Prediction Of Motor Performance Research Articles

Pick your battles: Elite ski-jumpers’ motives affect world cup performance depending on competition type

According to motive disposition theory, athletes high in affiliation motivation should find team contexts more rewarding than individual contexts, and hence perform better in team than in individual competitions. The opposite is predicted for athletes high in power motivation. To the best of our knowledge, this is the first study to test these hypotheses in an elite sample (here: ski jumping athletes) based on archived worldcup competition data from both individual and team competitions on the one hand, and self-reported and projectively assessed motives on the other hand. Results confirmed that even at the highest levels of professional sports, individual differences in motives show systematic relationships to competition performance. First, the negative impact of athletes' projectively assessed affiliation motive in individual competitions was significantly attenuated in team competitions, indicating that these represent more favorable conditions for athletes high in affiliation. Second, the projectively assessed power motive exhibited an overall negative relationship to performance. In contrast, self-reported achievement and affiliation motives showed a positive relationship to performance. These findings attest to the role of personality differences in predicting motor performance variability in elite sports.

The effects of internal representations on performance and fluidity in a motor task.

Individuals can differ in the mode in which they experience conscious thought. These differences in visualisation and verbalisation can also be evident during motor control. The Internal Representation Questionnaire (IRQ) was developed to measure propensity to engage certain types of representations, but its ability to predict motor control and links to reinvestment and motor imagery have not been tested. 159 included participants completed the IRQ, movement specific reinvestment scale (MSRS), and a novel online motor task before and after a period of practice. Results showed that the IRQ Verbal and Orthographic factors were significant predictors of scores on the MSRS. The IRQ factor of Manipulational Representations predicted motor performance both before and after practice. The fluidity of executed movements were predicted by the IRQ verbalisation factor where higher propensity to verbalise was associated with higher levels of jitter, but only after a period of practice. Results suggest there may be some informative conceptual overlap between internal verbalisations and reinvestment and that the propensity to manipulate internal representations may be predictive of motor performance in new tasks. The IRQ has potential to be a valuable tool for predicting motor performance.

Local Field Potentials Predict Motor Performance in Deep Brain Stimulation for Parkinson's Disease.

Deep brain stimulation (DBS) is an effective treatment option for patients with Parkinson's disease (PD). However, clinical programming remains challenging with segmented electrodes. Using novel sensing-enabled neurostimulators, we investigated local field potentials (LFPs) and their modulation by DBS to assess whether electrophysiological biomarkers may facilitate clinical programming in chronically implanted patients. Sixteen patients (31 hemispheres) with PD implanted with segmented electrodes in the subthalamic nucleus and a sensing-enabled neurostimulator were included in this study. Recordings were conducted 3 months after DBS surgery following overnight withdrawal of dopaminergic medication. LFPs were acquired while stimulation was turned OFF and during a monopolar review of both directional and ring contacts. Directional beta power and stimulation-induced beta power suppression were computed. Motor performance, as assessed by a pronation-supination task, clinical programming and electrode placement were correlated to directional beta power and stimulation-induced beta power suppression. Better motor performance was associated with stronger beta power suppression at higher stimulation amplitudes. Across directional contacts, differences in directional beta power and the extent of stimulation-induced beta power suppression predicted motor performance. However, within individual hemispheres, beta power suppression was superior to directional beta power in selecting the contact with the best motor performance. Contacts clinically activated for chronic stimulation were associated with stronger beta power suppression than non-activated contacts. Our results suggest that stimulation-induced β power suppression is superior to directional β power in selecting the clinically most effective contact. In sum, electrophysiological biomarkers may guide programming of directional DBS systems in PD patients. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Motor Performance During Sensorimotor Training for Airway Protection in Parkinson's Disease.

