Task-level Variables Research Articles

Are inter-limb differences in change of direction velocity and angle associated with inter-limb differences in kinematics and kinetics following anterior cruciate ligament reconstruction?

BackgroundQuantifying inter-limb differences in kinematics and kinetics during change of direction is proposed as a means of monitoring rehabilitation following anterior cruciate ligament reconstruction (ACLR). Velocity and centre of mass (CoM) deflection angle are fundamental task descriptors that influence kinematics and kinetics during change of direction. Inter-limb differences in approach velocity and CoM deflection angle have been identified following ACLR and may contribute to the presence of inter-limb differences in kinematics and kinetics during change of direction. Research questionThe aim of this study was to quantify the proportion of variance in kinematic and kinetic inter-limb differences attributable to inter-limb differences in approach velocity and centre of mass deflection angle during a change of direction task. MethodsA cohort of 192 patients (male, 23.8 ± 3.6 years, 6.3 ± 0.4 months post primary ACLR) completed a pre-planned 90° change of direction task on both their operated and non-operated limb. Inter-limb differences in approach velocity and CoM deflection angle were calculated alongside lower-extremity kinematic and kinetic variables. The relationship between inter-limb differences in task-level variables and inter-limb differences in kinematic and kinetic variables was examined using linear regression models. Kinematic and kinetic inter-limb differences were adjusted for inter-limb differences in approach velocity and CoM deflection angle. Adjusted and unadjusted inter-limb differences were submitted to one sample t-tests. ResultsInter-limb differences in approach velocity and centre of mass deflection angle explained 3 – 60% of the variance in kinematic and kinetic inter-limb differences. Statistical inferences remained consistent between adjusted and unadjusted conditions with the exception of hip flexion angle. SignificanceInter-limb differences in task-level features explain a large proportion of the variance in inter-limb differences in several kinematic and kinetic variables. Accounting for this variation reduced the magnitude of kinematic and kinetic inter-limb differences comparable to those previously observed in normative cohorts.

Adaptive Pincer Grasping of Soft Pneumatic Grippers Based on Object Stiffness for Modellable and Controllable Grasping Quality

In this study, adaptive pincer grasping of soft pneumatic grippers (SPGs) is considered, and we propose how the performance of soft pneumatic actuators (SPAs) and the stiffness of grasped objects can be accounted for in modeling and control. The grasping kinetics was analyzed. The connection between grasping quality and SPA performance is discussed. We also devised a subjective definition of grasping quality due to SPA performance. A modeling technique was established, which makes dominant factors of grasping quality due to the SPA performance predictable over the gripper input. Later, a control architecture was developed. This architecture demonstrates how the grasping is implemented. The modeling technique was used to forecast grasping quality due to the SPA performance and its factors. An experiment was conducted to obtain actual results. The predicted and actual results were correspondingly compared. The results show minute deviation, thereby validating the reliability of the grasping. This study clarifies the association between grasping quality and SPA performance and contributes an advancement toward modellable and controllable task-level variables, such as grasping quality, in SPG pincer grasping.

Synergistic control of hand position, velocity, and acceleration fluctuates across time during simulated Nordic skiing

A central application of Uncontrolled Manifold (UCM) analysis is the quantification of the presence of motor synergies for the control of task-level variables during human movement. Choosing which task-level variable to analyse is a critical step in UCM analyses because this choice determines a relationship linking the motor performance and motor control. End-effector and/or centre of mass position are frequently chosen as task-level variables, whereas velocity and acceleration receive relatively little attention in this regard. Additionally, UCM analyses are most often conducted on discrete time points of a movement cycle, although these singular time points do not necessarily represent the characteristics of the whole cycle. Accordingly, the purpose of this investigation was to explore synergistic hand control during simulated Nordic skiing. It was hypothesized that 1) hand velocity would be a controlled task-level variable, 2) hand position would not be a controlled task-level variable, and 3) synergistic control of hand kinematics would be fluid (not constant throughout the movement cycle). Seven varsity-level skiers completed a simulated Nordic skiing task, producing specified power outputs on a Nordic skiing ergometer. Normalized time series of indices of task control from UCM analyses were analyzed using statistical parametric mapping. Synergies were observed for all of position, velocity, and acceleration (p < 0.0001), but not for the entire- skiing cycle. Therefore, UCM analyses conducted on discrete time points are not recommended without suitable a priori justification because its outputs fluctuate across time- especially during continuous movements. Velocity and acceleration should be considered in the choice of task-level variables, especially if they help define task performance.

