The neural correlates of learned motor acuity

Corticospinal and corticoreticulospinal projections benefit motor behaviors in chronic stroke

After corticospinal tract (CST) stroke, several motor deficits in the upper extremity (UE) emerge, including diminished muscle strength, motor control, and muscle individuation. Both the ipsilesional CST and contralesional corticoreticulospinal tract (CReST) innervate the paretic UE and may have different innervation patterns for the proximal and distal UE segments. These patterns may underpin distinct pathway relationships to separable motor behaviors. In this cross-sectional study of 15 chronic stroke patients and 28 healthy subjects, we examined two key questions: (1) whether segmental motor behaviors differentially relate to ipsilesional CST and contralesional CReST projection strengths, and (2) whether motor behaviors segmentally differ in the paretic UE. We measured strength, motor control, and muscle individuation in a proximal (biceps, BIC) and distal muscle (first dorsal interosseous, FDI) of the paretic UE. We measured the projection strengths of the ipsilesional CST and contralesional CReST to these muscles using transcranial magnetic stimulation (TMS). Stroke subjects had abnormal motor control and muscle individuation despite strength comparable to healthy subjects. In stroke subjects, stronger ipsilesional CST projections were linked to superior motor control in both UE segments, whereas stronger contralesional CReST projections were linked to superior muscle strength and individuation in both UE segments. Notably, both pathways also shared associations with behaviors in the proximal segment. Motor control deficits were segmentally comparable, but muscle individuation was worse for distal motor performance. These results suggest that each pathway has specialized contributions to chronic motor behaviors but also work together, with varying levels of success in supporting chronic deficits.

Key points summary

Individuals with chronic stroke typically have deficits in strength, motor control, and muscle individuation in their paretic upper extremity (UE). It remains unclear how these altered behaviors relate to descending motor pathways and whether they differ by proximal and distal UE segment.In this study, we used transcranial magnetic stimulation (TMS) to examine projection strengths of the ipsilesional corticospinal tract (CST) and contralesional corticoreticulospinal tract (CReST) with respect to quantitated motor behaviors in chronic stroke.We found that stronger ipsilesional CST projections were associated with better motor control in both UE segments, whereas stronger contralesional CReST projections were associated with better strength and individuation in both UE segments. In addition, projections of both pathways shared associations with motor behaviors in the proximal UE segment.We also found that deficits in strength and motor control were comparable across UE segments, but muscle individuation was worse with controlled movement in the distal UE segment.These results suggest that the CST and CReST have specialized contributions to chronic motor behaviors and also work together, although with different degrees of efficacy.

Measuring and monitoring skill learning in closed-loop myoelectric hand prostheses using speed-accuracy tradeoffs

Objective.Closed-loop myoelectric prostheses, which combine supplementary sensory feedback and electromyography (EMG) based control, hold the potential to narrow the divide between natural and bionic hands. The use of these devices, however, requires dedicated training. Therefore, it is crucial to develop methods that quantify how users acquire skilled control over their prostheses to effectively monitor skill progression and inform the development of interfaces that optimize this process.Approach.Building on theories of skill learning in human motor control, we measured speed-accuracy tradeoff functions (SAFs) to comprehensively characterize learning-induced changes in skill-as opposed to merely tracking changes in task success across training-facilitated by a closed-loop interface that combined proportional control and EMG feedback. Sixteen healthy participants and one individual with a transradial limb loss participated in a three-day experiment where they were instructed to perform the box-and-blocks task using a timed force-matching paradigm at four specified speeds to reach two target force levels, such that the SAF could be determined.Main results.We found that the participants' accuracy increased in a similar way across all speeds we tested. Consequently, the shape of the SAF remained similar across days, at both force levels. Further, we observed that EMG feedback enabled participants to improve their motor execution in terms of reduced trial-by-trial variability, a hallmark of skilled behavior. We then fit a power law model of the SAF, and demonstrated how the model parameters could be used to identify and monitor changes in skill.Significance.We comprehensively characterized how an EMG feedback interface enabled skill acquisition, both at the level of task performance and movement execution. More generally, we believe that the proposed methods are effective for measuring and monitoring user skill progression in closed-loop prosthesis control.

Different Effect Sizes of Motor Skill Training Combined with Repetitive Transcranial versus Trans-Spinal Magnetic Stimulation in Healthy Subjects

Repetitive transcranial magnetic stimulation (rTMS) is used to enhance motor training (MT) performance. The use of rTMS is limited under certain conditions, such as after a stroke with severe damage to the corticospinal tract. This raises the question as to whether repetitive trans-spinal magnetic stimulation (rSMS) can also be used to improve MT. A direct comparison of the effect size between rTMS and rSMS on the same MT is still lacking. Before conducting the study in patients, we determined the effect sizes of different stimulation approaches combined with the same motor training in healthy subjects. Two experiments (E1 and E2) with 96 subjects investigated the effect size of combining magnetic stimulation with the same MT. In E1, high-frequency rTMS, rSMS, and spinal sham stimulation (sham-spinal) were applied once in combination with MT, while one group only received the same MT (without stimulation). In E2, rTMS, rSMS, and sham-spinal were applied in combination with MT over several days. In all subjects, motor tests and motor-evoked potentials were evaluated before and after the intervention period. rTMS had the greatest effect on MT, followed by rSMS and then sham-spinal. Daily stimulation resulted in additional training gains. This study suggests that rSMS increases excitability and also enhances MT performance. This current study provides a basis for further research to discover whether patients who cannot be treated effectively with rTMS would benefit from rSMS.

Neural correlates of fine motor grasping skills: Longitudinal insights into motor cortex activation using fNIRS

BACKGROUND

Motor learning is essential for performing specific tasks and progresses through distinct stages, including the rapid learning phase (initial skill acquisition), the consolidation phase (skill refinement), and the stable performance phase (skill mastery and maintenance). Understanding the cortical activation dynamics during these stages can guide targeted rehabilitation interventions.

METHODS

In this longitudinal randomized controlled trial, functional near-infrared spectroscopy was used to explore the temporal dynamics of cortical activation in hand-related motor learning. Thirty-one healthy right-handed individuals were randomly assigned to perform either easy or intricate motor tasks with their non-dominant hand over 10 days. We conducted 10 monitoring sessions to track cortical activation in the right hemisphere (according to lateralization principles, the primary hemisphere for motor control) and evaluated motor proficiency concurrently.

RESULTS

The study delineated three stages of nondominant hand motor learning: rapid learning (days 1 and 2), consolidation (days 3-7), and stable performance (days 8-10). There was a power-law enhancement of motor skills correlated with learning progression. Sustained activation was observed in the supplementary motor area (SMA) and parietal lobe (PL), whereas activation in the right primary motor cortex (M1R) and dorsolateral prefrontal cortex (PFCR) decreased. These cortical activation patterns exhibited a high correlation with the augmentation of motor proficiency.