Cough dysfunction is highly prevalent in Parkinson's disease (PD) and associated with pneumonia, a leading cause of death. Although research suggests that cough can be volitionally upregulated, patterns of improvements that occur during cough skill training and potential correlates remain unexamined. Therefore, we sought to characterize changes to peak flow during cough skill training, examine whether early variability predicted motor performance trajectories during treatment, and explore the relationship between peak flow during cough skill training and motor learning on a similar but untrained task (i.e., reflex cough testing). This secondary analysis of treatment data from a randomized controlled trial included 28 individuals with PD who participated in five sessions of sensorimotor training for airway protection (smTAP). During this novel cough skill training, participants completed 25 repetitions of coughs targeting peak flow 25% above their baseline. Reflex and voluntary cough testing was performed pre- and posttreatment. Bayesian multilevel growth curve models provided group and individual-level estimates of peak flow during training. The magnitude and consistency of peak flow increased during cough skill training. Variability in peak flow during the first treatment session was associated with greater improvements to peak flow in later sessions. There was no relationship between changes to peak flow during cough skill training and motor learning. Individuals with PD improved the strength and variability of cough peak flow during cough skill training. These findings provide a clinically relevant characterization of motor performance during cough skill training and lend insight into potential correlates to guide future treatment paradigms.

Three-dimensional numerical simulation of hybrid rocket motor based on dynamic mesh technology

The three-dimensional dynamic numerical simulation is rare in previous studies of hybrid rocket motors, therefore, a three-dimensional dynamic numerical model is established. A hybrid rocket motor is designed, which adopts 98 wt% hydrogen peroxide and polyethylene as the propellants. Then, a ground experiment is conducted to verify the model. The results show that the method of adopting dynamic mesh technology to simulate the three-dimensional regression of the combustion surface is feasible. The average errors of thrust and pressure in the simulation and experiment are 5.6% and 7.9%, respectively. Moreover, the inner surface of grain is scanned by computed tomography after the experiment. The average deviation of port diameter is 5% between the simulation and experiment, therefore, the accuracy of this model is acceptable. Then, the results also show that the thrust and pressure both gradually decrease with time in the simulation and experiment at 5-10 s. The main reason is the rapid reduction in the fuel mass flow rate. However, the pressure in simulation is stable but decreases with time in experiment at 10-25 s. The main reason is the expansion of the nozzle throat caused by the ablation. The results demonstrate that the numerical method can accurately predict motor performance. In addition, the flow field is approximately uniform along the circumference by the dynamic numerical method, which is difficult to obtain for the conventional steady-state and two-dimensional methods. It is the first time to realize the three-dimensional regression in hybrid rocket motors. Therefore, this method can be used to predict the three-dimensional regression of the complex shapes grain and also can guide the design of grain shape in hybrid rocket motors.

Neurophysiological Markers of Premotor-Motor Network Plasticity Predict Motor Performance in Young and Older Adults.

Aging is commonly associated with a decline in motor control and neural plasticity. Tuning cortico-cortical interactions between premotor and motor areas is essential for controlling fine manual movements. However, whether plasticity in premotor-motor circuits predicts hand motor abilities in young and elderly humans remains unclear. Here, we administered transcranial magnetic stimulation (TMS) over the ventral premotor cortex (PMv) and primary motor cortex (M1) using the cortico-cortical paired-associative stimulation (ccPAS) protocol to manipulate the strength of PMv-to-M1 connectivity in 14 young and 14 elderly healthy adults. We assessed changes in motor-evoked potentials (MEPs) during ccPAS as an index of PMv-M1 network plasticity. We tested whether the magnitude of MEP changes might predict interindividual differences in performance in two motor tasks that rely on premotor-motor circuits, i.e., the nine-hole pegboard test and a choice reaction task. Results show lower motor performance and decreased PMv-M1 network plasticity in elderly adults. Critically, the slope of MEP changes during ccPAS accurately predicted performance at the two tasks across age groups, with larger slopes (i.e., MEP increase) predicting better motor performance at baseline in both young and elderly participants. These findings suggest that physiological indices of PMv-M1 plasticity could provide a neurophysiological marker of fine motor control across age-groups.

