General Muscle Torque Generator Model for a Two Degree-of-Freedom Shoulder Joint

Muscle torque generators (MTGs) have been developed as an alternative to muscle-force models, reducing the muscle-force model complexity to a single torque at the joint. Current MTGs can only be applied to single Degree-of-freedom (DoF) joints, leading to complications in modeling joints with multiple-DoFs such as the shoulder. This study aimed to develop an MTG model that accounts for the coupling between 2-DoF at the shoulder joint: shoulder plane of elevation (horizontal abduction/adduction) and shoulder elevation (flexion/extension). Three different 2-DoF MTG equations were developed to model the coupling between these two movements. Net joint torques at the shoulder were determined for 20 participants (10 females and 10 males) in isometric, isokinetic, and passive tests. Curve and surface polynomial fitting were used to find the best general fit for the experimental data in terms of the different degrees of coupling. The models were validated against experimental isokinetic torque data. It was determined that implicit coupling that used interpolation between single-DoF MTGs resulted in the lowest root-mean-square percent error of 8.5%. The work demonstrated that general MTG models can predict torque results that are dependent on multiple-DoFs of the shoulder.

Evolution, biomechanics, and neurobiology converge to explain selective finger motor control

Humans use their fingers to perform a variety of tasks, from simple grasping to manipulating objects, to typing and playing musical instruments, a variety wider than any other species. The more sophisticated the task, the more it involves individuated finger movements, those in which one or more selected fingers perform an intended action while the motion of other digits is constrained. Here we review the neurobiology of such individuated finger movements. We consider their evolutionary origins, the extent to which finger movements are in fact individuated, and the evolved features of neuromuscular control that both enable and limit individuation. We go on to discuss other features of motor control that combine with individuation to create dexterity, the impairment of individuation by disease, and the broad extent of capabilities that individuation confers on humans. We comment on the challenges facing the development of a truly dexterous bionic hand. We conclude by identifying topics for future investigation that will advance our understanding of how neural networks interact across multiple regions of the central nervous system to create individuated movements for the skills humans use to express their cognitive activity.

Mu-ERD reflects action understanding, but the effect is small

Since the mid-2000's, many researchers have provided evidence that mu-ERD measured at the motor cortex may reflect the collective activation of upstream brain regions associated with the human mirror system during action observation paradigms; however, several recent papers have called these findings into question. Our study represents an effort to address these criticisms. In our study, participants watched videos in which the type of grip an actor used to grasp a coffee mug either conveyed the goal with 100 % certainty (unambiguous-goal trials), or offered no predictive information (ambiguous-goal trials). If mu-ERD indexes action understanding, then we predicted that mu-ERD should increase while participants watched the actor grasp the mug for unambiguous-goal trials, but not for ambiguous-goal trials. During the intervals where participants watched the actor execute the goal, mu-ERD for unambiguous-goal trials should remain steady, whereas mu-ERD for ambiguous-goal trials should now increase. Conversely, if mu-ERD does not index action understanding, and instead reflects general motor processes associated with action (such as the activation of population vectors in M1 or planning processes), then mu-ERD should show no difference across conditions. Across most comparisons, we found that mu-ERD mostly reflected general motor processes; however, there was a small effect when participants overserved unambiguous-goal trials while watching the actor execute the goal suggesting that mu-ERD does reflect mirroring, but the effect is small.

Evaluation of antigravitational support levels provided by a passive upper-limb occupational exoskeleton in repetitive arm movements

Upper-limb occupational exoskeletons to support the workers' upper arms are typically designed to provide antigravitational support. Although typical work activities require workers to perform static and dynamic actions, the majority of the studies in literature investigated the effects of upper-limb occupational exoskeletons in static and quasi-static activities, while only a few works focused on dynamic tasks. This article presents a systematic evaluation of the effects of different levels of antigravitational support (from about 60% to 100% of the arm gravitational load) provided by a passive upper-limb occupational exoskeleton on muscles' activity during repetitive arm movements. The effect of the exoskeleton on muscle activity was evaluated by the comparison of muscle activations with and without the exoskeleton. The average muscle activation was computed considering shoulder full flexion-extension cycles, and sub-movements, namely the arm-lifting (i.e., flexion) and arm-lowering (i.e., extension) movements. Results showed a quasi-linear correlation between antigravitational support and muscle activity reductions, both when considering the full flexion-extension cycle and in the arm-lifting movement (reductions were up to 64 and 61% compared to not wearing the exoskeleton, respectively). When considering the arm-lowering movement, providing antigravitational support close to or higher than 100% of the arm gravitational load led to increased muscle activations of the extensors (up to 127%), suggesting that such an amount of antigravitational support may be not effective for a complete biomechanical load reduction on the shoulder district in dynamic tasks.

