A Dual-Learning Paradigm Simultaneously Improves Multiple Features of Gait Post-Stroke

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.

Reinforcement feedback impairs locomotor adaptation and retention

Introduction

Locomotor adaptation is a motor learning process used to alter spatiotemporal elements of walking that are driven by prediction errors, a discrepancy between the expected and actual outcomes of our actions. Sensory and reward prediction errors are two different types of prediction errors that can facilitate locomotor adaptation. Reward and punishment feedback generate reward prediction errors but have demonstrated mixed effects on upper extremity motor learning, with punishment enhancing adaptation, and reward supporting motor memory. However, an in-depth behavioral analysis of these distinct forms of feedback is sparse in locomotor tasks.

Methods

For this study, three groups of healthy young adults were divided into distinct feedback groups [Supervised, Reward, Punishment] and performed a novel locomotor adaptation task where each participant adapted their knee flexion to 30 degrees greater than baseline, guided by visual supervised or reinforcement feedback (Adaptation). Participants were then asked to recall the new walking pattern without feedback (Retention) and after a washout period with feedback restored (Savings).

Results

We found that all groups learned the adaptation task with external feedback. However, contrary to our initial hypothesis, enhancing sensory feedback with a visual representation of the knee angle (Supervised) accelerated the rate of learning and short-term retention in comparison to monetary reinforcement feedback. Reward and Punishment displayed similar rates of adaptation, short-term retention, and savings, suggesting both types of reinforcement feedback work similarly in locomotor adaptation. Moreover, all feedback enhanced the aftereffect of locomotor task indicating changes to implicit learning.

Discussion

These results demonstrate the multi-faceted nature of reinforcement feedback on locomotor adaptation and demonstrate the possible different neural substrates that underly reward and sensory prediction errors during different motor tasks.

Reduced corticospinal drive and inflexible temporal adaptation during visually guided walking in older adults

Corticospinal drive during walking is reduced in older adults compared with young adults, but it is not clear how this decrease might compromise one's ability to adjust stepping, particularly during visuomotor adaptation. We hypothesize that age-related changes in corticospinal drive could predict differences in older adults' step length and step time adjustments in response to visual perturbations compared with younger adults. Healthy young (n = 21; age 18-33 yr) and older adults (n = 20; age 68-80 yr) were tested with a treadmill task, incorporating visual feedback of the foot position and stepping targets in real-time. During adaptation, the visuomotor gain was reduced on one side, causing the foot cursor and step targets to move slower on that side of the screen (i.e., split-visuomotor adaptation). Corticospinal drive was quantified by coherence between electromyographic signals in the beta-gamma frequency band (15-45 Hz). The results showed that 1) older adults adapted to visuomotor perturbations during walking, with a similar reduction in error asymmetry compared with younger adults; 2) however, older adults showed reduced adaptation in step time symmetry, despite demonstrating similar adaptation in step length asymmetry compared with younger adults; and 3) smaller overall changes in step time asymmetry was associated with reduced corticospinal drive to the tibialis anterior in the slow leg during split-visuomotor adaptation. These findings suggest that changes in corticospinal drive may affect older adults' control of step timing in response to visual challenges. This could be important for safe navigation when walking in different environments or dealing with unexpected circumstances.NEW & NOTEWORTHY Corticospinal input is essential for visually guided walking, especially when the walking pattern must be modified to accurately step on safe locations. Age-related changes in corticospinal drive are associated with inflexible step time, which necessitates different locomotor adaptation strategies in older adults.

Asymmetric shoe height induces reactive changes in gait kinematics but not kinetics in healthy young adults

BACKGROUND

Footwear interventions are a potential avenue to correct walking asymmetry in neurologic populations, such as stroke. However, the motor learning mechanisms that underlie the changes in walking imposed by asymmetric footwear are unclear.