Deep learning prediction of motor performance in stroke individuals using neuroimaging data

The degree of motor impairment and profile of recovery after stroke are difficult to predict for each individual. Measures obtained from clinical assessments, as well as neurophysiological and neuroimaging techniques have been used as potential biomarkers of motor recovery, with limited accuracy up to date. To address this, the present study aimed to develop a deep learning model based on structural brain images obtained from stroke participants and healthy volunteers. The following inputs were used in a multi-channel 3D convolutional neural network (CNN) model: fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity maps obtained from Diffusion Tensor Imaging (DTI) images, white and gray matter intensity values obtained from Magnetic Resonance Imaging, as well as demographic data (e.g., age, gender). Upper limb motor function was classified into “Poor” and “Good” categories. To assess the performance of the DL model, we compared it to more standard machine learning (ML) classifiers including k-nearest neighbor, support vector machines (SVM), Decision Trees, Random Forests, Ada Boosting, and Naïve Bayes, whereby the inputs of these classifiers were the features taken from the fully connected layer of the CNN model. The highest accuracy and area under the curve values were 0.92 and 0.92 for the 3D-CNN and 0.91 and 0.91 for the SVM, respectively. The multi-channel 3D-CNN with residual blocks and SVM supported by DL was more accurate than traditional ML methods to classify upper limb motor impairment in the stroke population. These results suggest that combining volumetric DTI maps and measures of white and gray matter integrity can improve the prediction of the degree of motor impairment after stroke. Identifying the potential of recovery early on after a stroke could promote the allocation of resources to optimize the functional independence of these individuals and their quality of life.

Motor cad를 이용한 11,000[V]급 수중 펌프용 전동기 개발

In this paper, a motor for 11,000[V] class Electrical submersible pump was developed for the first time in Korea. In order to prevent the deterioration of the winding or the breakdown of insulation due to the current flowing during the start-up of extra-high voltage, Nomex was wound around the PAI winding to increase the mechanical heat resistance and to produce a group winding. Motor cad program was used to predict the performance of the motor and the temperature characteristics due to the loss that occurs during high-speed operation. A prototype was manufactured. Then, the dielectric strength and performance analysis of the winding wire were compared with the predicted values of the simulation. The motor cad simulation showed current 18.8[A], resistance 8.02 [Ω], efficiency 95.3[%], power factor 83.8[%]. The prototype confirmed the measured values of current 19.7[A], resistance 8.1[Ω], efficiency 93.8[%], power factor 84.7[%]. The temperature characteristics were confirmed as 89.8°C for the winding part, 44°C for the upper and lower parts of the bearing, and 48.2°C based on the maximum limit of 25°C in water. The result of this study improved the completeness of completion by predicting motor performance with the Motor cad program before manufacturing prototypes.

Baseline Measures of Cortical Inhibition Predict Motor Performance Changes after Exercise Interventions

<h3>Research Objectives</h3> To investigate the relationship of transcranial magnetic stimulation (TMS) measures on cortical inhibition before and after an exercise intervention in older adults. Our hypothesis is that higher levels of cortical inhibition would predict greater motor skill acquisition. We predicted that persons randomized to an aerobic spin exercise intervention would increase cortical inhibition and motor performance as compared to light strength training. <h3>Design</h3> The study design is randomized controlled trial with two groups investigating a balance and strength training intervention (both lasting 12-weeks or 36 sessions) against an Aerobic Cycling Intervention. The assessment sessions included behavioral testing, TMS taken at study baseline and after 12-weeks. <h3>Setting</h3> This project involved community dwelling older adults and was performed in a medical center. The main study sites were the Atlanta VA and Emory University. <h3>Participants</h3> We randomized 20 participants to either an exercise intervention or a balance and strength training group after obtaining informed consent. Participants were required to be over the age of 60 years and reportedly healthy at inclusion. This report is on 13 completers. <h3>Interventions</h3> Participants were randomized to either a 12-week interval aerobic spin cycling (HIIT spin) or a 12-week intervention involving light strength training both under supervised trainers thrice weekly for up to 45 minutes per session. <h3>Main Outcome Measures</h3> We acquired transcranial magnetic stimulation measures of: cortical excitability (motor threshold), Short intracortical inhibition, Long Intracortical Inhibition, Short Interhemispheric inhibition, long interhemispheric inhibition. Speed and accuracy of motor learning was the behavioral outcome. <h3>Results</h3> Baseline measures of SICI and LICI showed participants with higher levels of disinhibition showed better motor performance. We found no effect for group. Contrary to our hypothesis, individuals with greater increases in TMS inhibition showed lower motor skill performance after interventions. <h3>Conclusions</h3> We can conclude from the preliminary data that measures of cortical inhibition taken from TMS do show change associated with interventions in older adults and predict improvement in motor skill acquisition. Additional study is needed to identify the mechanisms of change in cortical inhibition. <h3>Author(s) Disclosures</h3> None.