Öğrenenlerin E-Değerlendirmeye Dayalı Kişiselleştirilmiş Geri Bildirim Yollarının İncelenmesi

Purpose: The purpose of the research is to investigate personalized feedback paths of learners based on e-assessment according to the feedback preferences of learners and their needs. Methodology: The design-based research method consisting of two stages was used in this study. The study group comprised of 36 undergraduates in the department of Computer and Instructional Technology in the Education Faculty in one of the state universities was determined based on criterion sampling method. The data collection process has carried out with the same study group at both design stages by using blended learning method. Data collection tools are consisted of Motivation and Metacognition scales, learning management system records and semi-structured interview form. The descriptive analysis methods, Chi-Square independence test, multiple correspondence analysis, and content analysis have been used for data analysis. Findings: According to the findings of the research, the effect of test anxiety and extrinsic goal orientation from motivation sources, metacognition, the judgment of learning and task level variables have determined on feedback preferences of the learner. Classify by these characteristics, a number of personalized feedback strategies have been developed based on the learner's preferences and needs for feedback. In addition, it was found that learners wanted to get feedback from teachers rather than peers because they found teacher’s feedback more qualified and they did not trust their peers' feedback. Highlights: In order to use the personalized feedback strategies developed in the research in different research groups and training programs, it should be important that the system is similar to those in this study. These should be similar systems that determine both the learner's preference and the needs for feedback according to the learner characteristics to support learning performance. Otherwise, it is thought that will be out of the context of personalization.

Similar sensorimotor transformations control balance during standing and walking.

Standing and walking balance control in humans relies on the transformation of sensory information to motor commands that drive muscles. Here, we evaluated whether sensorimotor transformations underlying walking balance control can be described by task-level center of mass kinematics feedback similar to standing balance control. We found that delayed linear feedback of center of mass position and velocity, but not delayed linear feedback from ankle angles and angular velocities, can explain reactive ankle muscle activity and joint moments in response to perturbations of walking across protocols (discrete and continuous platform translations and discrete pelvis pushes). Feedback gains were modulated during the gait cycle and decreased with walking speed. Our results thus suggest that similar task-level variables, i.e. center of mass position and velocity, are controlled across standing and walking but that feedback gains are modulated during gait to accommodate changes in body configuration during the gait cycle and in stability with walking speed. These findings have important implications for modelling the neuromechanics of human balance control and for biomimetic control of wearable robotic devices. The feedback mechanisms we identified can be used to extend the current neuromechanical models that lack balance control mechanisms for the ankle joint. When using these models in the control of wearable robotic devices, we believe that this will facilitate shared control of balance between the user and the robotic device.

