Neurocognitive mechanisms of error-based motor learning

OPTIMAL theory's claims about motivation lack evidence in the motor learning literature

Motivation is commonly recognized by researchers and practitioners as a key factor for motor learning. The OPTIMAL theory of motor learning (Wulf & Lewthwaite, 2016) claims that practice conditions that enhance learners' expectancies for future successful outcomes or that are autonomy supportive are motivating, thus leading to better learning. To examine the current evidence of the association between motivation and motor learning, we searched the literature for studies that manipulated expectancies and/or autonomy support. Specifically, our goals were to assess whether these manipulations resulted in group differences in motivation and, if so, whether increased motivation was associated with learning advantages. Results showed that out of 166 experiments, only 21% (n = 35) included at least one measure of motivation, even though this is the main factor proposed by OPTIMAL theory to explain the learning benefits of these manipulations. Among those, only 23% (n = 8) found group-level effects on motivation, suggesting that these manipulations might not be as motivating as expected. Of the eight experiments that found a group-level effect on motivation, five also observed learning benefits, offering limited evidence that when practice conditions increase motivation, learning is more likely to occur. Overall, the small number of studies assessing motivation precludes any reliable conclusions on the association between motivation and motor learning from being drawn. Together, our results question whether manipulations implemented in the research lines supporting OPTIMAL theory are indeed motivating and highlight the lack of sufficient evidence in these literatures to support that increased motivation benefits motor learning.

The effects of verbal and spatial working memory on short- and long-latency sensorimotor circuits in the motor cortex

Multiple sensorimotor loops converge in the motor cortex to create an adaptable system capable of context-specific sensorimotor control. Afferent inhibition provides a non-invasive tool to investigate the substrates by which procedural and cognitive control processes interact to shape motor corticospinal projections. Varying the transcranial magnetic stimulation properties during afferent inhibition can probe specific sensorimotor circuits that contribute to short- and long-latency periods of inhibition in response to the peripheral stimulation. The current study used short- (SAI) and long-latency (LAI) afferent inhibition to probe the influence of verbal and spatial working memory load on the specific sensorimotor circuits recruited by posterior-anterior (PA) and anterior-posterior (AP) TMS-induced current. Participants completed two sessions where SAI and LAI were assessed during the short-term maintenance of two- or six-item sets of letters (verbal) or stimulus locations (spatial). The only difference between the sessions was the direction of the induced current. PA SAI decreased as the verbal working memory load increased. In contrast, AP SAI was not modulated by verbal working memory load. Visuospatial working memory load did not affect PA or AP SAI. Neither PA LAI nor AP LAI were sensitive to verbal or spatial working memory load. The dissociation of short-latency PA and AP sensorimotor circuits and short- and long-latency PA sensorimotor circuits with increasing verbal working memory load support multiple convergent sensorimotor loops that provide distinct functional information to facilitate context-specific supraspinal control.

Evaluating the influence of feedback on motor skill learning and motor performance for children with developmental coordination disorder: a systematic review

Introduction

Children with developmental coordination disorder (DCD) have difficulties with learning and performing physical tasks. It is well known that task-specific practice is effective in improving motor skills. Additional feedback during practice may function as a quality improvement mechanism and therefore enhance motor skill outcomes.

Aims

To investigate the effect of different forms of feedback on motor learning and motor performance in children with DCD.

Methods

A systematic review was conducted (registration CRD42020175118) to investigate the effectiveness of different types of feedback, compared to other forms of feedback, or no additional feedback, on motor learning and motor performance outcomes in children with DCD. The search was run across six electronic databases (last search January 2024). Two reviewers independently screened studies for inclusion, assessed the quality of included studies, and extracted relevant data. A narrative synthesis was performed and included studies that assessed motor learning and/or performance outcomes following an intervention that delivered a specific form of feedback in comparison to another form of feedback or no specific feedback.

Results

14 articles from 13 trials were included in this review. Feedback was delivered by providing various forms of feedback, including: knowledge of results, focus of attention and augmented feedback delivered via technology. No significant differences were found between different forms of feedback for motor learning or performance outcomes for children with DCD. Interventions that used technology (with augmented feedback) to deliver the intervention were found to be as effective as traditional therapy. All groups who participated in therapy, regardless of the presence or type of feedback received, improved in overall scores on a motor performance outcome assessment.

Conclusion

Despite the clear rationale for using feedback-oriented interventions for children with DCD, there is surprisingly limited and low-quality research. There is no clear evidence that one form of feedback is more effective than another, although it appears that feedback delivered via technology may be as effective as feedback delivered in traditional therapy interventions for children with DCD. Further exploration is required from appropriately powered and well-designed trials.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=175118, identifier (CRD42020175118).

When direction matters: Neural correlates of interlimb coordination of rhythm and beat

In a previous experiment, we found evidence for a bodily hierarchy governing interlimb coordination of rhythm and beat, using five effectors: 1) Left foot, 2) Right foot, 3) Left hand, 4) Right hand and 5) Voice. The hierarchy implies that, during simultaneous rhythm and beat performance and using combinations of two of these effectors, executing the task by performing the rhythm with an effector that has a higher number than the beat effector is significantly easier than vice versa. To investigate the neural underpinnings of this proposed bodily hierarchy, we here scanned 46 professional musicians using fMRI as they performed a rhythmic pattern with one effector while keeping the beat with another. The conditions combined the voice and the right hand (V + RH), the right hand and the left hand (RH + LH), and the left hand and the right foot (LH + RF). Each effector combination was performed with and against the bodily hierarchy. Going against the bodily hierarchy increased tapping errors significantly and also increased activity in key brain areas functionally associated with top-down sensorimotor control and bottom-up feedback processing, such as the cerebellum and SMA. Conversely, going with the bodily hierarchy engaged areas functionally associated with the default mode network and regions involved in emotion processing. Theories of general brain function that hold prediction as a key principle, propose that action and perception are governed by the brain's attempt to minimise prediction error at different levels in the brain. Following this viewpoint, our results indicate that going against the hierarchy induces stronger prediction errors, while going with the hierarchy allows for a higher degree of automatization. Our results also support the notion of a bodily hierarchy in motor control that prioritizes certain conductive and supportive tapping roles in specific effector combinations.