Cortical thickness of primary motor and vestibular brain regions predicts recovery from fall and balance directly after spaceflight.

Motor adaptations to the microgravity environment during spaceflight allow astronauts to perform adequately in this unique environment. Upon return to Earth, this adaptation is no longer appropriate and can be disruptive for mission critical tasks. Here, we measured if metrics derived from MRI scans collected from astronauts can predict motor performance post-flight. Structural and diffusion MRI scans from 14 astronauts collected before launch, and motor measures (balance performance, speed of recovery from fall, and tandem walk step accuracy) collected pre-flight and post-flight were analyzed. Regional measures of gray matter volume (motor cortex, paracentral lobule, cerebellum), myelin density (motor cortex, paracentral lobule, corticospinal tract), and white matter microstructure (corticospinal tract) were derived as a-priori predictors. Additional whole-brain analyses of cortical thickness, cerebellar gray matter, and cortical myelin were also tested for associations with post-flight and pre-to-post-flight motor performance. The pre-selected regional measures were not significantly associated with motor behavior. However, whole-brain analyses showed that paracentral and precentral gyri thickness significantly predicted recovery from fall post-spaceflight. Thickness of vestibular and sensorimotor regions, including the posterior insula and the superior temporal gyrus, predicted balance performance post-flight and pre-to-post-flight decrements. Greater cortical thickness pre-flight predicted better performance post-flight. Regional thickness of somatosensory, motor, and vestibular brain regions has some predictive value for post-flight motor performance in astronauts, which may be used for the identification of training and countermeasure strategies targeted for maintaining operational task performance.

Age-Related Differences of Frequency-Dependent Functional Connectivity in Brain Networks and Their Link to Motor Performance.

Background: Aging affects the brain at the anatomical and functional levels, resulting in a decline in motor and cognitive performance. Functional magnetic resonance imaging (fMRI) studies documented lower connectivity within brain networks and higher connectivity between them, for older as compared with young adults. However, it is still unclear whether the reduced segregation between networks, as observed with fMRI, has neurophysiological underpinnings. Methods: We collected high-density electroencephalography (hdEEG) data in 24 young and 24 older adults at rest. Bimanual coordination performance was also measured in the same participants, using a computerized test. Using the hdEEG data, we reconstructed oscillatory power and functional connectivity for six large-scale brain networks, in delta, theta, alpha, beta and gamma frequency bands. We evaluated age-related differences in network power and connectivity between young and older participants, and their possible relationships with bimanual coordination performance. Results: We observed that the level of network segregation generally decreased with age, in line with fMRI findings. However, there was a relatively strong dependence on the frequency band and the brain network being considered. EEG connectivity in the sensorimotor network predicted motor performance differences across older individuals, particularly when neural oscillations in the beta frequency band were considered. Discussion: Our study provides electrophysiological evidence in support of the "de-differentiation hypothesis" for the aging brain, and for the existence of a clear link between the strength of EEG connectivity at rest and motor performance.