CONCLUSIONS

The findings suggest that early rehabilitation interventions, such as transcranial magnetic stimulation and transcranial direct current stimulation (tDCS), could be optimally directed at M1 and PFC in the initial stages. In contrast, SMA and PL can be targeted throughout the motor learning process. This research illuminates the path for developing tailored motor rehabilitation interventions based on specific stages of motor learning.

NEW AND NOTEWORTHY

In an innovative approach, our study uniquely combines a longitudinal design with the robustness of generalized estimating equations (GEEs). With the synergy of functional near-infrared spectroscopy (fNIRS) and the Minnesota Manual Dexterity Test (MMDT) paradigm, we precisely trace the evolution of neural resources during complex, real-world fine-motor task learning. Centering on right-handed participants using their nondominant hand magnifies the intricacies of right hemisphere spatial motor processing. We unravel the brain's dynamic response throughout motor learning stages and its potent link to motor skill enhancement. Significantly, our data point toward the early-phase rehabilitation potential of TMS and transcranial direct current stimulation on the M1 and PFC regions. Concurrently, SMA and PL appear poised to benefit from ongoing interventions during the entire learning curve. Our findings carve a path for refined motor rehabilitation strategies, underscoring the importance of timely noninvasive brain stimulation treatments.

Plasticity-stability dynamics during post-training processing of learning

Learning continues beyond the end of training. Post-training learning is supported by changes in plasticity and stability in the brain during both wakefulness and sleep. However, the lack of a unified measure for assessing plasticity and stability dynamics during training and post-training periods has limited our understanding of how these dynamics shape learning. Focusing primarily on procedural learning, we integrate work using behavioral paradigms and a recently developed measure, the excitatory-to-inhibitory (E/I) ratio, to explore the delicate balance between plasticity and stability and its relationship to post-training learning. This reveals plasticity-stability cycles during both wakefulness and sleep that enhance learning and protect it from new learning during post-training processing.

Effects of an app-based sensorimotor training in promoting neuroplasticity and neuropsychological functioning in frailty: A randomized controlled trial

BACKGROUND

Loss of sensorimotor stimulation and maladaptive plastic changes of the brain may play a major role in problematic aging phenomena such as frailty. However, it is not clear if interventions specifically targeting neuroplasticity can reverse or slow the development of frailty.

OBJECTIVES

We compared the effect of a tablet-based neuroplasticity-oriented sensorimotor training (experimental group, EG) and a tablet-based relaxation training (control group, CG) on frailty and sensorimotor brain function.

METHODS

Interventions consisted of daily 30 min sessions distributed over 90 days. Assessments took place at baseline, after 60 days, and after 90 days. A total of N = 48 frail older adults (EG: n = 24; CG: n = 24) were assigned to the two groups and reassessed after 60 days. Primary outcomes included frailty phenotype (FP) and frailty index (FI). Sensorimotor brain activity was evaluated using functional magnetic resonance imaging and single-pulse transcranial magnetic stimulation.

RESULTS

After 60 days of training, both groups showed a reduction in the number of FP criteria (p < 0.001) with a trend towards a significant time-by-group interaction (p = 0.058) indicating a stronger reduction of frailty in the EG (p < 0.001) compared to the CG (p = 0.039). In addition, pain was significantly reduced in the EG but not the CG. No significant effects were found for measures of brain function.

DISCUSSION

We provided initial evidence that a neuroplasticity-oriented sensorimotor training could be beneficial in counteracting frailty as well as chronic pain. Further studies are needed to determine the potentially underlying neuroplastic mechanisms and the influence of plasticity-related biomarkers as well as their clinical significance.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03666039 (registered 11 September 2018).

Reflecting on what is "skill" in human motor skill learning

Humans have an exceptional ability to execute a variety of skilled movements. Researchers have been long interested in understanding behavioral and neurophysiological basis of human motor skill learning for advancing both fundamental neuroscientific knowledge and clinical outcomes. However, despite decades of work in this field there is a lack of consensus about what is meant by "skill" in skill learning. With an advent of various task paradigms testing human motor behavior and increasing heterogeneity in motor learning assessments methods, it is very crucial to identify key features of skill in order to avoid any ambiguity that may result in misinterpretation or over-generalization of findings, which could have serious implications for replication and translational research. In this review, we attempt to highlight the features of skill following a historical approach, considering the seminal work that led to the first definitions of skill and including some contemporary concepts emerging from human motor learning research. Overall, based on this literature, we emphasize that skill has some fundamental characteristics, such as- (i) optimal movement selection and execution, (ii) improved movement speed and accuracy, and (iii) reduced movement variability and error. These features of skill can emerge as a consequence of extensive practice/training/learning, thus resulting in an improved performance state beyond baseline levels. Finally we provide some examples of model tasks that can appropriately capture these features of skill, and conclude that any neuroscientific endeavor aimed at understanding the essence of skill in human motor skill learning should focus on these aspects.

Innovative Approaches and Therapies to Enhance Neuroplasticity and Promote Recovery in Patients With Neurological Disorders: A Narrative Review

Brain rehabilitation and recovery for people with neurological disorders, such as stroke, traumatic brain injury (TBI), and neurodegenerative diseases, depend mainly on neuroplasticity, the brain's capacity to restructure and adapt. This literature review aims to look into cutting-edge methods and treatments that support neuroplasticity and recovery in these groups. A thorough search of electronic databases revealed a wide range of research and papers investigating several neuroplasticity-targeting methods, such as cognitive training, physical activity, non-invasive brain stimulation, and pharmaceutical interventions. The results indicate that these therapies can control neuroplasticity and improve motor, mental, and sensory function. In addition, cutting-edge approaches, such as virtual reality (VR) and brain-computer interfaces (BCIs), promise to increase neuroplasticity and foster rehabilitation. However, many issues and restrictions still need to be resolved, including the demand for individualized treatments and the absence of defined standards. In conclusion, this review emphasizes the significance of neuroplasticity in brain rehabilitation. It identifies novel strategies and treatments that promise to enhance recovery in patients with neurological illnesses. Future studies should concentrate on improving these therapies and developing evidence-based standards to direct clinical practice and enhance outcomes for this vulnerable population.

Visuomotor skill learning in young adults with Down syndrome

BACKGROUND

Individuals with Down syndrome (DS) have impaired general motor skills compared to typically developed (TD) individuals.

AIMS

To gain knowledge on how young adults with DS learn and retain new motor skills.

METHODS AND PROCEDURES

A DS-group (mean age = 23.9 ± 3 years, N = 11), and an age-matched TD-group (mean age 22.8 ± 1.8, N = 14) were recruited. The participants practiced a visuomotor accuracy tracking task (VATT) in seven blocks (10.6 min). Online and offline effects of practice were assessed based on tests of motor performance at baseline immediate and 7-day retention.

OUTCOMES AND RESULTS

The TD-group performed better than the DS-group on all blocks (all P < 0.001). Both groups improved VATT-performance online from baseline to immediate retention, (all P < 0.001) with no difference in online effect between groups. A significant between-group difference was observed in the offline effect (∆TD - ∆DS, P = 0.04), as the DS-group's performance at 7-day retention was equal to their performance at immediate retention (∆DS, P > 0.05), whereas an offline decrease in performance was found in the TD-group (∆TD, P < 0.001).

