroke may damage the neural substrates underlying explicit and/or implicit learning, leading to deficits in overall motor performance. While both learning processes are typically used in concert in daily life and rehabilitation, no gait studies have determined how these processes function together after stroke when tested during a task that elicits dissociable contributions from both. Here, we compared explicit and implicit locomotor learning in individuals with chronic stroke to age- and sex-matched neurologically intact controls. We assessed implicit learning using split-belt adaptation (where two treadmill belts move at different speeds). We assessed explicit learning (i.e., strategy-use) using visual feedback during split-belt walking to help individuals explicitly correct for step length errors created by the split-belts. The removal of visual feedback after the first 40 strides of split-belt walking, combined with task instructions, minimized contributions from explicit learning for the remainder of the task. We utilized a multi-rate state-space model to characterize individual explicit and implicit process contributions to overall behavioral change. The computational and behavioral analyses revealed that, compared to controls, individuals with chronic stroke demonstrated deficits in both explicit and implicit contributions to locomotor learning, a result that runs counter to prior work testing each process individually during gait. Since post-stroke locomotor rehabilitation involves interventions that rely on both explicit and implicit motor learning, future work should determine how locomotor rehabilitation interventions can be structured to optimize overall motor learning.

Fundamental processes in sensorimotor learning: Reasoning, refinement, and retrieval.

Motor learning is often viewed as a unitary process that operates outside of conscious awareness. This perspective has led to the development of sophisticated models designed to elucidate the mechanisms of implicit sensorimotor learning. In this review, we argue for a broader perspective, emphasizing the contribution of explicit strategies to sensorimotor learning tasks. Furthermore, we propose a theoretical framework for motor learning that consists of three fundamental processes: reasoning, the process of understanding action-outcome relationships; refinement, the process of optimizing sensorimotor and cognitive parameters to achieve motor goals; and retrieval, the process of inferring the context and recalling a control policy. We anticipate that this '3R' framework for understanding how complex movements are learned will open exciting avenues for future research at the intersection between cognition and action.

A reliable and efficient adaptive Bayesian method to assess static lower limb position sense.

Background: Lower limb proprioception is critical for maintaining stability during gait and may impact how individuals modify their movements in response to changes in the environment and body state, a process termed "sensorimotor adaptation". However, the connection between lower limb proprioception and sensorimotor adaptation during human gait has not been established. We suspect this gap is due in part to the lack of reliable, efficient methods to assess global lower limb proprioception in an ecologically valid context. New Method: We assessed static lower limb proprioception using an alternative forced choice task, administered twice to determine test-retest reliability. Participants stood on a dual-belt treadmill which passively moved one limb to stimulus locations selected by a Bayesian adaptive algorithm. At the stimulus locations, participants judged relative foot positions and the algorithm estimated the point of subjective equality (PSE) and the uncertainty of lower limb proprioception. Results: Using the Bland-Altman method, combined with Bayesian statistics, we found that both the PSE and uncertainty estimates had good reliability. Comparison with Existing Methods: Current methods assessing static lower limb proprioception do so within a single joint, in non-weight bearing positions, and rely heavily on memory. One exception assessed static lower limb proprioception in standing but did not measure reliability and contained confounds impacting participants' judgments, which we experimentally controlled here. Conclusions: This efficient and reliable method assessing lower limb proprioception will aid future mechanistic understanding of locomotor adaptation and serve as a useful tool for basic and clinical researchers studying balance and falls.

A reliable and efficient adaptive Bayesian method to assess static lower limb position sense.

BACKGROUND: Lower limb proprioception is critical for maintaining stability during gait and may impact how individuals modify their movements in response to changes in the environment and body state, a process termed "sensorimotor adaptation". However, the connection between lower limb proprioception and sensorimotor adaptation during human gait has not been established. We suspect this gap is due in part to the lack of reliable, efficient methods to assess global lower limb proprioception in an ecologically valid context. NEW METHOD: We assessed static lower limb proprioception using an alternative forced choice task, administered twice to determine test-retest reliability. Participants stood on a dual-belt treadmill which passively moved one limb to stimulus locations selected by a Bayesian adaptive algorithm. At the stimulus locations, participants judged relative foot positions and the algorithm estimated the point of subjective equality (PSE) and the uncertainty of lower limb proprioception. RESULTS: Using the Bland-Altman method, combined with Bayesian statistics, we found that both the PSE and uncertainty estimates had good reliability. COMPARISON WITH EXISTING METHOD(S): Current methods assessing static lower limb proprioception do so within a single joint, in non-weight bearing positions, and rely heavily on memory. One exception assessed static lower limb proprioception in standing but did not measure reliability and contained confounds impacting participants' judgments, which we experimentally controlled here. CONCLUSIONS: This efficient and reliable method assessing lower limb proprioception will aid future mechanistic understanding of locomotor adaptation and serve as a useful tool for basic and clinical researchers studying balance and falls.

Assessing Corticospinal Excitability During Goal-Directed Reaching Behavior.

Reaching is a widely studied behavior in motor physiology and neuroscience research. While reaching has been examined using a variety of behavioral manipulations, there remain significant gaps in the understanding of the neural processes involved in reach planning, execution, and control. The novel approach described here combines a two-dimensional reaching task with transcranial magnetic stimulation (TMS) and concurrent electromyography (EMG) recording from multiple muscles. This method allows for the noninvasive detection of corticospinal activity at precise time points during the unfolding of reaching movements. The example task code includes a delayed response reaching task with two possible targets displayed ± 45° off the midline. Single pulse TMS is delivered on the majority of task trials, either at the onset of the preparatory cue (baseline) or 100 ms prior to the imperative cue (delay). This sample design is suitable for investigating changes in corticospinal excitability during reach preparation. The sample code also includes a visuomotor perturbation (i.e., cursor rotation of ± 20°) to investigate the effects of adaptation on corticospinal excitability during reach preparation. The task parameters and TMS delivery can be adjusted to address specific hypotheses about the state of the motor system during reaching behavior. In the initial implementation, motor evoked potentials (MEPs) were successfully elicited on 83% of TMS trials, and reach trajectories were recorded on all trials.