Explore the vast range of titles available.

A successful high-level gymnastics performance is the result of the coordination and inter-relation of body segments to produce movement prototypes. In this context, the exploration of different movement prototypes, as well as their relations with judges’ scores, can aid coaches to design better learning and practice methodologies. Therefore, we investigate if there are different movement prototypes of the technique of the handspring tucked somersault with a half twist (HTB) on a mini trampoline with a vaulting table and its relations with judges’ scores. We assessed flexion/extension angles of five joints during fifty trials, using an inertial measurement unit system. All trials were scored by international judges for execution. A multivariate time series cluster analysis was performed to identify movement prototypes and their differential association with judges’ scores was statistically assessed. Nine different movement prototypes were identified for the HTB technique, with two of them associated with higher scores. Statistically strong associations were found between scores and movement phases one (i.e., from the last step on the carpet to the initial contact of both feet with the mini trampoline), two (i.e., from the initial contact to the take-off on the mini trampoline) and four (i.e., from the initial contact of both hands with the vaulting table to take-off on the vaulting table) and moderate associations with movement phase six (i.e., from the tucked body position to landing with both feet on the landing mat). Our findings suggest (a) the presence of multiple movement prototypes yielding successful scoring and (b) the moderate-to-strong association of movement variations along phases one, two, four and six with judges’ scores. We suggest and provide guidelines for coaches to encourage movement variability that can lead their gymnasts to functionally adapt their performance and succeed when facing different constraints.

Background: Variability in running mechanics, termed running variability, reflects the adaptability of the locomotor system to dynamic environments. Due to inconsistent findings in the literature, there is a research gap in understanding its role in injury. Objectives: This scoping review explores running variability’s influence on injury susceptibility, examining studies across various injury types, skill levels, methods, and analysis adhering to the guidelines outlined in the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist (PRISMA-ScR). Eligibility criteria and sources of evidence: Twenty-one studies illustrating the complexity of running variability in relation to running-related injuries were selected from Web of Science, ScienceDirect, Google Scholar, and PubMed databases during December 2022 to June 2024. Results: There are significant differences in running variability between injured and healthy runners, with variability influenced by injury type, stage, and individual differences with varying levels of evidence. Out of 21 studies, 8 (38%) found no group differences, 11 (52%) noted higher running variability in injured participants, and 5 (24%) reported lower variability in injured than healthy subjects. The review was constrained by the diverse subjects, methods, tasks, and outcome variables across the studies. Conclusions: Currently, there is no standard normal range for running variability and abnormal variability is defined relative to control groups, though healthy controls can also show abnormal variability without injury in some study designs. Despite the absence of standardized running variability norms, wearable sensors offer insights into real-world running mechanics, presenting running variability as a potential predictor of running-related injuries. The review highlights the need for standardized protocols and further research to clarify running variability’s role in injury prediction and prevention, emphasizing the necessity of individualized approaches in training and rehabilitation. Future studies should aim to establish a causal relationship between running variability and injury susceptibility, focusing on identifying variability patterns that precede or follow an injury. This review sets the stage for developing evidence-based strategies to optimize running performance and minimize injury risks.

Movement provides a link between individual behavioral ecology and the spatial and temporal variation in an individual’s landscape. Individual variation in movement traits is an important axis of animal personality, particularly in the context of foraging ecology. We tested whether individual caribou (Rangifer tarandus) displayed plasticity in movement and space-use behavior across a gradient of resource aggregation. We quantified first-passage time and range-use ratio as proxies for movement-related foraging behavior and examined how these traits varied at the individual level across a foraging resource gradient. Our results suggest that individuals adjusted first-passage time but not range-use ratio to maximize access to high-quality foraging resources. First-passage time was repeatable, and intercepts for first-passage time and range-use ratio were negatively correlated. Individuals matched first-passage time but not rangeuse ratio to the expectations of our patch-use model that maximized access to foraging resources, a result that suggests that individuals acclimated their movement patterns to accommodate both intra- and interannual variation in foraging resources on the landscape. Collectively, we highlight repeatable movement and space-use tactics and provide insight into how individual plasticity in movement interacts with landscape processes to affect the distribution of behavioral phenotypes and potentially fitness and population dynamics.