Feature-Selective Attentional Modulations in Human Frontoparietal Cortex

Control over visual selection has long been framed in terms of a dichotomy between "source" and "site," where top-down feedback signals originating in frontoparietal cortical areas modulate or bias sensory processing in posterior visual areas. This distinction is motivated in part by observations that frontoparietal cortical areas encode task-level variables (e.g., what stimulus is currently relevant or what motor outputs are appropriate), while posterior sensory areas encode continuous or analog feature representations. Here, we present evidence that challenges this distinction. We used fMRI, a roving searchlight analysis, and an inverted encoding model to examine representations of an elementary feature property (orientation) across the entire human cortical sheet while participants attended either the orientation or luminance of a peripheral grating. Orientation-selective representations were present in a multitude of visual, parietal, and prefrontal cortical areas, including portions of the medial occipital cortex, the lateral parietal cortex, and the superior precentral sulcus (thought to contain the human homolog of the macaque frontal eye fields). Additionally, representations in many-but not all-of these regions were stronger when participants were instructed to attend orientation relative to luminance. Collectively, these findings challenge models that posit a strict segregation between sources and sites of attentional control on the basis of representational properties by demonstrating that simple feature values are encoded by cortical regions throughout the visual processing hierarchy, and that representations in many of these areas are modulated by attention. Influential models of visual attention posit a distinction between top-down control and bottom-up sensory processing networks. These models are motivated in part by demonstrations showing that frontoparietal cortical areas associated with top-down control represent abstract or categorical stimulus information, while visual areas encode parametric feature information. Here, we show that multivariate activity in human visual, parietal, and frontal cortical areas encode representations of a simple feature property (orientation). Moreover, representations in several (though not all) of these areas were modulated by feature-based attention in a similar fashion. These results provide an important challenge to models that posit dissociable top-down control and sensory processing networks on the basis of representational properties.

The motor and the brake of the trailing leg in human walking: leg force control through ankle modulation and knee covariance.

Human walking is a complex task, and we lack a complete understanding of how the neuromuscular system organizes its numerous muscles and joints to achieve consistent and efficient walking mechanics. Focused control of select influential task-level variables may simplify the higher-level control of steady-state walking and reduce demand on the neuromuscular system. As trailing leg power generation and force application can affect the mechanical efficiency of step-to-step transitions, we investigated how joint torques are organized to control leg force and leg power during human walking. We tested whether timing of trailing leg force control corresponded with timing of peak leg power generation. We also applied a modified uncontrolled manifold analysis to test whether individual or coordinated joint torque strategies most contributed to leg force control. We found that leg force magnitude was adjusted from step to step to maintain consistent leg power generation. Leg force modulation was primarily determined by adjustments in the timing of peak ankle plantar-flexion torque, while knee torque was simultaneously covaried to dampen the effect of ankle torque on leg force. We propose a coordinated joint torque control strategy in which the trailing leg ankle acts as a motor to drive leg power production while trailing leg knee torque acts as a brake to refine leg power production.

Their teacher can't be an app: Preschoolers' listening comprehension of digital storybooks

This study sought to determine the relationship among student- and task-level variables at play in the digital storybook listening experiences of 130 English-speaking preschoolers at risk of reading failure. Specifically, this study investigated the relationship among the (1) features of computer-based electronic storybooks, (2) preschoolers' competency in the task environment, and (3) preschoolers' background knowledge with respect to listening comprehension outcomes following a single digital storybook listening experience. The results indicate significant and strong relationships among the three variables under investigation and their consequent understanding of the digital storybook (i.e. explicit and implicit/inferential content related to the plot). The preschoolers' topic knowledge was the best predictor of comprehension. In addition, the interaction between the features of the e-book and the preschoolers' competency in the task environment also significantly predicted the outcome.

Long-latency muscle activity reflects continuous, delayed sensorimotor feedback of task-level and not joint-level error

In both the upper and lower limbs, evidence suggests that short-latency electromyographic (EMG) responses to mechanical perturbations are modulated based on muscle stretch or joint motion, whereas long-latency responses are modulated based on attainment of task-level goals, e.g., desired direction of limb movement. We hypothesized that long-latency responses are modulated continuously by task-level error feedback. Previously, we identified an error-based sensorimotor feedback transformation that describes the time course of EMG responses to ramp-and-hold perturbations during standing balance (Safavynia and Ting 2013; Welch and Ting 2008, 2009). Here, our goals were 1) to test the robustness of the sensorimotor transformation over a richer set of perturbation conditions and postural states; and 2) to explicitly test whether the sensorimotor transformation is based on task-level vs. joint-level error. We developed novel perturbation trains of acceleration pulses such that perturbations were applied when the body deviated from the desired, upright state while recovering from preceding perturbations. The entire time course of EMG responses (∼4 s) in an antagonistic muscle pair was reconstructed using a weighted sum of center of mass (CoM) kinematics preceding EMGs at long-latency delays (∼100 ms). Furthermore, CoM and joint kinematic trajectories became decorrelated during perturbation trains, allowing us to explicitly compare task-level vs. joint feedback in the same experimental condition. Reconstruction of EMGs was poorer using joint kinematics compared with CoM kinematics and required unphysiologically short (∼10 ms) delays. Thus continuous, long-latency feedback of task-level variables may be a common mechanism regulating long-latency responses in the upper and lower limbs.