RESEARCH QUESTION

The objectives of this study were to examine symmetry changes during and after an asymmetric shoe height intervention in (1) vertical impulse and (2) spatiotemporal gait parameters and (3) joint kinematics, in healthy young adults METHODS: Eleven healthy young adults (3 males, 8 females; 21.2 ± 3.1 years old) participated in this study. Participants walked on an instrumented treadmill at 1.3 m/s for four conditions: (1) a 5-minute familiarization with equal shoe height, (2) a 5-minute baseline with equal shoe height, (3) a 10-minute intervention, where participants walked with asymmetric shoe height with a 10 mm shoe insert in one shoe, and (4) a 10-minute post-intervention, where participants walked with equal shoe height. Asymmetry in kinetics and kinematics were used to identify changes during intervention and aftereffects, a hallmark of feedforward adaptation RESULTS: Participants did not alter vertical impulse asymmetry (p = 0.667) nor stance time asymmetry (p = 0.228). During the intervention, step time asymmetry (p = 0.003) and double support asymmetry (p < 0.001) were greater compared to baseline. Leg joint asymmetry during stance (Ankle plantarflexion: p < 0.001; Knee flexion: p < 0.001; Hip extension: p = 0.011) was greater during the intervention compared to baseline. However, changes in spatiotemporal gait variables and joint mechanics did not demonstrate aftereffects.

SIGNIFICANCE

Our results show that healthy human adults change gait kinematics, but not weight-bearing symmetry with asymmetrical footwear. This suggests that healthy humans prioritize maintaining vertical impulse by changing their kinematics. Further, the changes in gait kinematics are short-lived, suggesting feedback-based control, and a lack of feedforward motor adaptations.

Visuomotor errors drive step length and step time adaptation during 'virtual' split-belt walking: the effects of reinforcement feedback

Precise foot placement is dependent on changes in spatial and temporal coordination between two legs in response to a perturbation during walking. Here, we used a 'virtual' split-belt adaptation task to examine the effects of reinforcement (reward and punishment) feedback about foot placement on the changes in error, step length and step time asymmetry. Twenty-seven healthy adults (20 ± 2.5 years) walked on a treadmill with continuous feedback of the foot position and stepping targets projected on a screen, defined by a visuomotor gain for each leg. The paradigm consisted of a baseline period (same gain on both legs), visuomotor adaptation period (split: one high = 'fast', one low = 'slow' gain) and post-adaptation period (same gain). Participants were divided into 3 groups: control group received no score, reward group received increasing score for each target hit, and punishment group received decreasing score for each target missed. Re-adaptation was assessed 24 ± 2 h later. During early adaptation, the slow foot undershot and fast foot overshot the stepping target. Foot placement errors were gradually reduced by late adaptation, accompanied by increasing step length asymmetry (fast < slow step length) and step time asymmetry (fast > slow step time). Only the punishment group showed greater error reduction and step length re-adaptation on the next day. The results show that (1) explicit feedback of foot placement alone drives adaptation of both step length and step time asymmetry during virtual split-belt walking, and (2) specifically, step length re-adaptation driven by visuomotor errors may be enhanced by punishment feedback.

Neural Control of Human Locomotor Adaptation: Lessons about Changes with Aging

Walking patterns are adaptable in response to different environmental demands, which requires neural input from spinal and supraspinal structures. With an increase in age, there are changes in walking adaptation and in the neural control of locomotion, but the age-related changes in the neural control of locomotor adaptation is unclear. The purpose of this narrative review is to establish a framework where the age-related changes of neural control of human locomotor adaptation can be understood in terms of reactive feedback and predictive feedforward control driven by sensory feedback during locomotion. We parse out the effects of aging on (a) reactive adaptation to split-belt walking, (b) predictive adaptation to split-belt walking, (c) reactive visuomotor adaptation, and (d) predictive visuomotor adaptation, and hypothesize that specific neural circuits are influenced differentially with age, which influence locomotor adaptation. The differences observed in the age-related changes in walking adaptation across different locomotor adaptation paradigms will be discussed in light of the age-related changes in the neural mechanisms underlying locomotion.

The Effect of Split-Belt Treadmill Interventions on Step Length Asymmetry in Individuals Poststroke: A Systematic Review With Meta-Analysis

BACKGROUND

Individuals poststroke experience gait asymmetries that result in decreased community ambulation and a lower quality of life. A variety of studies have utilized split-belt treadmill training to investigate its effect on gait asymmetry, but many employ various methodologies that report differing results.

OBJECTIVE

The purpose of this meta-analysis was to determine the effects of split-belt treadmill walking on step length symmetry in individuals poststroke both during and following training.

METHODS

A comprehensive search of PubMed/MEDLINE, CINAHL, Web of Science, and Scopus was conducted to find peer-reviewed journal articles that included individuals poststroke that participated in a split-belt treadmill walking intervention. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) was used to assess risk of bias. Pooled Hedge's g with random effects models were used to estimate the effect of split-belt training on step length symmetry.