A quantitative model of optimal transport–aperture coordination (TAC) during reach-to-grasp movements has been developed in our previous studies. The utilization of that model for data analysis allowed, for the first time, to examine the phase dependence of the precision demand specified by the CNS for neurocomputational information processing during an ongoing movement. It was shown that the CNS utilizes a two-phase strategy for movement control. That strategy consists of reducing the precision demand for neural computations during the initial phase, which decreases the cost of information processing at the expense of lower extent of control optimality. To successfully grasp the target object, the CNS increases precision demand during the final phase, resulting in higher extent of control optimality. In the present study, we generalized the model of optimal TAC to a model of optimal coordination between X and Y components of point-to-point planar movements (XYC). We investigated whether the CNS uses the two-phase control strategy for controlling those movements, and how the strategy parameters depend on the prescribed movement speed, movement amplitude and the size of the target area. The results indeed revealed a substantial similarity between the CNS’s regulation of TAC and XYC. First, the variability of XYC within individual trials was minimal, meaning that execution noise during the movement was insignificant. Second, the inter-trial variability of XYC was considerable during the majority of the movement time, meaning that the precision demand for information processing was lowered, which is characteristic for the initial phase. That variability significantly decreased, indicating higher extent of control optimality, during the shorter final movement phase. The final phase was the longest (shortest) under the most (least) challenging combination of speed and accuracy requirements, fully consistent with the concept of the two-phase control strategy. This paper further discussed the relationship between motor variability and XYC variability.

Skeletal forces are fundamental information in predicting the risk of bone fracture. The neuromotor control system can drive muscle forces with various task- and health-dependent strategies but current modelling techniques provide a single optimal solution of the muscle load sharing problem. The aim of the present work was to study the variability of the hip load magnitude due to sub-optimal neuromotor control strategies using a subject-specific musculoskeletal model. The model was generated from computed tomography (CT) and dissection data from a single cadaver. Gait kinematics, ground forces and electromyographic (EMG) signals were recorded on a body-matched volunteer. Model results were validated by comparing the traditional optimisation solution with the published hip load measurements and the recorded EMG signals. The solution space of the instantaneous equilibrium problem during the first hip load peak resulted in 105 dynamically equivalent configurations of the neuromotor control. The hip load magnitude was computed and expressed in multiples of the body weight (BW). Sensitivity of the hip load boundaries to the uncertainty on the muscle tetanic stress (TMS) was also addressed. The optimal neuromotor control induced a hip load magnitude of 3.3BW. Sub-optimal neuromotor controls induced a hip load magnitude up to 8.93BW. Reducing TMS from the maximum to the minimum the lower boundary of the hip load magnitude varied moderately whereas the upper boundary varied considerably from 4.26 to 8.93BW. Further studies are necessary to assess how far the neuromotor control can degrade from the optimal activation pattern and to understand which sub-optimal controls are clinically plausible. However we can consider the possibility that sub-optimal activations of the muscular system play a role in spontaneous fractures not associated with falls.

In order to successfully intercept a moving target one must be at the right place at the right time. But simply being there is seldom enough. One usually needs to make contact in a certain manner, for instance to hit the target in a certain direction. How this is best achieved depends on the exact task, but to get an idea of what factors may limit performance we asked people to hit a moving virtual disk through a virtual goal, and analysed the spatial and temporal variability in the way in which they did so. We estimated that for our task the standard deviations in timing and spatial accuracy are about 20 ms and 5 mm. Additional variability arises from individual movements being planned slightly differently and being adjusted during execution. We argue that the way that our subjects moved was precisely tailored to the task demands, and that the movement accuracy is not only limited by the muscles and their activation, but also--and probably even mainly--by the resolution of visual perception.