Effects of glabellar botulinum toxin injections on resting-state functional connectivity in borderline personality disorder

Meta-analyses suggest a sustained alleviation of depressive symptoms through glabellar botulinum toxin (BTX) injections. This can be explained by the disruption of facial feedback loops, which may moderate and reinforce the experience of negative emotions. Borderline personality disorder (BPD) is characterized by excessive negative emotions. Here, a seed-based resting-state functional connectivity (rsFC) analysis following BTX (N = 24) or acupuncture (ACU, N = 21) treatment in BPD is presented on areas related to the motor system and emotion processing. RsFC in BPD using a seed-based approach was analyzed. MRI data were measured before and 4 weeks after treatment. Based on previous research, the rsFC focus was on limbic and motor areas as well as the salience and default mode network. Clinically, after 4 weeks both groups showed a reduction of borderline symptoms. However, the anterior cingulate cortex (ACC) and the face area in the primary motor cortex (M1) displayed aberrant rsFC after BTX compared to ACU treatment. The M1 showed higher rsFC to the ACC after BTX treatment compared to ACU treatment. In addition, the ACC displayed an increased connectivity to the M1 as well as a decrease to the right cerebellum. This study shows first evidence for BTX-specific effects in the motor face region and the ACC. The observed effects of BTX on rsFC to areas are related to motor behavior. Since symptom improvement did not differ between the two groups, a BTX-specific effect seems plausible rather than a general therapeutic effect.

Distinguishing Laparoscopic Surgery Experts from Novices Using EEG Topographic Features

The study aimed to differentiate experts from novices in laparoscopic surgery tasks using electroencephalogram (EEG) topographic features. A microstate-based common spatial pattern (CSP) analysis with linear discriminant analysis (LDA) was compared to a topography-preserving convolutional neural network (CNN) approach. Expert surgeons (N = 10) and novice medical residents (N = 13) performed laparoscopic suturing tasks, and EEG data from 8 experts and 13 novices were analysed. Microstate-based CSP with LDA revealed distinct spatial patterns in the frontal and parietal cortices for experts, while novices showed frontal cortex involvement. The 3D CNN model (ESNet) demonstrated a superior classification performance (accuracy > 98%, sensitivity 99.30%, specificity 99.70%, F1 score 98.51%, MCC 97.56%) compared to the microstate based CSP analysis with LDA (accuracy ~90%). Combining spatial and temporal information in the 3D CNN model enhanced classifier accuracy and highlighted the importance of the parietal-temporal-occipital association region in differentiating experts and novices.

Distinct neural representations during a brain-machine interface and manual reaching task in motor cortex, prefrontal cortex, and striatum

Although brain-machine interfaces (BMIs) are directly controlled by the modulation of a select local population of neurons, distributed networks consisting of cortical and subcortical areas have been implicated in learning and maintaining control. Previous work in rodents has demonstrated the involvement of the striatum in BMI learning. However, the prefrontal cortex has been largely ignored when studying motor BMI control despite its role in action planning, action selection, and learning abstract tasks. Here, we compare local field potentials simultaneously recorded from primary motor cortex (M1), dorsolateral prefrontal cortex (DLPFC), and the caudate nucleus of the striatum (Cd) while nonhuman primates perform a two-dimensional, self-initiated, center-out task under BMI control and manual control. Our results demonstrate the presence of distinct neural representations for BMI and manual control in M1, DLPFC, and Cd. We find that neural activity from DLPFC and M1 best distinguishes control types at the go cue and target acquisition, respectively, while M1 best predicts target-direction at both task events. We also find effective connectivity from DLPFC → M1 throughout both control types and Cd → M1 during BMI control. These results suggest distributed network activity between M1, DLPFC, and Cd during BMI control that is similar yet distinct from manual control.

Observational Learning in Surgical Skill Development

Observation plays a key role in the development of surgical skills, as it allows trainees to learn from experts and improve their performance through trial-and-error practice. This process, known as motor learning, involves the creation of new neural pathways that enable precise control of surgical instruments through hand movements. In recent years, there has been a shift towards minimally invasive surgery, which requires surgeons to continually learn new motor skills to control specialized instrumentation. Motor learning can be enhanced through repetition and the observation of expert performances. Observational learning is particularly useful when it is used in combination with physical practice, as it can provide hints and clues about important aspects of the task that may not be immediately apparent through verbal instruction alone. The role of mirror neurons, which are activated both when an action is performed and when it is observed, is also important in the process of observational learning. By understanding the mechanisms behind observational learning and the factors that influence its effectiveness, trainers can optimize the use of this method in surgical training.

Distinct neural representations during a brain-machine interface and manual reaching task in motor cortex, prefrontal cortex, and striatum

Although brain-machine interfaces (BMIs) are directly controlled by the modulation of a select local population of neurons, distributed networks consisting of cortical and subcortical areas have been implicated in learning and maintaining control. Previous work in rodent BMI has demonstrated the involvement of the striatum in BMI learning. However, the prefrontal cortex has been largely ignored when studying motor BMI control despite its role in action planning, action selection, and learning abstract tasks. Here, we compare local field potentials simultaneously recorded from the primary motor cortex (M1), dorsolateral prefrontal cortex (DLPFC), and the caudate nucleus of the striatum (Cd) while nonhuman primates perform a two-dimensional, self-initiated, center-out task under BMI control and manual control. Our results demonstrate the presence of distinct neural representations for BMI and manual control in M1, DLPFC, and Cd. We find that neural activity from DLPFC and M1 best distinguish between control types at the go cue and target acquisition, respectively. We also found effective connectivity from DLPFC→M1 throughout trials across both control types and Cd→M1 during BMI control. These results suggest distributed network activity between M1, DLPFC, and Cd during BMI control that is similar yet distinct from manual control.

Decoding cerebro-spinal signatures of human behavior: application to motor sequence learning

Mapping the neural patterns that drive human behavior is a key challenge in neuroscience. Even the simplest of our everyday actions stem from the dynamic and complex interplay of multiple neural structures across the central nervous system (CNS). Yet, most neuroimaging research has focused on investigating cerebral mechanisms, while the way the spinal cord accompanies the brain in shaping human behavior has been largely overlooked. Although the recent advent of functional magnetic resonance imaging (fMRI) sequences that can simultaneously target the brain and spinal cord has opened up new avenues for studying these mechanisms at multiple levels of the CNS, research to date has been limited to inferential univariate techniques that cannot fully unveil the intricacies of the underlying neural states. To address this, we propose to go beyond traditional analyses and instead use a data-driven multivariate approach leveraging the dynamic content of cerebro-spinal signals using innovation-driven coactivation patterns (iCAPs). We demonstrate the relevance of this approach in a simultaneous brain-spinal cord fMRI dataset acquired during motor sequence learning (MSL), to highlight how large-scale CNS plasticity underpins rapid improvements in early skill acquisition and slower consolidation after extended practice. Specifically, we uncovered cortical, subcortical and spinal functional networks, which were used to decode the different stages of learning with a high accuracy and, thus, delineate meaningful cerebro-spinal signatures of learning progression. Our results provide compelling evidence that the dynamics of neural signals, paired with a data-driven approach, can be used to disentangle the modular organization of the CNS. While we outline the potential of this framework to probe the neural correlates of motor learning, its versatility makes it broadly applicable to explore the functioning of cerebro-spinal networks in other experimental or pathological conditions.