The Severity of Sensorimotor Tracts Degeneration May Predict Motor Performance in Chronic Stroke Patients, While Brain Structural Network Dysfunction May Not.

Although the relationship between corticospinal tract (CST) fiber degeneration and motor outcome after stroke has been established, the relationship of sensorimotor cortical areas with CST fibers has not been clarified. Also limited research has been conducted on how abnormalities in brain structural networks are related to motor recovery. To address these gaps in knowledge, we conducted a diffusion tensor imaging (DTI) study with 12 chronic stroke patients (CSPs) and 12 age-matched healthy controls (HCs). We compared fractional anisotropy (FA) and mean diffusivity (MD) in 60 CST segments using the probabilistic sensorimotor area tract template (SMATT). Least Absolute Shrinkage and Selection Operator (LASSO) regressions were used to select independent predictors of Fugl-Meyer upper extremity (FM-UE) scores among FA and MD values of SMATT regions. The Graph Theoretical Network Analysis Toolbox was used to assess the structural network of each subject's brain. Global and nodal metrics were calculated, compared between the groups, and correlated with FM-UE scores. Mann–Whitney U-tests revealed reduced FA values in CSPs, compared to HCs, in many ipsilesional SMATT regions and in two contralesional regions. Mean FA value of the left (L.) primary motor cortex (M1)/supplementary motor area (SMA) region was predictive of FM-UE score (P = 0.004). Mean MD values for the L. M1/ventral premotor cortex (PMv) region (P = 0.001) and L. PMv/SMA region (P = 0.001) were found to be significant predictors of FM-UE scores. Network efficiency was the only global metric found to be reduced in CSPs (P = 0.006 vs. HCs). Nodal efficiency of the L. hippocampus, L. parahippocampal gyrus, L. fusiform gyrus (P = 0.001), and nodal local efficiency of the L. supramarginal gyrus (P < 0.001) were reduced in CSPs relative to HCs. No graph metric was associated with FM-UE scores. In conclusion, the integrity of CSTs connected to M1, SMA, and PMv were shown to be independent predictors of motor performance in CSPs, while stroke-induced topological changes in the brain's structural connectome may not be. A sensorimotor cortex-specific tract template can refine CST degeneration data and the relationship of CST degeneration with motor performance.

Numerical Analysis of Nozzle Erosion in Hybrid Rockets and Comparison with Experiments

Nozzle throat erosion in hybrid rocket engines is generally more emphasized than in solid rockets due to a greater concentration of oxidizing species in the combustion products. Therefore, its accurate understanding and modeling is of fundamental importance in order to correctly predict motor performance and possibly to help reducing the associated losses. Moreover, throttling and/or mixture ratio shift can significantly alter the conditions under which the thermal protection material is operating, further complicating the problem. The aim of this work is to numerically investigate the graphite nozzle erosion in hybrid rockets burning high-density polyethylene and oxygen. Nozzle throat erosion rate and wall temperature are evaluated as a function of the operating conditions by performing numerical simulations with a proven in-house computational fluid dynamics solver. The results obtained from a detailed parametric analysis are discussed and then used to derive a general closed-form regression law for rapid estimation of nozzle throat erosion rate for the analyzed propellant combination that is dependent on the operating conditions, chamber pressure and mixture ratio, and on the nozzle geometry. The possible role of combustion efficiency is also discussed. The regression law is then validated through comparison with the experimental results obtained from several lab-scale 2-kN-thrust-class firing tests, underlining a good ability to correctly capture the average nozzle erosion mass flux behavior with the operating conditions and highlighting the different role of the driving parameters.

The relationship of motive disposition and situational incentives to individual differences in choking under pressure.