Review and perspective: neuromechanical considerations for predicting muscle activation patterns for movement

Muscle coordination may be difficult or impossible to predict accurately based on biomechanical considerations alone because of redundancy in the musculoskeletal system. Because many solutions exist for any given movement, the role of the nervous system in further constraining muscle coordination patterns for movement must be considered in both healthy and impaired motor control. On the basis of computational neuromechanical analyses of experimental data combined with modeling techniques, we have demonstrated several such neural constraints on the temporal and spatial patterns of muscle activity during both locomotion and postural responses to balance perturbations. We hypothesize that subject-specific and trial-by-trial differences in muscle activation can be parameterized and understood by a hierarchical and low-dimensional framework that reflects the neural control of task-level goals. In postural control, we demonstrate that temporal patterns of muscle activity may be governed by feedback control of task-level variables that represent the overall goal-directed motion of the body. These temporal patterns then recruit spatially-fixed patterns of muscle activity called muscle synergies that produce the desired task-level biomechanical functions that require multijoint coordination. Moreover, these principles apply more generally to movement, and in particular to locomotor tasks in both healthy and impaired individuals. Overall, understanding the goals and organization of the neural control of movement may provide useful reduced dimension parameter sets to address the degrees-of-freedom problem in musculoskeletal movement control. More importantly, however, neuromechanical analyses may lend insight and provide a framework for understanding subject-specific and trial-by-trial differences in movement across both healthy and motor-impaired populations.

Optimization of muscle activity for task-level goals predicts complex changes in limb forces across biomechanical contexts.

Optimality principles have been proposed as a general framework for understanding motor control in animals and humans largely based on their ability to predict general features movement in idealized motor tasks. However, generalizing these concepts past proof-of-principle to understand the neuromechanical transformation from task-level control to detailed execution-level muscle activity and forces during behaviorally-relevant motor tasks has proved difficult. In an unrestrained balance task in cats, we demonstrate that achieving task-level constraints center of mass forces and moments while minimizing control effort predicts detailed patterns of muscle activity and ground reaction forces in an anatomically-realistic musculoskeletal model. Whereas optimization is typically used to resolve redundancy at a single level of the motor hierarchy, we simultaneously resolved redundancy across both muscles and limbs and directly compared predictions to experimental measures across multiple perturbation directions that elicit different intra- and interlimb coordination patterns. Further, although some candidate task-level variables and cost functions generated indistinguishable predictions in a single biomechanical context, we identified a common optimization framework that could predict up to 48 experimental conditions per animal (n = 3) across both perturbation directions and different biomechanical contexts created by altering animals' postural configuration. Predictions were further improved by imposing experimentally-derived muscle synergy constraints, suggesting additional task variables or costs that may be relevant to the neural control of balance. These results suggested that reduced-dimension neural control mechanisms such as muscle synergies can achieve similar kinetics to the optimal solution, but with increased control effort (≈2×) compared to individual muscle control. Our results are consistent with the idea that hierarchical, task-level neural control mechanisms previously associated with voluntary tasks may also be used in automatic brainstem-mediated pathways for balance.