CONCLUSIONS AND IMPLICATIONS

Visuomotor pinch force accuracy is lower for adults with DS compared to TD. However, adults with DS display significant online improvements in performance with motor practice similar to changes observed for TD. Additionally, adults with DS demonstrate offline consolidation following motor learning leading to significant retention effects.

To copy or not to copy? That is the question! From chimpanzees to the foundation of human technological culture

A prerequisite for copying innovative behaviour faithfully is the capacity of observers' brains, regarded as 'hierarchically mechanistic minds', to overcome cognitive 'surprisal' (see 2.), by maximising the evidence for their internal models, through active inference. Unlike modern humans, chimpanzees and other great apes show considerable limitations in their ability, or 'Zone of Bounded Surprisal', to overcome cognitive surprisal induced by innovative or unorthodox behaviour that rarely, therefore, is copied precisely or accurately. Most can copy adequately what is within their phenotypically habitual behavioural repertoire, in which technology plays scant part. Widespread intra- and intergenerational social transmission of complex technological innovations is not a hall-mark of great-ape taxa. 3 Ma, precursors of the genus Homo made stone artefacts, and stone-flaking likely was habitual before 2 Ma. After that time, early Homo erectus has left traces of technological innovations, though faithful copying of these and their intra- and intergenerational social transmission were rare before 1 Ma. This likely owed to a cerebral infrastructure of interconnected neuronal systems more limited than ours. Brains were smaller in size than ours, and cerebral neuronal systems ceased to develop when early Homo erectus attained full adult maturity by the mid-teen years, whereas its development continues until our mid-twenties nowadays. Pleistocene Homo underwent remarkable evolutionary adaptation of neurobiological propensities, and cerebral aspects are discussed that, it is proposed here, plausibly, were fundamental for faithful copying, which underpinned social transmission of technologies, cumulative learning, and culture. Here, observers' responses to an innovation are more important for ensuring its transmission than is an innovator's production of it, because, by themselves, the minimal cognitive prerequisites that are needed for encoding and assimilating innovations are insufficient for practical outcomes to accumulate and spread intra- and intergenerationally.

Dynamic motor practice improves movement accuracy, force control and leads to increased corticospinal excitability compared to isometric motor practice

The central nervous system has a remarkable ability to plan motor actions, to predict and monitor the sensory consequences during and following motor actions and integrate these into future actions. Numerous studies investigating human motor learning have employed tasks involving either force control during isometric contractions or position control during dynamic tasks. To our knowledge, it remains to be elucidated how motor practice with an emphasis on position control influences force control and vice versa. Furthermore, it remains unexplored whether these distinct types of motor practice are accompanied by differential effects on corticospinal excitability. In this study, we tested motor accuracy and effects of motor practice in a force or position control task allowing wrist flexions of the non-dominant hand in the absence of online visual feedback. For each trial, motor performance was quantified as errors (pixels) between the displayed target and the movement endpoint. In the main experiment, 46 young adults were randomized into three groups: position control motor practice (PC), force control motor practice (FC), and a resting control group (CON). Following assessment of baseline motor performance in the position and force control tasks, intervention groups performed motor practice with, augmented visual feedback on performance. Motor performance in both tasks was assessed following motor practice. In a supplementary experiment, measures of corticospinal excitability were obtained in twenty additional participants by application of transcranial magnetic stimulation to the primary motor cortex hot spot of the flexor carpi radialis muscle before and following either position or force control motor practice. Following motor practice, accuracy in the position task improved significantly more for PC compared to FC and CON. For the force control task, both the PC and FC group improved more compared to CON. The two types of motor practice thus led to distinct effects including positive between-task transfer accompanying dynamic motor practice The results of the supplementary study demonstrated an increase in corticospinal excitability following dynamic motor practice compared to isometric motor practice. In conclusion, dynamic motor practice improves movement accuracy, and force control and leads to increased corticospinal excitability compared to isometric motor practice.

Assessment of human expertise and movement kinematics in first-person shooter games

In contrast to traditional professional sports, there are few standardized metrics in professional esports (competitive multiplayer video games) for assessing a player's skill and ability. We assessed the performance of professional-level players in Aim LabTM, a first-person shooter training and assessment game, with two target-shooting tasks. These tasks differed primarily in target size: the task with large targets provided an incentive to be fast but imprecise and the task with large targets provided an incentive to be precise but slow. Each player's motor acuity was measured by characterizing the speed-accuracy trade-off in shot behavior: shot time (elapsed time for a player to shoot at a target) and shot spatial error (distance from center of a target). We also characterized the fine-grained kinematics of players' mouse movements. Our findings demonstrate that: 1) movement kinematics depended on task demands; 2) individual differences in motor acuity were significantly correlated with kinematics; and 3) performance, combined across the two target sizes, was poorly characterized by Fitts Law. Our approach to measuring motor acuity has widespread applications not only in esports assessment and training, but also in basic (motor psychophysics) and clinical (gamified rehabilitation) research.

Age-related increases in reaction time result from slower preparation, not delayed initiation

Recent work indicates that healthy younger adults can prepare accurate responses faster than their voluntary reaction times would suggest, leaving a seemingly unnecessary delay of 80-100 ms before responding. Here, we examined how the preparation of movements, initiation of movements, and the delay between them are affected by aging. Participants made planar reaching movements in two conditions. The "free reaction time" condition assessed the voluntary reaction times with which participants responded to the appearance of a stimulus. The "forced reaction time" condition assessed the minimum time actually needed to prepare accurate movements by controlling the time allowed for movement preparation. The time taken to both initiate movements in the free reaction time and to prepare movements in the forced response condition increased with age. Notably, the time required to prepare accurate movements was significantly shorter than participants' self-selected initiation times; however, the delay between movement preparation and initiation remained consistent across the lifespan (∼90 ms). These results indicate that the slower reaction times of healthy older adults are not due to an increased hesitancy to respond, but can instead be attributed to changes in their ability to process stimuli and prepare movements accordingly, consistent with age-related changes in brain structure and function.NEW & NOTEWORTHY Previous research argues that older adults have slower response times because they hesitate to react, favoring accuracy over speed. The present results challenge this proposal. We found the delay between the minimum time required to prepare movements and the self-selected time at which they initiated remained consistent at ∼90 ms from ages 21 to 80. We therefore suggest older adults' slower response times can be attributed to changes in their ability to process stimuli and prepare movements.

Estimating speed-accuracy trade-offs to evaluate and understand closed-loop prosthesis interfaces

OBJECTIVE

Closed-loop prosthesis interfaces, which combine electromyography (EMG)-based control with supplementary feedback, represent a promising direction for developing the next generation of bionic limbs. However, we still lack an understanding of how users utilize these interfaces and how to evaluate competing solutions. In this study, we used the framework of speed-accuracy trade-off functions (SAF) to understand, evaluate, and compare the performance of two closed-loop user-prosthesis interfaces.