Error-related brain state analysis using electroencephalography in conjunction with functional near-infrared spectroscopy during a complex surgical motor task

Error-based learning is one of the basic skill acquisition mechanisms that can be modeled as a perception-action system and investigated based on brain-behavior analysis during skill training. Here, the error-related chain of mental processes is postulated to depend on the skill level leading to a difference in the contextual switching of the brain states on error commission. Therefore, the objective of this paper was to compare error-related brain states, measured with multi-modal portable brain imaging, between experts and novices during the Fundamentals of Laparoscopic Surgery (FLS) "suturing and intracorporeal knot-tying" task (FLS complex task)-the most difficult among the five psychomotor FLS tasks. The multi-modal portable brain imaging combined functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) for brain-behavior analysis in thirteen right-handed novice medical students and nine expert surgeons. The brain state changes were defined by quasi-stable EEG scalp topography (called microstates) changes using 32-channel EEG data acquired at 250 Hz. Six microstate prototypes were identified from the combined EEG data from experts and novices during the FLS complex task that explained 77.14% of the global variance. Analysis of variance (ANOVA) found that the proportion of the total time spent in different microstates during the 10-s error epoch was significantly affected by the skill level (p < 0.01), the microstate type (p < 0.01), and the interaction between the skill level and the microstate type (p < 0.01). Brain activation based on the slower oxyhemoglobin (HbO) changes corresponding to the EEG band power (1-40 Hz) changes were found using the regularized temporally embedded Canonical Correlation Analysis of the simultaneously acquired fNIRS-EEG signals. The HbO signal from the overlying the left inferior frontal gyrus-opercular part, left superior frontal gyrus-medial orbital, left postcentral gyrus, left superior temporal gyrus, right superior frontal gyrus-medial orbital cortical areas showed significant (p < 0.05) difference between experts and novices in the 10-s error epoch. We conclude that the difference in the error-related chain of mental processes was the activation of cognitive top-down attention-related brain areas, including left dorsolateral prefrontal/frontal eye field and left frontopolar brain regions, along with a 'focusing' effect of global suppression of hemodynamic activation in the experts, while the novices had a widespread stimulus(error)-driven hemodynamic activation without the 'focusing' effect.

Directed information flow during laparoscopic surgical skill acquisition dissociated skill level and medical simulation technology

Virtual reality (VR) simulator has emerged as a laparoscopic surgical skill training tool that needs validation using brain-behavior analysis. Therefore, brain network and skilled behavior relationship were evaluated using functional near-infrared spectroscopy (fNIRS) from seven experienced right-handed surgeons and six right-handed medical students during the performance of Fundamentals of Laparoscopic Surgery (FLS) pattern of cutting tasks in a physical and a VR simulator. Multiple regression and path analysis (MRPA) found that the FLS performance score was statistically significantly related to the interregional directed functional connectivity from the right prefrontal cortex to the supplementary motor area with F (2, 114) = 9, p < 0.001, and R² = 0.136. Additionally, a two-way multivariate analysis of variance (MANOVA) found a statistically significant effect of the simulator technology on the interregional directed functional connectivity from the right prefrontal cortex to the left primary motor cortex (F (1, 15) = 6.002, p = 0.027; partial η² = 0.286) that can be related to differential right-lateralized executive control of attention. Then, MRPA found that the coefficient of variation (CoV) of the FLS performance score was statistically significantly associated with the CoV of the interregionally directed functional connectivity from the right primary motor cortex to the left primary motor cortex and the left primary motor cortex to the left prefrontal cortex with F (2, 22) = 3.912, p = 0.035, and R² = 0.262. This highlighted the importance of the efference copy information from the motor cortices to the prefrontal cortex for postulated left-lateralized perceptual decision-making to reduce behavioral variability.

EXPRESS: Perceptual scale expansion: A natural design for improving the precision of motor control

Space perception is systematically biased. Few theories of spatial bias address the possible functional advantages of mechanisms that produce spatial biases. The scale expansion hypothesis proposes that many spatial biases are due to the perceptual expansion of visual angles, which acts somewhat like a natural magnifying glass in vision. The present study examined the idea that visual expansion may improve motor precision (i.e., reduce motor variability) in movements when using closed-loop control but not when using open-loop control. Experiment 1 tested this idea in an online tracking task (closed-loop control), whereas Experiment 2 tested it in a fast-hitting task (open-loop control). The results were consistent with the hypothesis. To rule out the effect of the task difference (i.e., tracking vs. fast hitting), Experiment 3 examined the effect of visual expansion on the variability of motor performance in a line-reproduction task. The control type (closed-loop or open-loop) was manipulated by the form of visual feedback (online or offline). The results were again consistent with the present assumption. Taken together, the present data suggest that perceptual expansion in vision improves motor control precision when using closed-loop control (but not when using open-loop control), which supports the scale-expansion hypothesis. In addition, the present findings also improve our understanding of how visual error amplification affects motor control.

Spike Prediction on Primary Motor Cortex from Medial Prefrontal Cortex during Task Learning

OBJECTIVES

Brain-machine interfaces (BMIs) aim to help people with motor disabilities by interpreting brain signals into motor intentions using advanced signal processing methods. Currently, BMI users require intensive training to perform a pre-defined task, not to mention learning a new task. Thus, it is essential to understand neural information pathways among the cortical areas in task learning to provide principles for designing BMIs with learning abilities. We propose to investigate the relationship between the medial prefrontal cortex (mPFC) and primary motor cortex (M1), which are actively involved in motor control and task learning, and show how information is conveyed in spikes between the two regions on a single-trial basis by computational models.

APPROACH

We are interested in modeling the functional relationship between mPFC and M1 activities during task learning. Six Sprague Dawley rats were trained to learn a new behavioral task. Neural spike data was recorded from mPFC and M1 during learning. We then implement the generalized linear model, the second-order generalized Laguerre-Volterra model, and the staged point-process model to predict M1 spikes from mPFC spikes across multiple days during task learning. The prediction performance is compared across different models or learning stages to reveal the relationship between mPFC and M1 spike activities.

MAIN RESULTS

We find that M1 neural spikes can be well predicted from mPFC spikes on the single-trial level, which indicates a highly correlated relationship between mPFC and M1 activities during task learning. By comparing the performance across models, we find that models with higher nonlinear capacity perform significantly better than linear models. This indicates that predicting M1 activity from mPFC activity requires the model to consider higher-order nonlinear interactions beyond pairwise interactions. We also find that the correlation coefficient between the mPFC and M1 spikes increases during task learning. The spike prediction models perform the best when the subjects become well trained on the new task compared with the early and middle stages. The results suggest that the co-activation between mPFC and M1 activities evolves during task learning, and becomes stronger as subjects become well trained.

SIGNIFICANCE

This study demonstrates that the dynamic patterns of M1 spikes can be predicted from mPFC spikes during task learning, and this will further help in the design of adaptive BMI decoders for task learning.