Motive disposition theory posits that individuals exhibit stable differences in their achievement, affiliation, and power motives - shaping their capacity to perceive performance, social affiliative, or competitive contexts as rewarding. Whereas this approach has been employed in research on individual differences in motor performance, it has not been considered in predicting individual differences in choking under pressure. Typical pressure manipulations often use competitive or team settings which also constitute prime examples of power and affiliation incentives. Consequently, we hypothesized participants' affiliation (vs. power) motive to be related to golf putting performance in team (vs. competitive) settings. In addition, due to the performance feedback provided by the task, it should also generally appeal to participants high in achievement motivation. Specifically, after a familiarization phase a total of 115 participants completed a baseline assessment of golf putting performance, followed by an experimental block manipulating the task's incentives (competition, team, control) between participants. Analysis of participants' previously assessed motives revealed that both participants' affiliation and achievement motive were positively related to performance (variable error) under pressure. No effects emerged for the power motive. These findings highlight the role of personality differences in predicting motor performance variability in pressure situations. We discuss the specific contributions of projective and self-report motive measures and touch upon possible avenues for coaches and practitioners to counter choking effects.

Non‐linear model of the switched reluctance motor with included core losses’ effects

To accurately predict motor performance, considering the effects of core losses is of great importance, especially at speeds much higher than the base where the core losses represent a considerable portion of the total drive losses. Neglecting the effects of core losses leads to an error in the switched reluctance motor (SRM) performance prediction. In this study, a previously developed non-linear SRM model with multiphase coupling is extended by considering the instantaneous effects of core losses on the SRM performance. Using the new model, the nature of these effects is determined. A comparison of the simulation results of the proposed, basic, and finite element method (FEM) model confirms the importance of considering the effects of core losses on motor performance. Besides the FEM model, the accuracy of the proposed model is verified by experiments.

Increased prefrontal top-down control in older adults predicts motor performance and age-group association

Bimanual motor control declines during ageing, affecting the ability of older adults to maintain independence. An important underlying factor is cortical atrophy, particularly affecting frontal and parietal areas in older adults. As these regions and their interplay are highly involved in bimanual motor preparation, we investigated age-related connectivity changes between prefrontal and premotor areas of young and older adults during the preparatory phase of complex bimanual movements using high-density electroencephalography. Generative modelling showed that excitatory inter-hemispheric prefrontal to premotor coupling in older adults predicted age-group affiliation and was associated with poor motor-performance. In contrast, excitatory intra-hemispheric prefrontal to premotor coupling enabled older adults to maintain motor-performance at the cost of lower movement speed. Our results disentangle the complex interplay in the prefrontal-premotor network during movement preparation underlying reduced bimanual control and the well-known speed-accuracy trade-off seen in older adults.

Prediction of Motor Recovery after Stroke by Assessment of Corticospinal Tract Wallerian Degeneration Using Diffusion Tensor Imaging.

Aim of the Study To predict motor recovery after stroke by detection of diffusion tensor imaging (DTI) fractional anisotropy (FA) changes of corticospinal tract (CST) and correlate findings with clinical scores to provide more effective treatment and rehabilitation. Subjects and Methods Thirty patients with cerebral stroke were enrolled and underwent conventional magnetic resonance imaging and DTI at admission and 1 month after stroke. Mean diffusivity (MD), FA, FA ratio (rFA), and fiber number (FN) values of CST were calculated at the pons at admission and after 1 month of stroke. Three-dimensional reconstruction of bilateral CST and the structural changes of fibrous bands were observed. Severity of limb weakness was assessed by using the motor sub-index scores of the National Institutes of Health Stroke Scale (NIHSS) at admission, and after 1, 6, and 9 months for severity of limb weakness. Results The mean age of our patients was 61.32 ± 4.34 years, 17/30 (56.6%) were females, and 13/30 (43.4%) were males. In our study, 18/30 (60%) were hypertensive, 19/30 (63.3%) were diabetic, and 12/30 (40%) were smokers. A significant negative correlation was found between rFA and FN in the ipsilateral CST of the cerebral infarction at the rostral part of pons after 1 month of infarction and NIHSS score at 6 months ( r = 0.377, p = 0.04 and r = 0.237, p = 0.02, respectively). However, a positive insignificant correlation was found between MD and NIHSS ( r = 0.345, p = 0.635). The initial NIHSS score at the time of injury was 19.2 ± 4.3, which changed to 7.9 ± 2.4, 4.6 ± 1.9, and 3.3 ± 1.4 at 1, 6, and 9 months, respectively. Conclusion DTI is a sensitive tool for early detection of Wallerian degeneration in the CST after stroke, and can predict motor performance to provide effective treatment and rehabilitation to improve quality of life.