APPROACH

Ten able-bodied participants and an amputee performed a force-matching task in a functional box-and-block setup at three different speeds. All participants were subjected to both interfaces in a crossover study design with a one-week washout period. Importantly, both interfaces used (identical) direct proportional control but differed in the feedback provided to the participant (EMG feedback vs. Force feedback). Therefore, we estimated the SAFs afforded by the two interfaces and sought to understand how the participants planned and executed the task under the various conditions.

MAIN RESULTS

We found that execution speed significantly influenced performance, and that EMG feedback afforded better overall performance, especially at medium speeds. Notably, we found that there was a difference in the SAF between the two interfaces, with EMG feedback enabling participants to attain higher accuracies faster than Force feedback. Furthermore, both interfaces enabled participants to develop flexible control policies, while EMG feedback also afforded participants the ability to generate smoother, more repeatable EMG commands.

SIGNIFICANCE

Overall, the results indicate that the performance of closed-loop prosthesis interfaces depends critically on the feedback approach and execution speed. This study showed that the SAF framework could be used to reveal the differences between feedback approaches, which might not have been detected if the assessment was performed at a single speed. Therefore, we argue that it is important to consider the speed-accuracy trade-offs to rigorously evaluate and compare user-prosthesis interfaces.

Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks

Humans learn movements naturally, but it takes a lot of time and training to achieve expert performance in motor skills. In this review, we show how modern technologies can support people in learning new motor skills. First, we introduce important concepts in motor control, motor learning and motor skill learning. We also give an overview about the rapid expansion of machine learning algorithms and sensor technologies for human motion analysis. The integration between motor learning principles, machine learning algorithms and recent sensor technologies has the potential to develop AI-guided assistance systems for motor skill training. We give our perspective on this integration of different fields to transition from motor learning research in laboratory settings to real world environments and real world motor tasks and propose a stepwise approach to facilitate this transition.

Motor skill learning decreases movement variability and increases planning horizon

We investigated motor skill learning using a path tracking task, where human subjects had to track various curved paths at a constant speed while maintaining the cursor within the path width. Subjects' accuracy increased with practice, even when tracking novel untrained paths. Using a "searchlight" paradigm, where only a short segment of the path ahead of the cursor was shown, we found that subjects with a higher tracking skill differed from the novice subjects in two respects. First, they had lower movement variability, in agreement with previous findings. Second, they took a longer section of the future path into account when performing the task, i.e. had a longer planning horizon. We estimate that between one third and one half of the performance increase in the expert group was due to the longer planning horizon. An optimal control model with a fixed horizon (receding horizon control) that increases with tracking skill quantitatively captured the subjects' movement behaviour. These findings demonstrate that human subjects not only increase their motor acuity but also their planning horizon when acquiring a motor skill.

Long-Term Motor Learning in the "Wild" With High Volume Video Game Data

Motor learning occurs over long periods of practice during which motor acuity, the ability to execute actions more accurately, precisely, and in less time, improves. Laboratory-based studies of motor learning are typically limited to a small number of participants and a time frame of minutes to several hours per participant. There is a need to assess the generalizability of theories and findings from lab-based motor learning studies on larger samples and time scales. In addition, laboratory-based studies of motor learning use relatively simple motor tasks which participants are unlikely to be intrinsically motivated to learn, limiting the interpretation of their findings in more ecologically valid settings ("in the wild"). We studied the acquisition and longitudinal refinement of a complex sensorimotor skill embodied in a first-person shooter video game scenario, with a large sample size (N = 7174, 682,564 repeats of the 60 s game) over a period of months. Participants voluntarily practiced the gaming scenario for up to several hours per day up to 100 days. We found improvement in performance accuracy (quantified as hit rate) was modest over time but motor acuity (quantified as hits per second) improved considerably, with 40-60% retention from 1 day to the next. We observed steady improvements in motor acuity across multiple days of video game practice, unlike most motor learning tasks studied in the lab that hit a performance ceiling rather quickly. Learning rate was a non-linear function of baseline performance level, amount of daily practice, and to a lesser extent, number of days between practice sessions. In addition, we found that the benefit of additional practice on any given day was non-monotonic; the greatest improvements in motor acuity were evident with about an hour of practice and 90% of the learning benefit was achieved by practicing 30 min per day. Taken together, these results provide a proof-of-concept in studying motor skill acquisition outside the confines of the traditional laboratory, in the presence of unmeasured confounds, and provide new insights into how a complex motor skill is acquired in an ecologically valid setting and refined across much longer time scales than typically explored.

Motor Memory Consolidation after Augmented Variability Depends on the Space in which Variability is Introduced

Motor memories undergo a period of consolidation before they become resistant to the practice of another task. Although movement variability is important in motor memory consolidation, its role is not fully understood in redundant tasks where variability can exist along two orthogonal subspaces (the 'task space' and the 'null space') that have different effects on task performance. Here, we used haptic perturbations to augment variability in these different spaces and examined their effect on motor memory consolidation. Participants learned a shuffleboard task, where they held a bimanual manipulandum and made a discrete throwing motion to slide a virtual puck towards a target. The task was redundant because the distance travelled by the puck was determined by the sum of the left and right hand speeds at release. After participants practiced the task, we used haptic perturbations to introduce motor variability in the task space or null space and examined consolidation of the original task on the next day. We found that regardless of the amplitude, augmenting variability in the task space resulted in significantly better consolidation relative to augmenting variability in the null space, but was not different from a control group that practiced with no variability. This benefit of increasing task space variability relative to increasing null space variability was likely due to the fact that it did not disrupt the pre-existing coordination strategy. These results suggest that the effects of variability on motor memory consolidation depend on the interplay between the induced variability and the pre-existing coordination strategy.

Motor skill training without online visual feedback enhances feedforward control

Motor skill learning involves improvement in feedforward control, the ability to execute a motor plan more reliably, and feedback control, the ability to adjust the motor plan on the fly. The dependence between these control components and the association between training conditions and their improvement have not been directly examined. This study characterizes the contribution of feedforward and feedback control components to motor skill learning using the arc-pointing task (APT), a drawing task that requires high motor acuity. In experiment 1, the performance of three groups of subjects was tested before and after training with online visual feedback (OF group), with knowledge of performance feedback that was presented after movement completion (KP group), and with both online and KP feedback (KP + OF group). Although the improvement of the OF group was not different from the improvement of the KP + OF group, comparison of the KP and KP + OF groups revealed an advantage to the KP group in the fast test speed, suggesting that training without online feedback leads to a greater improvement in feedforward control. In experiment 2, subject's improvement was examined using test probes for estimating feedback and feedforward control. Both KP + OF and KP groups showed improvement in feedforward and feedback conditions with a trend toward a greater improvement of the KP group. Our results suggest that online visual feedback suppresses improvement in feedforward control during motor skill learning.NEW & NOTEWORTHY Becoming a skillful player requires both executing reliable movements and being able to efficiently control them online. We study here how training with and without online visual feedback affects feedforward and feedback control improvement in a drawing task that requires high precision. We show that training with online feedback suppresses improvement in feedforward control and leads to inferior performance in fast movements.