Hierarchical Reinforcement Learning, Sequential Behavior, and the Dorsal Frontostriatal System

To effectively behave within ever-changing environments, biological agents must learn and act at varying hierarchical levels such that a complex task may be broken down into more tractable subtasks. Hierarchical reinforcement learning (HRL) is a computational framework that provides an understanding of this process by combining sequential actions into one temporally extended unit called an option. However, there are still open questions within the HRL framework, including how options are formed and how HRL mechanisms might be realized within the brain. In this review, we propose that the existing human motor sequence literature can aid in understanding both of these questions. We give specific emphasis to visuomotor sequence learning tasks such as the discrete sequence production task and the M × N (M steps × N sets) task to understand how hierarchical learning and behavior manifest across sequential action tasks as well as how the dorsal cortical-subcortical circuitry could support this kind of behavior. This review highlights how motor chunks within a motor sequence can function as HRL options. Furthermore, we aim to merge findings from motor sequence literature with reinforcement learning perspectives to inform experimental design in each respective subfield.

Correlations between Hand Dexterity and Bimanual Coordination on the Activities of Daily Living in Older Adults with Mild Cognitive Impairment

Background/Aims

Many motor impairments are present in older adults with cognitive decline. One of them is the impairment of hand dexterity and bimanual coordination that result in poor functional ability in the activities of daily living (ADL). This study investigated the effects of hand dexterity and bimanual coordination declination on the sub-domains of ADL in older adults with mild cognitive impairment (MCI).

Methods

Thirty-one senior individuals with MCI were recruited in this study. The Purdue Pegboard Test was used to measure hand dexterity, and bimanual coordination was assessed by the continuous circle-drawing task. Their ADL were assessed with the General Activity Daily Living questionnaire.

Results

The correlations analysis showed an association between the dominant hand and bimanual dexterity with the domestic domain of ADL and all conditions of hand dexterity with the complex domain of ADL. Moreover, the multiple regression analysis showed that the predictor of the greatest effect for domestic and complex domains was dominant hand dexterity.

Discussion/Conclusion

These results revealed that dominant hand dexterity strongly affected domestic and complex ADL in older adults with MCI. There were age-related changes regarding lateral asymmetrical motor reduction, especially in cognitive tasks. However, complex tasks involving cognitive function may need dominant, nondominant and bimanual hand dexterity.

Procedural Learning through Action Observation: Preliminary Evidence from Virtual Gardening Activity in Intellectual Disability

Intellectual disability (ID) compromises intellectual and adaptive functioning. People with an ID show difficulty with procedural skills, with loss of autonomy in daily life. From an embodiment perspective, observation of action promotes motor skill learning. Among promising technologies, virtual reality (VR) offers the possibility of engaging the sensorimotor system, thus, improving cognitive functions and adaptive capacities. Indeed, VR can be used as sensorimotor feedback, which enhances procedural learning. In the present study, fourteen subjects with an ID underwent progressive steps training combined with VR aimed at learning gardening procedures. All participants were trained twice a week for fourteen weeks (total 28 sessions). Participants were first recorded while sowing zucchini, then they were asked to observe a virtual video which showed the correct procedure. Next, they were presented with their previous recordings, and they were asked to pay attention and to comment on the errors made. At the end of the treatment, the results showed that all participants were able to correctly garden in a real environment. Interestingly, action observation facilitated, not only procedural skills, but also specific cognitive abilities. This evidence emphasizes, for the first time, that action observation combined with VR improves procedural learning in ID.

Interactive effects of incentive value and valence on the performance of discrete action sequences

Incentives can be used to increase motivation, leading to better learning and performance on skilled motor tasks. Prior work has shown that monetary punishments enhance on-line performance while equivalent monetary rewards enhance off-line skill retention. However, a large body of literature on loss aversion has shown that losses are treated as larger than equivalent gains. The divergence between the effects of punishments and reward on motor learning could be due to perceived differences in incentive value rather than valence per se. We test this hypothesis by manipulating incentive value and valence while participants trained to perform motor sequences. Consistent with our hypothesis, we found that large reward enhanced on-line performance but impaired the ability to retain the level of performance achieved during training. However, we also found that on-line performance was better with reward than punishment and that the effect of increasing incentive value was more linear with reward (small, medium, large) while the effect of value was more binary with punishment (large vs not large). These results suggest that there are differential effects of punishment and reward on motor learning and that these effects of valence are unlikely to be driven by differences in the subjective magnitude of gains and losses.

Association of short- and long-latency afferent inhibition with human behavior

Transcranial magnetic stimulation (TMS) paired with nerve stimulation evokes short-latency afferent inhibition (SAI) and long-latency afferent inhibition (LAI), which are non-invasive assessments of the excitability of the sensorimotor system. SAI and LAI are abnormally reduced in various special populations in comparison to healthy controls. However, the relationship between afferent inhibition and human behavior remains unclear. The purpose of this review is to survey the current literature and synthesize observations and patterns that affect the interpretation of SAI and LAI in the context of human behavior. We discuss human behaviour across the motor and cognitive domains, and in special and control populations. Further, we discuss future considerations for research in this field and the potential for clinical applications. By understanding how human behavior is mediated by changes in SAI and LAI, this can allow us to better understand the neurophysiological underpinnings of human motor control.

The Forward Model: A Unifying Theory for the Role of the Cerebellum in Motor Control and Sense of Agency

For more than two decades, there has been converging evidence for an essential role of the cerebellum in non-motor functions. The cerebellum is not only important in learning and sensorimotor processes, some growing evidences show its implication in conditional learning and reward, which allows building our expectations about behavioral outcomes. More recent work has demonstrated that the cerebellum is also required for the sense of agency, a cognitive process that allows recognizing an action as our own, suggesting that the cerebellum might serve as an interface between sensorimotor function and cognition. A unifying model that would explain the role of the cerebellum across these processes has not been fully established. Nonetheless, an important heritage was given by the field of motor control: the forward model theory. This theory stipulates that movements are controlled based on the constant interactions between our organism and its environment through feedforward and feedback loops. Feedforward loops predict what is going to happen, while feedback loops confront the prediction with what happened so that we can react accordingly. From an anatomical point of view, the cerebellum is at an ideal location at the interface between the motor and sensory systems, as it is connected to cerebral, striatal, and spinal entities via parallel loops, so that it can link sensory and motor systems with cognitive processes. Recent findings showing that the cerebellum participates in building the sense of agency as a predictive and comparator system will be reviewed together with past work on motor control within the context of the forward model theory.

The Potential Role of Dopamine in Mediating Motor Function and Interpersonal Synchrony

Motor functions in general and motor planning in particular are crucial for our ability to synchronize our movements with those of others. To date, these co-occurring functions have been studied separately, and as yet it is unclear whether they share a common biological mechanism. Here, we synthesize disparate recent findings on motor functioning and interpersonal synchrony and propose that these two functions share a common neurobiological mechanism and adhere to the same principles of predictive coding. Critically, we describe the pivotal role of the dopaminergic system in modulating these two distinct functions. We present attention deficit hyperactivity disorder (ADHD) as an example of a disorder that involves the dopaminergic system and describe deficits in motor and interpersonal synchrony. Finally, we suggest possible directions for future studies emphasizing the role of dopamine modulation as a link between social and motor functioning.