People take account of the variability in their movements in a near-optimal manner in various visuo-motor tasks. Is knowledge of one’s variability needed for such near-optimal performance, or could it arise from responding to one’s success in previous attempts in some simple manner? We asked subjects to move a pen back and forth across a tablet to make a cursor move as quickly as possible between two targets. The cursor had to stop within the targets. Task difficulty was varied between blocks. Part of the variation in difficulty was explicit (three target sizes) whereas the rest had to be discovered during the movements (two mappings between the movements of pen and cursor). In all cases, subjects sped up after stopping within a target and slowed down after failing to do so. We interpret this as evidence that explicit knowledge of one’s variability is not necessary for performing close to optimally.

In the companion paper utilizing a quantitative model of optimal motor coordination (Part I, Rand and Shimansky, in Exp Brain Res 225:55–73, 2013 ), we examined coordination between X and Y movement directions (XYC) during reaching movements performed under three prescribed speeds, two movement amplitudes, and two target sizes. The obtained results indicated that the central nervous system (CNS) utilizes a two-phase strategy, where the initial and the final phases correspond to lower and higher precision of information processing, respectively, for controlling goal-directed reach-type movements to optimize the total cost of task performance including the cost of neural computations. The present study investigates how two different well-known concepts used for describing movement performance relate to the concepts of optimal XYC and two-phase control strategy. First, it is examined to what extent XYC is equivalent to movement trajectory straightness. The data analysis results show that the variability, the movement trajectory’s deviation from the straight line, increases with an increase in prescribed movement speed. In contrast, the dependence of XYC strength on movement speed is opposite (in total agreement with an assumption of task performance optimality), suggesting that XYC is a feature of much higher level of generality than trajectory straightness. Second, it is tested how well the ballistic and the corrective components described in the traditional concept of two-component model of movement performance match with the initial and the final phase of the two-phase control strategy, respectively. In fast reaching movements, the percentage of trials with secondary corrective submovement was smaller under larger-target shorter-distance conditions. In slower reaching movements, meaningful parsing was impossible due to massive fluctuations in the kinematic profile throughout the movement. Thus, the parsing points determined by the conventional submovement analysis did not consistently reflect separation between the ballistic and error-corrective components. In contrast to the traditional concept of two-component movement performance, the concept of two-phase control strategy is applicable to a wide variety of experimental conditions.

A quantitative model of optimal coordination between hand transport and grip aperture has been derived in our previous studies of reach-to-grasp movements without utilizing explicit knowledge of the optimality criterion or motor plant dynamics. The model’s utility for experimental data analysis has been demonstrated. Here we show how to generalize this model for a broad class of reaching-type, goal-directed movements. The model allows for measuring the variability of motor coordination and studying its dependence on movement phase. The experimentally found characteristics of that dependence imply that execution noise is low and does not affect motor coordination significantly. From those characteristics it is inferred that the cost of neural computations required for information acquisition and processing is included in the criterion of task performance optimality as a function of precision demand for state estimation and decision making. The precision demand is an additional optimized control variable that regulates the amount of neurocomputational resources activated dynamically. It is shown that an optimal control strategy in this case comprises two different phases. During the initial phase, the cost of neural computations is significantly reduced at the expense of reducing the demand for their precision, which results in speed-accuracy tradeoff violation and significant inter-trial variability of motor coordination. During the final phase, neural computations and thus motor coordination are considerably more precise to reduce the cost of errors in making a contact with the target object. The generality of the optimal coordination model and the two-phase control strategy is illustrated on several diverse examples.

This paper investigates the effects of fixed versus flexible exchange rates on firms' location choices and on countries' specialization patterns. In a two-country, two-differentiated-goods monetary model, demand, supply, and monetary (as well as exchange rate) shocks arise after wages are set and prices are optimally chosen. The paper finds that countries are more specialized under flexible than fixed rates, and that the pattern of specialization is not uniquely defined by trade models but depends also on the exchange rate regime. The adoption of fixed exchange rates endogenously increases the desirability of this currency area by reducing the shock asymmetry. These results also shed light on the effects of exchange rate variability on trade.