The Strength of the Corticospinal Tract Not the Reticulospinal Tract Determines Upper-Limb Impairment Level and Capacity for Skill-Acquisition in the Sub-Acute Post-Stroke Period

Background. Upper-limb impairment in patients with chronic stroke appears to be partly attributable to an upregulated reticulospinal tract (RST). Here, we assessed whether the impact of corticospinal (CST) and RST connectivity on motor impairment and skill-acquisition differs in sub-acute stroke, using transcranial magnetic stimulation (TMS)–based proxy measures. Methods. Thirty-eight stroke survivors were randomized to either reach training 3-6 weeks post-stroke (plus usual care) or usual care only. At 3, 6 and 12 weeks post-stroke, we measured ipsilesional and contralesional cortical connectivity (surrogates for CST and RST connectivity, respectively) to weak pre-activated triceps and deltoid muscles with single pulse TMS, accuracy of planar reaching movements, muscle strength (Motricity Index) and synergies (Fugl-Meyer upper-limb score). Results. Strength and presence of synergies were associated with ipsilesional (CST) connectivity to the paretic upper-limb at 3 and 12 weeks. Training led to planar reaching skill beyond that expected from spontaneous recovery and occurred for both weak and strong ipsilesional tract integrity. Reaching ability, presence of synergies, skill-acquisition and strength were not affected by either the presence or absence of contralesional (RST) connectivity. Conclusion. The degree of ipsilesional CST connectivity is the main determinant of proximal dexterity, upper-limb strength and synergy expression in sub-acute stroke. In contrast, there is no evidence for enhanced contralesional RST connectivity contributing to any of these components of impairment. In the sub-acute post-stroke period, the balance of activity between CST and RST may matter more for the paretic phenotype than RST upregulation per se.

Promoting neuroplasticity and neuropsychological functioning in frailty through an app-based sensorimotor training: study protocol for a randomized trial

BACKGROUND

Frailty is characterized by an age-related decline in multiple physiological systems, leading to a high vulnerability to stressors, adverse health outcomes, and low quality of life. Neuroscientific models of pathological aging emphasize the loss of sensorimotor stimulation and reduced neuromodulatory capacities as core processes in age-related cognitive and bodily decline, which may be associated with maladaptive plastic changes in the brain. We plan to increase sensorimotor stimulation in frail persons through a newly developed app-based training program and link the training trials to biological and psychological correlates of age-associated vulnerability and health indices.

METHODS

We will conduct a randomized trial, applying an app-based sensorimotor home training (N = 30) in people suffering from frailty. An app-based relaxation training will serve as an active control condition (N = 30). Both interventions will last for 90 days each. The sensorimotor training includes unimodal and multimodal sensory discrimination tasks in the visual, auditory, and tactile domain, as well as sensorimotor precision tasks. The tasks will be implemented using an adaptive training algorithm and enriched with motivational components embedded in a virtual training environment. We expect a pre-post reduction of frailty status and associated functional decline related to refinement of representational maps within the sensorimotor system and improved sensorimotor function such as extremity function. Secondary analyses will study the influence of BDNF genotype as moderating variable. Additional outcomes will include measures of perceptual and cognitive functioning, quality of life as well as BDNF serum levels. Measurements will take place before training (baseline), after 60 days (assessment 1), and at the end of the training after 90 days (assessment 2).

DISCUSSION

In our randomized trial, we aim to characterize a multidimensional concept of frailty and to target maladaptive behaviors and neuroplasticity using an app-based sensorimotor training. This type of intervention might provide further knowledge and new possibilities for preventing decline and preserving function in older adults.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03666039 . Registered 11 September 2018 - Retrospectively registered. Protocol version: Version 4 revised (issue date: 19 May 2021).

Somatosensory versus cerebellar contributions to proprioceptive changes associated with motor skill learning: A theta burst stimulation study

BACKGROUND

It is well established that proprioception (position sense) is important for motor control, yet its role in motor learning and associated plasticity is not well understood. We previously demonstrated that motor skill learning is associated with enhanced proprioception and changes in sensorimotor neurophysiology. However, the neural substrates mediating these effects are unclear.

OBJECTIVE

To determine whether suppressing activity in the cerebellum and somatosensory cortex (S1) affects proprioceptive changes associated with motor skill learning.

METHODS

54 healthy young adults practiced a skill involving visually-guided 2D reaching movements through an irregular-shaped track using a robotic manipulandum with their right hand. Proprioception was measured using a passive two-alternative choice task before and after motor practice. Continuous theta burst stimulation (cTBS) was delivered over S1 or the cerebellum (CB) at the end of training for two consecutive days. We compared group differences (S1, CB, Sham) in proprioception and motor skill, quantified by a speed-accuracy function, measured on a third consecutive day (retention).

RESULTS

As shown previously, the Sham group demonstrated enhanced proprioceptive sensitivity after training and at retention. The S1 group had impaired proprioceptive function at retention through online changes during practice, whereas the CB group demonstrated offline decrements in proprioceptive function. All groups demonstrated motor skill learning. However, the magnitude of learning differed between the CB and Sham groups, consistent with a role for the cerebellum in motor learning.

CONCLUSION

Overall, these findings suggest that the cerebellum and S1 are important for distinct aspects of proprioceptive changes during skill learning.

TDCS effects on pointing task learning in young and old adults

Skill increase in motor performance can be defined as explicitly measuring task success but also via more implicit measures of movement kinematics. Even though these measures are often related, there is evidence that they represent distinct concepts of learning. In the present study, the effect of multiple tDCS-sessions on both explicit and implicit measures of learning are investigated in a pointing task in 30 young adults (YA) between 27.07 ± 3.8 years and 30 old adults (OA) between 67.97 years ± 5.3 years. We hypothesized, that OA would show slower explicit skill learning indicated by higher movement times/lower accuracy and slower implicit learning indicated by higher spatial variability but profit more from anodal tDCS compared with YA. We found age-related differences in movement time but not in accuracy or spatial variability. TDCS did not skill learning facilitate learning neither in explicit nor implicit parameters. However, contrary to our hypotheses, we found tDCS-associated higher accuracy only in YA but not in spatial variability. Taken together, our data shows limited overlapping of tDCS effects in explicit and implicit skill parameters. Furthermore, it supports the assumption that tDCS is capable of producing a performance-enhancing brain state at least for explicit skill acquisition.