Motor Learning, Neuroplasticity, and Strength and Skill Training: Moving From Compensation to Retraining in Behavioral Management of Dysphagia

Purpose Learning a motor skill and regaining a motor skill after it is lost are key tenets to the field of speech-language pathology. Motor learning and relearning have many theoretical underpinnings that serve as a foundation for our clinical practice. This review article applies selective motor learning theories and principles to feeding and swallowing across the life span. Conclusion In reviewing these theoretical fundamentals, clinical exemplars surrounding the roles of strength, skill, experience, compensation, and retraining, and their influence on motor learning and plasticity in regard to swallowing/feeding skills throughout the life span are discussed.

A Proposed Postural Control Theory Synthesizing Optimal Feedback Control Theory, Postural Motor Learning, and Cerebellar Supervision Learning

Multiple theories regarding motor learning and postural control development aim to explain how the central nervous system (CNS) acquires, adjusts, and learns postural behaviors. However, few theories of postural motor development and learning propose possible neurophysiologic correlates to support their assumptions. Evidence from behavioral and computational models support the cerebellum's role in supervising motor learning through the production of forward internal models, corrected by sensory prediction errors. Optimal Feedback Control Theory (OFCT) states that the CNS learns new behaviors by minimizing the cost of multi-joint movements that attain a task goal. By synthesizing principles of the OFCT, postural sway characteristics, and cerebellar anatomy and its internal models, we propose an integrated learning model in which cerebellar supervision of postural control is governed by movement cost functions.

Cerebellar alterations in cannabis users: A systematic review

Cannabis is the most used illicit substance in the world. As many countries are moving towards decriminalization, it is crucial to determine whether and how cannabis use affects human brain and behavior. The role of the cerebellum in cognition, emotion, learning, and addiction is increasingly recognized. Because of its high density in CB1 receptors, it is expected to be highly affected by cannabis use. The aim of this systematic review is to investigate how cannabis use affects cerebellar structure and function, as well as cerebellar-dependent behavioral tasks. Three databases were searched for peer-reviewed literature published until March 2018. We included studies that focused on cannabis effects on cerebellar structure, function, or cerebellar-dependent behavioral tasks. A total of 348 unique records were screened, and 40 studies were included in the qualitative synthesis. The most consistent findings include (1) increases in cerebellar gray matter volume after chronic cannabis use, (2) alteration of cerebellar resting state activity after acute or chronic use, and (3) deficits in memory, decision making, and associative learning. Age of onset and higher exposure to cannabis use were frequently associated with increased cannabis-induced alterations. Chronic cannabis use is associated with alterations in cerebellar structure and function, as well as with deficits in behavioral paradigms that involve the cerebellum (eg, eyeblink conditioning, memory, and decision making). Future studies should consider tobacco as confounding factor and use standardized methods for assessing cannabis use. Paradigms exploring the functional activity of the cerebellum may prove useful as monitoring tools of cannabis-induced impairment.

Age-related deficits in bilateral motor synergies and force coordination

Background

Ageing may cause impairments in executing bilateral movement control. This study investigated age-related changes in interlimb force coordination across multiple trials by quantifying bilateral motor synergies based on the uncontrolled manifold hypothesis. Participants completed the trials with and without visual feedback.

Methods

Twenty healthy individuals (10 older adults and 10 young adults) performed 12 isometric force control trials for the two vision conditions at 5% of maximal voluntary contraction. All dependent variables were analyzed in two-way mixed model (Group × Vision Condition; 2 × 2) ANOVAs with repeated measures on the last factor.

Results

The analyses revealed that older adults had greater mean force produced by two hands in both vision conditions (i.e., yes and no visual feedback). Across both vision conditions, the older adult group showed greater asymmetrical force variability (i.e., standard deviation of non-dominant hand > standard deviation of dominant hand) and revealed more positive correlation coefficients between forces produced by two hands as compared with the young adult group. Finally, an index of bilateral motor synergies was significantly greater in young adults than older adults when visual feedback was available.

Conclusion

The current findings indicate that deficits in interlimb force coordination across multiple trials appeared in older adults.

Early stages of sensorimotor map acquisition: learning with free exploration, without active movement or global structure

One of the puzzles of learning to talk or play a musical instrument is how we learn which movement produces a particular sound: an audiomotor map. The initial stages of map acquisition can be studied by having participants learn arm movements to auditory targets. The key question is what mechanism drives this early learning. Three learning processes from previous literature were tested: map learning may rely on active motor outflow (target), on error correction, and on the correspondence between sensory and motor distances (i.e., that similar movements map to similar sounds). Alternatively, we hypothesized that map learning can proceed without these. Participants made movements that were mapped to sounds in a number of different conditions that each precluded one of the potential learning processes. We tested whether map learning relies on assumptions about topological continuity by exposing participants to a permuted map that did not preserve distances in auditory and motor space. Further groups were tested who passively experienced the targets, kinematic trajectories produced by a robot arm, and auditory feedback as a yoked active participant (hence without active motor outflow). Another group made movements without receiving targets (thus without experiencing errors). In each case we observed substantial learning, therefore none of the three hypothesized processes is required for learning. Instead early map acquisition can occur with free exploration without target error correction, is based on sensory-to-sensory correspondences, and possible even for discontinuous maps. The findings are consistent with the idea that early sensorimotor map formation can involve instance-specific learning.NEW & NOTEWORTHY This study tested learning of novel sensorimotor maps in a variety of unusual circumstances, including learning a mapping that was permuted in such as way that it fragmented the sensorimotor workspace into discontinuous parts, thus not preserving sensory and motor topology. Participants could learn this mapping, and they could learn without motor outflow or targets. These results point to a robust learning mechanism building on individual instances, inspired from machine learning literature.

Is there a prediction network? Meta-analytic evidence for a cortical-subcortical network likely subserving prediction

Predictive coding is an increasingly influential and ambitious concept in neuroscience viewing the brain as a 'hypothesis testing machine' that constantly strives to minimize prediction error, the gap between its predictions and the actual sensory input. Despite the invaluable contribution of this framework to the formulation of brain function, its neuroanatomical foundations have not been fully defined. To address this gap, we conducted activation likelihood estimation (ALE) meta-analysis of 39 neuroimaging studies of three functional domains (action perception, language and music) inherently involving prediction. The ALE analysis revealed a widely distributed brain network encompassing regions within the inferior and middle frontal gyri, anterior insula, premotor cortex, pre-supplementary motor area, temporoparietal junction, striatum, thalamus/subthalamus and the cerebellum. This network is proposed to subserve domain-general prediction and its relevance to motor control, attention, implicit learning and social cognition is discussed in light of the predictive coding scheme. Better understanding of the presented network may help advance treatments of neuropsychiatric conditions related to aberrant prediction processing and promote cognitive enhancement in healthy individuals.