Interindividual differences in incentive sensitivity moderate motivational effects of competition and cooperation on motor performance.

Established research has documented the pervasive influence of incentives (i.e., food, sex, money) on animal and human behavior. Additionally, motivational theories postulating intra–individually stable preferences for specific types of incentives (i.e., motives) highlight that effects of a given incentive are highly dependent on the motive disposition of the individual. Indeed, also research on motor performance has documented the interactive effects of motives and motive–specific incentives on motor outcomes. However, the majority of this research has relied on correlational designs focusing on the effects of the achievement motive, with few studies addressing the role of the affiliation and power motive. In order to extend findings in this domain, we tested whether a fit between individuals’ power (affiliation) motive and incentives of competition (cooperation) would improve motor performance. Following baseline measures, participants performed a dart–throwing task as part of a dyadic performance (i.e., cooperative) or a one–on–one competition scenario. In the dyadic performance scenario, a stronger affiliation motive did not translate to better performance. However, in the one–on–one competition scenario a stronger power motive was associated with better performance. Results highlight the role of the power motive in predicting motor performance, particularly in competitive situations.

Influence of Adiposity and Maturation on the Motor Performance of Girls Aged 8 to 16 Years

ABSTRACT Excess adipose tissue may impact the motor performance of youth. Therefore, the current study examined (a) if adiposityinfluenced performance in the jump and reach and 30-yard dash and (b) if maturation predicted motor performance. Participants (N = 267) included girls aged 8 to 16 years. Latent growth curves were used to assess changes in motor performance. Sum of skinfolds predicted jump and reach performance from age 8.5 to 10.5 years, 11.5–12.0 years, 13.0 years, and from age 14 to 14.5 years (b = −0.013 to 0.051, p < 0.05). Sum of skinfolds predicted 30-yard dash performance from age 8.5 to 14.0 years and at age 15.5 years (b = 0.003 to 0.005, p < 0.05). Maturation did not predict performance. Future research should examine determinants that explain the link between adiposity and motor performance.

Sensorimotor cortex beta oscillations reflect motor skill learning ability after stroke.

Recovery of skilled movement after stroke is assumed to depend on motor learning. However, the capacity for motor learning and factors that influence motor learning after stroke have received little attention. In this study, we first compared motor skill acquisition and retention between well-recovered stroke patients and age- and performance-matched healthy controls. We then tested whether beta oscillations (15–30 Hz) from sensorimotor cortices contribute to predicting training-related motor performance. Eighteen well-recovered chronic stroke survivors (mean age 64 ± 8 years, range: 50–74 years) and 20 age- and sex-matched healthy controls were trained on a continuous tracking task and subsequently retested after initial training (45–60 min and 24 h later). Scalp electroencephalography was recorded during the performance of a simple motor task before each training and retest session. Stroke patients demonstrated capacity for motor skill learning, but it was diminished compared to age- and performance-matched healthy controls. Furthermore, although the properties of beta oscillations prior to training were comparable between stroke patients and healthy controls, stroke patients did show less change in beta measures with motor learning. Lastly, although beta oscillations did not help to predict motor performance immediately after training, contralateral (ipsilesional) sensorimotor cortex post-movement beta rebound measured after training helped predict future motor performance, 24 h after training. This finding suggests that neurophysiological measures such as beta oscillations can help predict response to motor training in chronic stroke patients and may offer novel targets for therapeutic interventions.