Visuomotor associations facilitate movement preparation

Many motor skills require rapidly choosing a movement goal and preparing a movement to that goal, such as in sports where circumstances often change quickly and many actions are possible. Humans can benefit from learning the perceptual cues that predict the requirements of movement so that the choice of a movement goal and movement preparation can occur earlier. However, there remains uncertainty about how these perceptual cues are learned. Here we investigate the use and learning of these perceptual-motor associations. First, we ask if episodic memory for associations can support learning. In Experiment 1, participants first memorized associations between symbols and movement goals. When these symbols were subsequently presented as cues, reaching movements were prepared as efficiently as if the goals themselves were previewed, without the need for additional practice. Next, we ask whether statistical learning can be used to learn the associations. In Experiment 2, participants had to learn the associations during the movement task itself. This learning enabled efficient movement preparation, and the rate of improvement scaled with the number and complexity of associations. These findings suggest that movement preparation can be facilitated by perceptual cues via statistical learning and memory recall, highlighting a potential role for learning and memory systems not conventionally implicated in motor behavior. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Motor training strengthens corticospinal suppression during movement preparation

Movement preparation involves a broad suppression in the excitability of the corticospinal pathway, a phenomenon called preparatory suppression. Here, we show that motor training strengthens preparatory suppression and that this strengthening is associated with faster reaction times. Our findings highlight a key role of preparatory suppression in training-driven behavioral improvements.

Reward-Based Improvements in Motor Control Are Driven by Multiple Error-Reducing Mechanisms

Reward has a remarkable ability to invigorate motor behavior, enabling individuals to select and execute actions with greater precision and speed. However, if reward is to be exploited in applied settings, such as rehabilitation, a thorough understanding of its underlying mechanisms is required. In a series of experiments, we first demonstrate that reward simultaneously improves the selection and execution components of a reaching movement. Specifically, reward promoted the selection of the correct action in the presence of distractors, while also improving execution through increased speed and maintenance of accuracy. These results led to a shift in the speed-accuracy functions for both selection and execution. In addition, punishment had a similar impact on action selection and execution, although it enhanced execution performance across all trials within a block, that is, its impact was noncontingent to trial value. Although the reward-driven enhancement of movement execution has been proposed to occur through enhanced feedback control, an untested possibility is that it is also driven by increased arm stiffness, an energy-consuming process that enhances limb stability. Computational analysis revealed that reward led to both an increase in feedback correction in the middle of the movement and a reduction in motor noise near the target. In line with our hypothesis, we provide novel evidence that this noise reduction is driven by a reward-dependent increase in arm stiffness. Therefore, reward drives multiple error-reduction mechanisms which enable individuals to invigorate motor performance without compromising accuracy.SIGNIFICANCE STATEMENT While reward is well-known for enhancing motor performance, how the nervous system generates these improvements is unclear. Despite recent work indicating that reward leads to enhanced feedback control, an untested possibility is that it also increases arm stiffness. We demonstrate that reward simultaneously improves the selection and execution components of a reaching movement. Furthermore, we show that punishment has a similar positive impact on performance. Importantly, by combining computational and biomechanical approaches, we show that reward leads to both improved feedback correction and an increase in stiffness. Therefore, reward drives multiple error-reduction mechanisms which enable individuals to invigorate performance without compromising accuracy. This work suggests that stiffness control plays a vital, and underappreciated, role in the reward-based imporvemenets in motor control.

"Two sides of the same coin": constant motor learning speeds up, whereas variable motor learning stabilizes, speed-accuracy movements

PURPOSE

The aim of this study was to determine the time course of the trade-off between speed and accuracy, intraindividual variability, and movement transfer and retention (4 weeks after learning) of speed-accuracy tasks.

METHODS

The participants in this study were healthy adults randomly divided into three groups (control versus constant versus variable). They were aged 19-24 years, and 30 (15 men and 15 women) were in each group. Participants had to perform various tasks with the right dominant hand: (a) simple reaction test; (b) maximal velocity measurement; and (c) a speed-accuracy task.

RESULTS

During constant and variable learning, the trade-off in a speed-accuracy task in specific situations shifted toward improved motor planning and motor execution speed, and to reduced intraindividual variability. However, during variable learning, the maximal velocity and variability of motor planning time did not change. Constant learning effectively transferred into variable tasks in terms of reaction time, average velocity and maximal velocity, and these effects were greater than those associated with variable learning. However, the effects of constant learning did not transfer fully into the performance variability of variable movements. Variable learning effectively transferred into constant tasks for the coefficient of variation of the path of movement, average velocity, maximal velocity and reaction time. The retention effect depended neither on learning nor task specificity (constant versus variable tasks).

CONCLUSION

Constant learning speeds up but does not stabilize speed-accuracy movements in variable tasks; whereas, variable learning stabilizes but does not speed up speed-accuracy movements in constant tasks.

Neurophysiology of motor skill learning in chronic stroke

OBJECTIVE

Motor learning is relevant in chronic stroke for acquiring compensatory strategies to motor control deficits. However, the neurophysiological mechanisms underlying motor skill acquisition with the paretic upper limb have received little systematic investigation. The aim of this study was to assess the modulation of corticomotor excitability and intracortical inhibition within ipsilesional primary motor cortex (M1) during motor skill learning.

METHODS

Ten people at the chronic stage after stroke and twelve healthy controls trained on a sequential visuomotor isometric wrist extension task. Skill was quantified before, immediately after, 24 hours and 7 days post-training. Transcranial magnetic stimulation was used to examine corticomotor excitability and short- and long-interval intracortical inhibition (SICI and LICI) pre- and post-training.

RESULTS

The patient group exhibited successful skill acquisition and retention, although absolute skill level was lower compared with controls. In contrast to controls, patients' ipsilesional corticomotor excitability was not modulated during skill acquisition, which may be attributed to excessive ipsilesional LICI relative to controls. SICI decreased after training for both patient and control groups.

CONCLUSIONS

Our findings indicate distinct inhibitory networks within M1 that may be relevant for motor learning after stroke.

SIGNIFICANCE

These findings have potential clinical relevance for neurorehabilitation adjuvants aimed at augmenting the recovery of motor function.

Fast and specific: insights into the acquisition and generalization of motor acuity

Motor acuity is considered to be the outcome of prolonged practice and to involve morphological changes in the motor cortex. We have previously designed a curved pointing task, the arc pointing task (APT), to study motor acuity acquisition, defined as a change in the speed-accuracy tradeoff function (SAF) of the task. Here, we studied the generalization of motor acuity between hands and between tasks (drawing the arc in the opposite direction and with the untrained hand) and the effect of training duration on motor acuity. We report that training-induced motor acuity improvement did not generalize across hands and across tasks performed with the same hand, suggesting a task-specific representation of motor acuity. To our surprise, the largest gains in motor acuity, measured both by changes in SAF and by improvement in multiple kinematic variables, were seen following a short exposure to the task. Our results suggest that motor acuity training-induced improvement is task specific and that motor acuity starts to improve following a very short practice.NEW & NOTEWORTHY We report that training induced motor acuity improvement does not generalize from one hand to another or between movements that are performed with the same effector. Furthermore, significant improvements in acuity were found following a very short exposure to the task (∼20 trials). Therefore, our results suggest that the nervous system has the capacity to rapidly improve motor acuity.