Dissociative effects of normative feedback on motor automaticity and motor accuracy in learning an arm movement sequence

Within a pre-post-design, we scrutinized the effects of normative augmented feedback with positive and negative valence on learning motor accuracy, consistency as well as automaticity by means of a dual-task paradigm. Forty-two healthy physical education students were instructed to produce an arm-movement sequence as precisely as possible with regard to three spatial reversal points within a time limit of 1200 ms. Twenty-eight practiced an elbow-extension-flexion-sequence (690 trials) and 14 participants were tested as a control group without feedback practice. Valence of normative feedback was systematically manipulated by means of reference lines in a visual feedback display. The reference lines indicated performance of a putative peer-group either to be superior (negative valence, Normative-Negative-Group) or inferior (positive valence, Normative-Positive-Group) to participants' actual performance. As a result, dual-task costs (n-back error) significantly decreased solely in the Normative-Positive-Group, p = .003, η²_p = .51, but in no other group. Surprisingly, the mean absolute error for the motor task significantly decreased (i.e., precision increased) only in the Normative-Negative-Group with a large effect size, but in none of the other groups. Motor consistency was not significantly affected by the valence of normative feedback. According to the hypotheses of error-provoked attentional control, positive feedback-valence appears to enhance skill automatization, while - unexpectedly - only negative feedback-valence seems to enhance movement precision, which may be explained by effects of feedback valence on the learners aspiration level.

Putting the "Sensory" Into Sensorimotor Control: The Role of Sensorimotor Integration in Goal-Directed Hand Movements After Stroke

Integration of sensory and motor information is one-step, among others, that underlies the successful production of goal-directed hand movements necessary for interacting with our environment. Disruption of sensorimotor integration is prevalent in many neurologic disorders, including stroke. In most stroke survivors, persistent paresis of the hand reduces function and overall quality of life. Current rehabilitative methods are based on neuroplastic principles to promote motor learning that focuses on regaining motor function lost due to paresis, but the sensory contributions to motor control and learning are often overlooked and currently understudied. There is a need to evaluate and understand the contribution of both sensory and motor function in the rehabilitation of skilled hand movements after stroke. Here, we will highlight the importance of integration of sensory and motor information to produce skilled hand movements in healthy individuals and individuals after stroke. We will then discuss how compromised sensorimotor integration influences relearning of skilled hand movements after stroke. Finally, we will propose an approach to target sensorimotor integration through manipulation of sensory input and motor output that may have therapeutic implications.

Neural Signatures of Prediction Errors in a Decision-Making Task Are Modulated by Action Execution Failures

Decisions must be implemented through actions, and actions are prone to error. As such, when an expected outcome is not obtained, an individual should be sensitive to not only whether the choice itself was suboptimal but also whether the action required to indicate that choice was executed successfully. The intelligent assignment of credit to action execution versus action selection has clear ecological utility for the learner. To explore this, we used a modified version of a classic reinforcement learning task in which feedback indicated whether negative prediction errors were, or were not, associated with execution errors. Using fMRI, we asked if prediction error computations in the human striatum, a key substrate in reinforcement learning and decision making, are modulated when a failure in action execution results in the negative outcome. Participants were more tolerant of non-rewarded outcomes when these resulted from execution errors versus when execution was successful, but reward was withheld. Consistent with this behavior, a model-driven analysis of neural activity revealed an attenuation of the signal associated with negative reward prediction errors in the striatum following execution failures. These results converge with other lines of evidence suggesting that prediction errors in the mesostriatal dopamine system integrate high-level information during the evaluation of instantaneous reward outcomes.

The role of the practice order: A systematic review about contextual interference in children

Aim

We aimed to identify and evaluate the quality and evidence of the motor learning literature about intervention studies regarding the contextual interference (CI) effect (blocked vs. random practice order) in children with brain lesions and typically developing (TD) children.

Method

Eight databases (Cinahl, Cochrane, Embase, PubMed, Pedro, PsycINFO, Scopus and Web of Knowledge) were searched systematically with predefined search terms. Controlled studies examining the CI effect in children (with brain lesions or TD) were included. Evidence level, conduct quality, and risk of bias were evaluated by two authors independently. A best evidence synthesis was performed.

Results

Twenty-five papers evaluating TD children were included. One of these studies also assessed children with cerebral palsy. Evidence levels were I, II, or III. Conduct quality was low and the risk of bias high, due to methodological issues in the study designs or poor description thereof. Best evidence synthesis showed mainly no or conflicting evidence. Single tasks showed limited to moderate evidence supporting the CI effect in TD children.

Conclusion

There is a severe limitation of good-quality evidence about the CI effect in children who practice different tasks in one session, especially in children with brain lesions.

Force Analysis and Evaluation of a Pelvic Support Walking Robot with Joint Compliance

The force analysis of a pelvic support walking robot with joint compliance is discussed in this paper. During gait training, pelvic motions of hemiplegic patients may be excessively large or out of control; however, restriction of pelvic motions is not likely to facilitate successful rehabilitation. A robot-assisted pelvic balance trainer (RAPBT) is proposed to help patients control the range of motion via force field, and force analysis is necessary for the control of the compliant joints. Thus, kinematic model and static model are developed to derive the Jacobian and the relation between the interaction forces and the pelvic movements, respectively. Since the joint compliance is realized through a nontorsional spring, a conventional (linear) Jacobian method and a piecewise linear method are derived to relate the interaction forces with the pelvis movements. Three preliminary experiments are carried out to evaluate the effectiveness of the proposed methods and the feasibility of the RAPBT. The experiment results indicate that the piecewise linear method is effective in the calculation of the interaction forces. Gait with pelvic brace strongly resembles free overground walking and partly decreases motion range via force field. The findings of this research demonstrate that the pelvic brace with joint compliance may provide effective interventions.

Strength or Motor Control: What Matters in High-Functioning Stroke?

Background: The two primary motor impairments that hinder function after stroke are declines in strength and motor control. The impact of motor impairments on functional capacity may vary with the severity of stroke motor impairments. In this study, we focus on high-functioning stroke individuals who experience mild to moderate motor impairments and often resume prior activities or return to work. These tasks require the ability to move independently, placing high demands on their functional mobility. Therefore, the purpose of this study was to quantify impairments in strength and motor control and their contribution to functional mobility in high-functioning stroke.

Methods:Twenty-one high-functioning stroke individuals (Fugl Meyer Lower Extremity Score = 28.67 ± 4.85; Functional Activity Index = 28.47 ± 7.04) and 21 age-matched healthy controls participated in this study. To examine motor impairments in strength and motor control, participants performed the following tasks with the paretic ankle (1) maximum voluntary contractions (MVC) and (2) visuomotor tracking of a sinusoidal trajectory. Strength was quantified as the maximum force produced during ankle plantarflexion and dorsiflexion. Motor control was quantified as (a) the accuracy and (b) variability of ankle movement during the visuomotor tracking task. For functional mobility, participants performed (1) overground walking for 7 meters and (2) simulated driving task. Functional mobility was determined by walking speed, stride length variability, and braking reaction time.