RESULTS

Twenty-one studies were assessed and included in the systematic review with 11 of them included in the meta-analysis. Included studies had an average STROBE score of 16.2 ± 2.5. The pooled effects for step length asymmetry from baseline to late adaptation were not significant (g = 0.060, P = .701). Large, significant effects were found at posttraining after a single session (g = 1.04, P < .01), posttraining after multiple sessions (g = -0.70, P = .01), and follow-up (g = -0.718, P = .023).

CONCLUSION

Results indicate split-belt treadmill training with the shorter step length on the fast belt has the potential to improve step length symmetry in individuals poststroke when long-term training is implemented, but randomized controlled trials are needed to confirm the efficacy of split-belt treadmill training.

Biofeedback for Post-stroke Gait Retraining: A Review of Current Evidence and Future Research Directions in the Context of Emerging Technologies

Real-time gait biofeedback is a promising rehabilitation strategy for improving biomechanical deficits in walking patterns of post-stroke individuals. Because wearable sensor technologies are creating avenues for novel applications of gait biofeedback, including use in tele-health, there is a need to evaluate the state of the current evidence regarding the effectiveness of biofeedback for post-stroke gait training. The objectives of this review are to: (1) evaluate the current state of biofeedback literature pertaining to post-stroke gait training; and (2) determine future research directions related to gait biofeedback in context of evolving technologies. Our overall goal was to determine whether gait biofeedback is effective at improving stroke gait deficits while also probing why and for whom gait biofeedback may be an efficacious treatment modality. Our literature review showed that the effects of gait biofeedback on post-stroke walking dysfunction are promising but are inconsistent in methodology and therefore results. We summarize sources of methodological heterogeneity in previous literature, such as inconsistencies in feedback target, feedback mode, dosage, practice structure, feedback structure, and patient characteristics. There is a need for larger-sample studies that directly compare different feedback parameters, employ more uniform experimental designs, and evaluate characteristics of potential responders. However, as these uncertainties in existing literature are resolved, the application of gait biofeedback has potential to extend neurorehabilitation clinicians' cues to individuals with post-stroke gait deficits during ambulation in clinical, home, and community settings, thereby increasing the quantity and quality of skilled repetitions during task-oriented stepping training. In addition to identifying gaps in previous research, we posit that future research directions should comprise an amalgam of mechanism-focused and clinical research studies, to develop evidence-informed decision-making guidelines for gait biofeedback strategies that are tailored to individual-specific gait and sensorimotor impairments. Wearable sensor technologies have the potential to transform gait biofeedback and provide greater access and wider array of options for clinicians while lowering rehabilitation costs. Novel sensing technologies will be particularly valuable for telehealth and home-based stepping exercise programs. In summary, gait biofeedback is a promising intervention strategy that can enhance efficacy of post-stroke gait rehabilitation in both clinical and tele-rehabilitation settings and warrants more in-depth research.

Use of explicit processes during a visually guided locomotor learning task predicts 24-h retention after stroke

Implicit and explicit processes can occur within a single locomotor learning task. The combination of these learning processes may impact how individuals acquire/retain the task. Because these learning processes rely on distinct neural pathways, neurological conditions may selectively impact the processes that occur, thus, impacting learning and retention. Thus, our purpose was to examine the contribution of implicit and explicit processes during a visually guided walking task and characterize the relationship between explicit processes and performance/retention in stroke survivors and age-matched healthy adults. Twenty chronic stroke survivors and twenty healthy adults participated in a 2-day treadmill study. Day 1 included baseline, acquisition1, catch, acquisition2, and immediate retention phases, and day 2 included 24-h retention. During acquisition phases, subjects learned to take a longer step with one leg through distorted visual feedback. During catch and retention phases, visual feedback was removed and subjects were instructed to walk normally (catch) or how they walked during the acquisition phases (retention). Change in step length from baseline to catch represented implicit processes. Change in step length from catch to the end of acquisition2 represented explicit processes. A mixed ANOVA found no difference in the type of learning between groups (P = 0.74). There was a significant relationship between explicit processes and 24-h retention in stroke survivors (r = 0.47, P = 0.04) but not in healthy adults (r = 0.34, P = 0.15). These results suggest that stroke may not affect the underlying learning mechanisms used during locomotor learning, but that these mechanisms impact how well stroke survivors retain the new walking pattern.NEW & NOTEWORTHY This study found that stroke survivors used implicit and explicit processes similar to age-matched healthy adults during a visually guided locomotion learning task. The amount of explicit processes was related to how well stroke survivors retained the new walking pattern but not to how well they performed during the task. This work illustrates the importance of understanding the underlying learning mechanisms to maximize retention of a newly learned motor behavior.