Absence of differences in the learning rate of a speed-accuracy movement task between women patients with mild and major depression and healthy adult women

This study tested the hypothesis that women patients with depression should perform movements more slowly and with greater variability, and their learning rate should be lower compared with age-matched healthy adult women. Three groups of adult women subjects (aged 33-37 years, women patients with mild and major depression and healthy adult women, n = 20 in each group) performed five series (20 repetitions in each series) of a speed-accuracy hand-movement task (SAT). The mean movement speed (V_a) of the SAT was lower and more stable (the coefficient of variation of V_a was lower) in women patients with major depression compared with those with minor depression and healthy adult women during the first series of the SAT. Only the V_a and movement accuracy (path of movement, S) of the SAT varied significantly in the five learning series regardless of the subject group (healthy women subjects and women patients with minor and major depression). The intraindividual variability of reaction time, V_a, maximal movement velocity to the target (tV_max), time to tV_max, and S did not change significantly in any of the groups. Our research data showed that although women patients with depression performed speed-accuracy movements more slowly, the stability of the performance of their movements and their learning rate did not differ from those of age-matched healthy adult women.

Distinct types of neural reorganization during long-term learning

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

Error-related Persistence of Motor Activity in Resting-state Networks

The relationship between neural activation during movement training and the plastic changes that survive beyond movement execution is not well understood. Here we ask whether the changes in resting-state functional connectivity observed following motor learning overlap with the brain networks that track movement error during training. Human participants learned to trace an arched trajectory using a computer mouse in an MRI scanner. Motor performance was quantified on each trial as the maximum distance from the prescribed arc. During learning, two brain networks were observed, one showing increased activations for larger movement error, comprising the cerebellum, parietal, visual, somatosensory, and cortical motor areas, and the other being more activated for movements with lower error, comprising the ventral putamen and the OFC. After learning, changes in brain connectivity at rest were found predominantly in areas that had shown increased activation for larger error during task, specifically the cerebellum and its connections with motor, visual, and somatosensory cortex. The findings indicate that, although both errors and accurate movements are important during the active stage of motor learning, the changes in brain activity observed at rest primarily reflect networks that process errors. This suggests that error-related networks are represented in the initial stages of motor memory formation.

Structural Gray Matter Changes in the Hippocampus and the Primary Motor Cortex on An-Hour-to-One- Day Scale Can Predict Arm-Reaching Performance Improvement

Recent studies have revealed rapid (e.g., hours to days) training-induced cortical structural changes using magnetic resonance imaging (MRI). Currently, there is great interest in studying how such a rapid brain structural change affects behavioral improvement. Structural reorganization contributes to memory or enhanced information processing in the brain and may increase its capability of skill learning. If the gray matter (GM) is capable of such rapid structural reorganization upon training, the extent of volume increase may characterize the learning process. To shed light on this issue, we conducted a case series study of 5-day visuomotor learning using neuroanatomical imaging, and analyzed the effect of rapid brain structural change on motor performance improvement via regression analysis. Participants performed an upper-arm reaching task under left-right mirror-reversal for five consecutive days; T1-weighted MR imaging was performed before training, after the first and fifth days, and 1 week and 1 month after training. We detected increase in GM volume on the first day (i.e., a few hours after the first training session) in the primary motor cortex (M1), primary sensory cortex (S1), and in the hippocampal areas. Notably, regression analysis revealed that individual differences in such short-term increases were associated with the learning levels after 5 days of training. These results suggest that GM structural changes are not simply a footprint of previous motor learning but have some relationship with future motor learning. In conclusion, the present study provides new insight into the role of structural changes in causing functional changes during motor learning.

Behavioral and neurophysiological mechanisms underlying motor skill learning in patients with post-stroke hemiparesis

OBJECTIVE

Given the presence of execution deficits after stroke, it is difficult to determine if patients with stroke have deficits in motor skill learning with the paretic arm. Here, we controlled for execution deficits while testing practice effects of the paretic arm on motor skill learning, long-term retention, and corticospinal excitability.

METHODS

Ten patients with unilateral stroke and ten age-matched controls practiced a kinematic arm skill for two days and returned for retention testing one-day and one-month post-practice. Motor skill learning was quantified as a change in speed-accuracy tradeoff from baseline to retention tests. Transcranial magnetic stimulation (TMS) was used to generate an input-output curve of the ipsilesional motor cortex (M1), and measure transcallosal inhibition from contralesional to ipsilesional M1.

RESULTS

While the control group had greater overall accuracy than the stroke group, both groups showed comparable immediate and long-term improvements with practice. Skill improvements were accompanied by greater excitability of the ipsilesional corticospinal system and reduced transcallosal inhibition from contralesional to ipsilesional M1.

CONCLUSIONS

When execution deficits are accounted for, patients with stroke demonstrate relatively intact motor skill learning with the paretic arm. Paretic arm learning is accompanied by modulations in corticospinal and transcallosal mechanisms.

SIGNIFICANCE

Functional recovery after stroke relies on ability for skill learning and the underlying mechanisms.

Quantitative Testing of fMRI-Compatibility of an Electrically Active Mechatronic Device for Robot-Assisted Sensorimotor Protocols

OBJECTIVE

To develop a quantitative set of methods for testing the functional magnetic resonance imaging (fMRI) compatibility of an electrically-active mechatronic device developed to support sensorimotor protocols during fMRI.

METHODS

The set of methods includes phantom and in vivo experiments to measure the effect of a progressively broader set of noise sources potentially introduced by the device. Phantom experiments measure the radio-frequency (RF) noise and temporal noise-to-signal ratio (tNSR) introduced by the device. The in vivo experiment assesses the effect of the device on measured brain activation for a human subject performing a representative sensorimotor task. The proposed protocol was validated via experiments using a 3T MRI scanner operated under nominal conditions and with the inclusion of an electrically-active mechatronic device - the MR-SoftWrist - as the equipment under test (EUT).

RESULTS

Quantitative analysis of RF noise data allows detection of active RF noise sources both in controlled RF noise conditions, and in conditions resembling improper filtering of the EUT's electrical signals. In conditions where no RF noise was detectable, the presence and operation of the EUT did not introduce any significant increase in tNSR. A quantitative analysis conducted on in vivo measurements of the number of active voxels in visual and motor areas further showed no significant difference between EUT and baseline conditions.

CONCLUSION AND SIGNIFICANCE

The proposed set of quantitative methods supports the development and troubleshooting of electrically-active mechatronic devices for use in sensorimotor protocols with fMRI, and may be used for future testing of such devices.

Chronic Stroke Survivors Improve Reaching Accuracy by Reducing Movement Variability at the Trained Movement Speed

BACKGROUND

Recovery from stroke is often said to have "plateaued" after 6 to 12 months. Yet training can still improve performance even in the chronic phase. Here we investigate the biomechanics of accuracy improvements during a reaching task and test whether they are affected by the speed at which movements are practiced.

METHOD

We trained 36 chronic stroke survivors (57.5 years, SD ± 11.5; 10 females) over 4 consecutive days to improve endpoint accuracy in an arm-reaching task (420 repetitions/day). Half of the group trained using fast movements and the other half slow movements. The trunk was constrained allowing only shoulder and elbow movement for task performance.