Results: Compared with the controls, the stroke group showed decreased plantarflexion strength, decreased accuracy, and increased variability of ankle movement. In addition, the stroke group demonstrated decreased walking speed, increased stride length variability, and increased braking reaction time. The multiple-linear regression model revealed that motor accuracy was a significant predictor of the walking speed and braking reaction time. Further, motor variability was a significant predictor of stride length variability. Finally, the dorsiflexion or plantarflexion strength did not predict walking speed, stride length variability or braking reaction time.

Conclusions: The impairments in motor control but not strength predict functional deficits in walking and driving in high-functioning stroke individuals. Therefore, rehabilitation interventions assessing and improving motor control will potentially enhance functional outcomes in high-functioning stroke survivors.

The impact of motor impairment on the processing of sensory information

Sensorimotor adaptation is driven by mismatch errors between desired movements and actual movement outcomes. A mismatch error can be minimized by adjusting movements or by altering the interpretation of sensory information. While the effect of mismatch errors on the motor system has received much attention, the contribution of somatosensory feedback, particularly the sensory-motor interplay in the process of adaptation, remains poorly understood. Our study analyzes the impact of peripheral deefferentation on the plasticity of the brain networks responsible for sensory-motor adaptation, focusing particularly on changes in the processing of somatosensory information. For this aim, task-based and resting-state functional MRI was performed on 24 patients in the acute state of a left-sided idiopathic peripheral facial nerve palsy. The functional connectivity of cortical and subcortical networks was analyzed and compared to a healthy control group. We found a strong involvement of the somatosensory system and the thalamus in the adaptation process following an acute peripheral deefferentation. The investigated network shows the principal pattern of a reduced connectivity between cortical areas, while the connectivity to subcortical areas (the basal ganglia and the thalamus) is increased. We suggest that the increased connectivity between the subcortical and cortical structures indicates an active sensory-motor adaptation process. We further hypothesize that the decreased functional connectivity at the cortical level reflects an unsuccessful sensorimotor adaptation process due to the inability to solve the somatosensory-motor mismatch. These results extend our understanding of the somatosensory-motor interaction in response to a mismatch signal and highlight the importance of the thalamus in this process.

Motor Planning Error: Toward Measuring Cognitive Frailty in Older Adults Using Wearables

Practical tools which can be quickly administered are needed for measuring subtle changes in cognitive–motor performance over time. Frailty together with cognitive impairment, or ‘cognitive frailty’, are shown to be strong and independent predictors of cognitive decline over time. We have developed an interactive instrumented trail-making task (iTMT) platform, which allows quantification of motor planning error (MPE) through a series of ankle reaching tasks. In this study, we examined the accuracy of MPE in identifying cognitive frailty in older adults. Thirty-two older adults (age = 77.3 ± 9.1 years, body-mass-index = 25.3 ± 4.7 kg/m², female = 38%) were recruited. Using either the Mini-Mental State Examination or Montreal Cognitive Assessment (MoCA), 16 subjects were classified as cognitive-intact and 16 were classified as cognitive-impaired. In addition, 12 young-healthy subjects (age = 26.0 ± 5.2 years, body-mass-index = 25.3 ± 3.9 kg/m², female = 33%) were recruited to establish a healthy benchmark. Subjects completed the iTMT, using an ankle-worn sensor, which transforms ankle motion into navigation of a computer cursor. The iTMT task included reaching five indexed target circles (including numbers 1-to-3 and letters A&B placed in random order) on the computer-screen by moving the ankle-joint while standing. The ankle-sensor quantifies MPE through analysis of the pattern of ankle velocity. MPE was defined as percentage of time deviation between subject’s maximum ankle velocity and the optimal maximum ankle velocity, which is halfway through the reaching pathway. Data from gait tests, including single task and dual task walking, were also collected to determine cognitive–motor performance. The average MPE in young-healthy, elderly cognitive-intact, and elderly cognitive-impaired groups was 11.1 ± 5.7%, 20.3 ± 9.6%, and 34.1 ± 4.2% (p < 0.001), respectively. Large effect sizes (Cohen’s d = 1.17–4.56) were observed for discriminating between groups using MPE. Significant correlations were observed between the MPE and MoCA score (r = −0.670, p < 0.001) as well as between the MPE and dual task stride velocity (r = −0.584, p < 0.001). This study demonstrated feasibility and efficacy of estimating MPE from a practical wearable platform with promising results in identifying cognitive–motor impairment and potential application in assessing cognitive frailty. The proposed platform could be also used as an alternative to dual task walking test, where gait assessment may not be practical. Future studies need to confirm these observations in larger samples.

Contextual interference during adaptation to asymmetric split-belt treadmill walking results in transfer of unique gait mechanics

When humans make errors in stepping during walking due to a perturbation, they may adapt their gait as a way to correct for discrepancies between predicted and actual sensory feedback. This study sought to determine if increased contextual interference during acquisition of a novel asymmetric gait pattern would change lower-limb mechanical strategies generalized to different walking contexts. Such knowledge could help to clarify the role of contextual interference in locomotor adaptation, and demonstrate potential use in future gait rehabilitation paradigms. One belt on a split-belt treadmill was driven at a constant velocity while the other was driven at changing velocities according to one of three practice paradigms: serial, random blocked, or random training. Subjects returned to complete one of two different transfer tests. Results indicate that during acquisition, random practice requires unique gait mechanics to adapt to a challenging walking environment. Also, results from one transfer test close to that of the acquisition experience did not seem to demonstrate any contextual interference effect. Finally, random blocked practice resulted in highly unique changes in step length symmetry on a second, more challenging, transfer test. This perhaps indicates that a moderate level of contextual interference causes unique locomotor generalization strategies.

Summary: Specific biomechanical gait adaptations occur as a result of variance of stepping errors during walking. Humans optimize a novel gait pattern based on different levels of error variance.

The Effects of Coding Schemes on Vibrotactile Biofeedback for Dynamic Balance Training in Parkinson's Disease and Healthy Elderly Individuals

Coding scheme for earlier versions of vibrotactile biofeedback systems for balance-related applications was primarily binary in nature, either on or off at a given threshold (range of postural tilt), making it unable to convey information about error magnitude. The purpose of this paper was to explore the effects of two coding schemes (binary versus continuous) for vibrotactile biofeedback during dynamic weight-shifting exercises that are common physical therapists' recommended balance exercises used in clinical settings. Nine individuals with idiopathic Parkinson's disease and nine healthy elderly individuals participated in this paper. All participants performed dynamic weight-shifting exercises assisted with either the binary or continuous vibrotactile biofeedback delivered using with vibrating actuators (tactors) in either the anterior-posterior or medial-lateral direction. Participants' limits of stability at pre and post exercises were compared to evaluate the effects of the exercises on their range of motion. The continuous coding scheme produced significantly better performance than the binary scheme when both groups were performing dynamic weight-shifting balance exercises with assistive vibrotactile biofeedback. The results have implications in terms of maximizing the effects of error-driven motor learning and increasing performance on balance rehabilitation training combined with vibrotactile biofeedback.