Short-Term Effects of Muscular Denervation and Fasciotomy on Global Limb Variables during Locomotion in the Decerebrate Cat

The motor system is capable of preserving the trajectories during locomotion of task level variables such as limb length and limb orientation in the face of paralysis of major muscle groups. This compensation is accomplished by the adjustment of the kinematics of joints other than the one most affected by the paralysis. The conservation of these task level variables could be accomplished quickly by feedback regulation or intrinsic mechanics, or by a longer-term adaptive process. We investigated the immediate effects of denervation of the triceps surae muscles in one limb of stepping, decerebrate cats to determine whether task level variables were preserved by short-term regulatory or intrinsic mechanisms. We further investigated the effects of disruption of the crural fascia in conjunction with denervation of the triceps surae muscles to determine whether the system consisting of multi-articular muscles of the thigh and crural fascia provided some contribution toward the preservation of limb length and orientation. Denervation led to substantial increases in ankle yield during stance, as previously observed, but also to significant decreases in limb length during early stance. Disruption of the crural fascia did not lead to increased ankle yield but, instead, to evidence for decreased propulsion. The results suggest that the preservation of task level variables observed in other studies does not result from online error correction or intrinsic properties of the musculoskeletal system but, by inference, from longer-term neural adaptation.

Mental Practice in the Intermanual Transfer of Motor Skills

The current study compared intermanual transfer for two different handwriting tasks (familiar letters and novel symbols), following both mental and physical practice. There was substantial transfer from practice with the dominant hand to the nondominant one in both time to produce a character and size of the character produced, but there was no transfer in the reverse direction (even for novel symbols). Most importantly, there was significant transfer as a result of mental practice in production time comparable to physical practice. However, there was no transfer from mental practice when measuring character size. During mental practice, task-level variables still had significant effects whereas effector-level variables did not. Thus, asymmetrical transfer as a result of mental practice is posited to result from the transfer of task-level processes but not effector-level processes.

Optimal sensorimotor transformations for balance

Here we have identified a sensorimotor transformation that is used by a mammalian nervous system to produce a multijoint motor behavior. Using a simple biomechanical model, a delayed-feedback rule based on an optimal tradeoff between postural error and neural effort explained patterns of muscle activation in response to a sudden loss of balance in cats. Following the loss of large sensory afferents, changes in these muscle-activation patterns reflected an optimal reweighting of sensory feedback gains to minimize postural instability. Specifically, a loss of center-of-mass-acceleration information, which allowed for a rapid initial rise in the muscle activity in intact animals, was absent after large-fiber sensory neuropathy. Our results demonstrate that a simple and flexible neural feedback control strategy coordinates multiple muscles over time via a small set of extrinsic, task-level variables during complex multijoint natural movements.

Dimensional reduction in sensorimotor systems: a framework for understanding muscle coordination of posture

The simple act of standing up is an important and essential motor behavior that most humans and animals achieve with ease. Yet, maintaining standing balance involves complex sensorimotor transformations that must continually integrate a large array of sensory inputs and coordinate multiple motor outputs to muscles throughout the body. Multiple, redundant local sensory signals are integrated to form an estimate of a few global, task-level variables important to postural control, such as body center of mass (CoM) position and body orientation with respect to Earth-vertical. Evidence suggests that a limited set of muscle synergies, reflecting preferential sets of muscle activation patterns, are used to move task-variables such as CoM position in a predictable direction following postural perturbations. We propose a hierarchical feedback control system that allows the nervous system the simplicity of performing goal-directed computations in task-variable space, while maintaining the robustness afforded by redundant sensory and motor systems. We predict that modulation of postural actions occurs in task-variable space, and in the associated transformations between the low-dimensional task-space and high-dimensional sensor and muscle spaces. Development of neuromechanical models that reflect these neural transformations between low- and high-dimensional representations will reveal the organizational principles and constraints underlying sensorimotor transformations for balance control, and perhaps motor tasks in general. This framework and accompanying computational models could be used to formulate specific hypotheses about how specific sensory inputs and motor outputs are generated and altered following neural injury, sensory loss, or rehabilitation.