RESULTS

Before training, movements were variable, tended to undershoot the target, and terminated in contralateral workspace (flexion bias). Both groups improved movement accuracy by reducing trial-to-trial variability; however, change in endpoint bias (systematic error) was not significant. Improvements were greatest at the trained movement speed and generalized to other speeds in the fast training group. Small but significant improvements were observed in clinical measures in the fast training group.

CONCLUSIONS

The reduction in trial-to-trial variability without an alteration to endpoint bias suggests that improvements are achieved by better control over motor commands within the existing repertoire. Thus, 4 days' training allows stroke survivors to improve movements that they can already make. Whether new movement patterns can be acquired in the chronic phase will need to be tested in longer term studies. We recommend that training needs to be performed at slow and fast movement speeds to enhance generalization.

Kinesthetic Feedback During 2DOF Wrist Movements via a Novel MR-Compatible Robot

We demonstrate the interaction control capabilities of the MR-SoftWrist, a novel MR-compatible robot capable of applying accurate kinesthetic feedback to wrist pointing movements executed during fMRI. The MR-SoftWrist, based on a novel design that combines parallel piezoelectric actuation with compliant force feedback, is capable of delivering 1.5 N [Formula: see text] of torque to the wrist of an interacting subject about the flexion/extension and radial/ulnar deviation axes. The robot workspace, defined by admissible wrist rotation angles, fully includes a circle with a 20 deg radius. Via dynamic characterization, we demonstrate capability for transparent operation with low (10% of maximum torque output) backdrivability torques at nominal speeds. Moreover, we demonstrate a 5.5 Hz stiffness control bandwidth for a 14 dB range of virtual stiffness values, corresponding to 25%-125% of the device's physical reflected stiffness in the nominal configuration. We finally validate the possibility of operation during fMRI via a case study involving one healthy subject. Our validation experiment demonstrates the capability of the device to apply kinesthetic feedback to elicit distinguishable kinetic and neural responses without significant degradation of image quality or task-induced head movements. With this study, we demonstrate the feasibility of MR-compatible devices like the MR-SoftWrist to be used in support of motor control experiments investigating wrist pointing under robot-applied force fields. Such future studies may elucidate fundamental neural mechanisms enabling robot-assisted motor skill learning, which is crucial for robot-aided neurorehabilitation.

Neural activation during imitation with or without performance feedback: An fMRI study

In our daily lives, we often receive performance feedback (PF) during imitative learning, and we adjust our behaviors accordingly to improve performance. However, little is known regarding the neural mechanisms underlying this learning process. We hypothesized that appropriate PF would enhance neural activation or recruit additional brain areas during subsequent action imitation. Pictures of 20 different finger gestures without any social meaning were shown to participants from the first-person perspective. Imitation with or without PF was investigated by functional magnetic resonance imaging in 30 healthy subjects. The PF was given by a real person or by a computer. PF from a real person induced hyperactivation of the parietal lobe (precuneus and cuneus), cingulate cortex (posterior and anterior), temporal lobe (superior and transverse temporal gyri), and cerebellum (posterior and anterior lobes) during subsequent imitation. The positive PF and negative PF from a real person, induced the activation of more brain areas during the following imitation. The hyperactivation of the cerebellum, posterior cingulate cortex, precuneus, and cuneus suggests that the subjects exhibited enhanced motor control and visual attention during imitation after PF. Additionally, random PF from a computer had a small effect on the next imitation. We suggest that positive and accurate PF may be helpful for imitation learning.

Increased functional connectivity between cortical hand areas and praxis network associated with training-related improvements in non-dominant hand precision drawing

Chronic forced use of the non-dominant left hand yields substantial improvements in the precision and quality of writing and drawing. These changes may arise from increased access by the non-dominant (right) hemisphere to dominant (left) hemisphere mechanisms specialized for end-point precision control. To evaluate this prediction, 22 healthy right-handed adults underwent resting state functional connectivity (FC) MRI scans before and after 10 days of training on a left hand precision drawing task. 89% of participants significantly improved left hand speed, accuracy, and smoothness. Smoothness gains were specific to the trained left hand and persistent: 6 months after training, 71% of participants exhibited above-baseline movement smoothness. Contrary to expectations, we found no evidence of increased FC between right and left hemisphere hand areas. Instead, training-related improvements in left hand movement smoothness were associated with increased FC between both sensorimotor hand areas and a left-lateralized parieto-prefrontal network implicated in manual praxis. By contrast, skill retention at 6 months was predicted by changes including decreased FC between the representation of the trained left hand and bilateral sensorimotor, parietal, and premotor cortices, possibly reflecting consolidation and a disengagement of early learning processes. These data indicate that modest amounts of training (< 200 min total) can induce substantial, persistent improvements the precision and quality of non-dominant hand control in healthy adults, supported by strengthened connectivity between bilateral sensorimotor hand areas and a left-lateralized parieto-prefrontal praxis network.

On tests of activation map dimensionality for fMRI-based studies of learning

A methodology for investigating learning is developed using activation distributions, as opposed to standard voxel-level interaction tests. The approach uses tests of dimensionality to consider the ensemble of paired changes in voxel activation. The developed method allows for the investigation of non-focal and non-localized changes due to learning. In exchange for increased power to detect learning-based changes, this procedure sacrifices the localization information gained via voxel-level interaction testing. The test is demonstrated on an arc-pointing motor task for the study of motor learning, which served as the motivation for this methodological development. The proposed framework considers activation distribution, while the specific proposed test investigates linear tests of dimensionality. This paper includes: the development of the framework, a large scale simulation study, and the subsequent application to a study of motor learning in healthy adults. While the performance of the method was excellent when model assumptions held, complications arose in instances of massive numbers of null voxels or varying angles of principal dimension across subjects. Further analysis found that careful masking addressed the former concern, while an angle correction successfully resolved the latter. The simulation results demonstrated that the study of linear dimensionality is able to capture learning effects. The motivating data set used to illustrate the method evaluates two similar arc-pointing tasks, each over two sessions, with training on only one of the tasks in between sessions. The results suggests different activation distribution dimensionality when considering the trained and untrained tasks separately. Specifically, the untrained task evidences greater activation distribution dimensionality than the trained task. However, the direct comparison between the two tasks did not yield a significant result. The nature of the indication for greater dimensionality in the untrained task is explored and found to be non-linear variation in the data.

Motor skill learning between selection and execution

Learning motor skills evolves from the effortful selection of single movement elements to their combined fast and accurate production. We review recent trends in the study of skill learning which suggest a hierarchical organization of the representations that underlie such expert performance, with premotor areas encoding short sequential movement elements (chunks) or particular component features (timing/spatial organization). This hierarchical representation allows the system to utilize elements of well-learned skills in a flexible manner. One neural correlate of skill development is the emergence of specialized neural circuits that can produce the required elements in a stable and invariant fashion. We discuss the challenges in detecting these changes with fMRI.