Unilateral step training can drive faster learning of novel gait patterns

Humans are capable of learning many new walking patterns. People have learned to snowshoe up mountains, racewalk marathons, and march in precise synchrony. But what is required to learn a new walking pattern? Here, we demonstrate that people can learn new walking patterns without actually walking. Through a series of experiments, we observe that stepping with only one leg can facilitate learning of an entirely new walking pattern (i.e., split-belt treadmill walking). We find that the nervous system learns from the relative speed difference between the legs-whether or not both legs are moving-and can transfer this learning to novel gaits. We also show that locomotor learning requires active movement: observing another person adapt their gait did not result in significantly faster learning. These findings reveal that people can learn new walking patterns without bilateral gait training, as stepping with one leg can facilitate adaptive learning that transfers to novel gait patterns.

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.

Providing low-dimensional feedback of a high-dimensional movement allows for improved performance of a skilled walking task

Learning a skilled movement often requires changing multiple dimensions of movement in a coordinated manner. Serial training is one common approach to learning a new movement pattern, where each feature is learned in isolation from the others. Once one feature is learned, we move on to the next. However, when learning a complex movement pattern, serial training is not only laborious but can also be ineffective. Often, movement features are linked such that they cannot simply be added together as we progress through training. Thus, the ability to learn multiple features in parallel could make training faster and more effective. When using visual feedback as the tool for changing movement, however, such parallel training may increase the attentional load of training and impair performance. Here, we developed a novel visual feedback system that uses principal component analysis to weight four features of movement to create a simple one-dimensional 'summary' of performance. We used this feedback to teach healthy, young participants a modified walking pattern and compared their performance to those who received four concurrent streams of visual information to learn the same goal walking pattern. We demonstrated that those who used the principal component-based visual feedback improved their performance faster and to a greater extent compared to those who received concurrent feedback of all features. These results suggest that our novel principal component-based visual feedback provides a method for altering multiple features of movement toward a prescribed goal in an intuitive, low-dimensional manner.

Individualized feedback to change multiple gait deficits in chronic stroke

Background

Walking deficits in people post-stroke are often multiple and idiosyncratic in nature. Limited patient and therapist resources necessitate prioritization of deficits such that some may be left unaddressed. More efficient delivery of therapy may alleviate this challenge. Here, we look to determine the utility of a novel principal component-based visual feedback system that targets multiple, patient-specific features of gait in people post-stroke.

Methods

Ten individuals with stroke received two sessions of visual feedback to attain a walking goal. This goal consisted of bilateral knee and hip joint angles of a typical ‘healthy’ walking pattern. The feedback system uses principal component analysis (PCA) to algorithmically weight each of the input features so that participants received one stream of performance feedback. In the first session, participants had to explore different patterns to achieve the goal, and in the second session they were informed of the goal walking pattern. Ten healthy, age-matched individuals received the same paradigm, but with a hemiparetic goal (i.e. to produce the pattern of an exemplar stroke participant). This was to distinguish the extent to which performance limitations in stroke were due neurological injury or the PCA based visual feedback itself.

Results

Principal component-based visual feedback can differentially bias multiple features of walking toward a prescribed goal. On average, individuals with stroke typically improved performance via increased paretic knee and hip flexion, and did not perform better with explicit instruction. In contrast, healthy people performed better (i.e. could produce the desired exemplar stroke pattern) in both sessions, and were best with explicit instruction. Importantly, the feedback for stroke participants accommodated a heterogeneous set of walking deficits by individually weighting each feature based on baseline walking.

Conclusions

People with and without stroke are able to use this novel visual feedback to train multiple, specific features of gait. Important for stroke, the PCA feedback allowed for targeting of patient-specific deficits. This feedback is flexible to any feature of walking in any plane of movement, thus providing a potential tool for therapists to simultaneously target multiple aberrant features of gait.