The effectiveness of robotic training depends on motor task characteristics

Previous research suggests that the effectiveness of robotic training depends on the motor task to be learned. However, it is still an open question which specific task's characteristics influence the efficacy of error-modulating training strategies. Motor tasks can be classified based on the time characteristics of the task, in particular the task's duration (discrete vs. continuous). Continuous tasks require movements without distinct beginning or end. Discrete tasks require fast movements that include well-defined postures at the beginning and the end. We developed two games, one that requires a continuous movement-a tracking task-and one that requires discrete movements-a fast reaching task. We conducted an experiment with thirty healthy subjects to evaluate the effectiveness of three error-modulating training strategies-no guidance, error amplification (i.e., repulsive forces proportional to errors) and haptic guidance-on self-reported motivation and learning of the continuous and discrete games. Training with error amplification resulted in better motor learning than haptic guidance, besides the fact that error amplification reduced subjects' interest/enjoyment and perceived competence during training. Only subjects trained with error amplification improved their performance after training the discrete game. In fact, subjects trained without guidance improved the performance in the continuous game significantly more than in the discrete game, probably because the continuous task required greater attentional levels. Error-amplifying training strategies have a great potential to provoke better motor learning in continuous and discrete tasks. However, their long-lasting negative effects on motivation might limit their applicability in intense neurorehabilitation programs.

The Influence of Guided Error-Based Learning on Motor Skills Self-Efficacy and Achievement

The authors investigated the role of errors in motor skills teaching, specifically the influence of errors on skills self-efficacy and achievement. The participants were 75 undergraduate students enrolled in pétanque courses. The experimental group (guided error-based learning, n = 37) received a 6-week period of instruction based on the students' errors, whereas the control group (correct motion instruction, n = 38) received a 6-week period of instruction emphasizing correct motor skills. The experimental group had significantly higher scores in motor skills self-efficacy and outcomes than did the control group. Novices' errors reflect their schema in motor skills learning, which provides a basis for instructors to implement student-centered instruction and to facilitate the learning process. Guided error-based learning can effectively enhance beginners' skills self-efficacy and achievement in precision sports such as pétanque.

Structural Learning in a Visuomotor Adaptation Task Is Explicitly Accessible

Structural learning is a phenomenon characterized by faster learning in a new situation that shares features of previously experienced situations. One prominent example within the sensorimotor domain is that human participants are faster to counter a novel rotation following experience with a set of variable visuomotor rotations. This form of learning is thought to occur implicitly through the updating of an internal forward model, which predicts the sensory consequences of motor commands. However, recent work has shown that much of rotation learning occurs through an explicitly accessible process, such as movement re-aiming. We sought to determine if structural learning in a visuomotor rotation task is purely implicit (e.g., driven by an internal model) or explicitly accessible (i.e., re-aiming). We found that participants exhibited structural learning: following training with a variable set of rotations, they more quickly learned a novel rotation. This benefit was entirely conferred by the explicit re-aiming of movements. Implicit learning offered little to no contribution. Next, we investigated the specificity of this learning benefit by exposing participants to a novel perturbation drawn from a statistical structure either congruent or incongruent with their prior experience. We found that participants who experienced congruent training and test phase structure (i.e., rotations to rotation) learned more quickly than participants exposed to incongruent training and test phase structure (i.e., gains to rotation) and a control group. These results suggest that structural learning in a visuomotor rotation task is specific to previously experienced statistical structure and expressed via explicit re-aiming of movements.

Force Irregularity Following Maximal Effort: The After-Peak Reduction

Irregularities in force output are present throughout human movement and can impair task performance. We investigated the presence of a large force discontinuity (after-peak reduction, APR) that appeared immediately following peak in maximal effort ramp contractions performed with the thumb adductor and ankle dorsiflexor muscles in 25 young adult participants (76% males, 24% females; M age 24.4 years, SD = 7.1). The after-peak reduction displayed similar parameters in both muscle groups with comparable drops in force during the after-peak reduction minima (thumb adductor: 27.5 ± 7.5% maximal voluntary contraction; ankle dorsiflexor: 25.8 ± 6.2% maximal voluntary contraction). A trend for the presence of fewer after-peak reductions with successive ramp trials was observed, suggesting a learning effect. Further investigation should explore underlying neural mechanisms contributing to the after-peak reduction.

The effect of 'device-in-charge' versus 'patient-in-charge' support during robotic gait training on walking ability and balance in chronic stroke survivors: A systematic review

This review describes the effects of two control strategies - used in robotic gait-training devices for chronic stroke survivors - on gait speed, endurance and balance. Control strategies are classified as 'patient-in-charge support', where the device 'empowers' the patient, and 'device-in-charge support', where the device imposes a pre-defined movement trajectory on the patient. Studies were collected up to 24 June 2015 and were included if they presented robotic gait training in chronic stroke survivors and used outcome measures that were indexed by the International Classification of Functioning, Disability and Health. In total, 11 articles were included. Methodological quality was assessed using the PEDro scale. Outcome measures were walking speed, endurance and balance. Pooled mean differences between pre and post measurements were calculated. No differences were found between studies that used device-in-charge support and patient-in-charge support. Training effects were small for both groups of control strategies, and none were considered to be clinically relevant as defined by the Minimal Clinically Important Difference. However, an important confounder is the short training duration among all included studies. As control strategies in robotic gait training are rapidly evolving, future research should take the recommendations that are made in this review into account.

Robot assistance of motor learning: A neuro-cognitive perspective

The last several years have seen a number of approaches to robot assistance of motor learning. Experimental studies have produced a range of findings from beneficial effects through null-effects to detrimental effects of robot assistance. In this review we seek an answer to the question under which conditions which outcomes should be expected. For this purpose we derive tentative predictions based on a classification of learning tasks in terms of the products of learning, the mechanisms involved, and the modulation of these mechanisms by robot assistance. Consistent with these predictions, the learning of dynamic features of trajectories is facilitated and the learning of kinematic and dynamic transformations is impeded by robotic guidance, whereas the learning of dynamic transformations can profit from robot assistance with error-amplifying forces. Deviating from the predictions, learning of spatial features of trajectories is impeded by haptic guidance, but can be facilitated by divergent force fields. The deviations point to the existence of additional effects of robot assistance beyond the modulation of learning mechanisms, e.g., the induction of a passive role of the motor system during practice with haptic guidance.