Evaluating peripheral neuromuscular function with brief movement-evoked pain

Movement-evoked pain is an understudied manifestation of musculoskeletal conditions that contributes to disability, yet little is known about how the neuromuscular system responds to movement-evoked pain. The present study examined whether movement-evoked pain impacts force production, electromyographic (EMG) muscle activity, and the rate of force development (RFD) during submaximal muscle contractions. Fifteen healthy adults (9 males; age = 30.3 ± 10.2 yr, range = 22-59 yr) performed submaximal isometric first finger abduction contractions without pain (baseline) and with movement-evoked pain induced by laser stimulation to the dorsum of the hand. Normalized force (% maximal voluntary contraction) and RFD decreased by 11% (P < 0.001) and 15% (P = 0.003), respectively, with movement-evoked pain, without any change in normalized peak EMG (P = 0.77). Early contractile RFD, force impulse, and corresponding EMG amplitude computed within time segments of 50, 100, 150, and 200 ms relative to the onset of movement were also unaffected by movement-evoked pain (P > 0.05). Our results demonstrate that movement-evoked pain impairs peak characteristics and not early measures of submaximal force production and RFD, without affecting EMG activity (peak and early). Possible explanations for the stability in EMG with reduced force include antagonist coactivation and a reorganization of motoneuronal activation strategy, which is discussed here.NEW & NOTEWORTHY We provide neurophysiological evidence to indicate that peak force and rate of force development are reduced by movement-evoked pain despite a lack of change in EMG and early rapid force development in the first dorsal interosseous muscle. Additional evidence suggests that these findings may coexist with a reorganization in motoneuronal activation strategy.

Comparison of Spectral Analysis of Gamma Band Activity During Actual and Imagined Movements as a Cognitive Tool

Background. Imagined motor movement is a cognitive process in which a subject imagines a movement without doing it, which activates similar brain regions as during actual motor movement. Brain gamma band activity (GBA) is linked to cognitive functions such as perception, attention, memory, awareness, synaptic plasticity, motor control, and Imagination. Motor imagery can be used in sports to improve performance, raising the possibility of using it as a rehabilitation method through brain plasticity through mirror neurons. Method. A comparative observational study was conducted on 56 healthy male subjects after obtaining clearance from the Ethics Committee. EEG recordings for GBA were taken for resting, real, and imaginary motor movements and compared. The power spectrum of gamma waves was analyzed using the Kruskal-Wallis test; a p-value <.05 was considered significant. Results. The brain gamma rhythm amplitude was statistically increased during both actual and imaginary motor movement compared to baseline (resting stage) in most of the regions of the brain except the occipital region. There was no significant difference in GBA between real and imaginary movements. Conclusions. Increased gamma rhythm amplitude during both actual and imaginary motor movement than baseline (resting stage) indicating raised brain cognitive activity during both types of movements. There was no potential difference between real and imaginary movements suggesting that the real movement can be replaced by the imaginary movement to enhance work performance through mirror therapy.

Collective search in ants: Movement determines footprints, and footprints influence movement

Collectively searching animals might be expected to coordinate with their groupmates to cover ground more evenly or efficiently than uncoordinated groups. Communication can lead to coordination in many ways. Previous work in ants suggests that chemical 'footprints', left behind by individuals as they walk, might serve this function by modulating the movement patterns of following ants. Here, we test this hypothesis by considering the two predictions that, first, ants may turn away from sites with higher footprint concentrations (klinotaxis), or, second, that they may change their turning patterns depending on the presence of footprints (klinokinesis). We tracked 5 whole colonies of Temnothorax rugatulus ants in a large arena over 5h. We approximated the footprint concentration by summing ant visitations for each point in the arena and calculated the speed and local path straightness for each point of the ant trajectories. We counterintuitively find that ants walk slightly faster and straighter in areas with fewer footprints. This is partially explained by the effect that ants who start out from the nest walking straighter move on average further away from the nest, where there are naturally fewer footprints, leading to an apparent relationship between footprint density and straightness However, ants walk slightly faster and straighter off footprints even when controlling for this effect. We tested for klinotaxis by calculating the footprint concentrations perceived by the left and right antennae of ants and found no evidence for a turning-away (nor turning-towards) behavior. Instead, we found noticeable effects of environmental idiosyncrasies on the behavior of ants which are likely to overpower any reactions to pheromones. Our results indicate that search density around an ant colony is affected by several independent processes, including individual differences in movement pattern, local spatial heterogeneities, and ants' reactions to chemical footprints. The multitude of effects illustrates that non-communicative coordination, individual biases and interactions with the environment might have a greater impact on group search efficiency and exploratory movements than pheromone communication.

The digital motor output: a conceptual framework for a meaningful clinical performance metric for a motor neuroprosthesis

In recent years, the majority of the population has become increasingly reliant on continuous and independent control of smart devices to conduct activities of daily living. Upper extremity movement is typically required to generate the motor outputs that control these interfaces, such as rapidly and accurately navigating and clicking a mouse, or activating a touch screen. For people living with tetraplegia, these abilities are lost, significantly compromising their ability to interact with their environment. Implantable brain computer interfaces (BCIs) hold promise for restoring lost neurologic function, including motor neuroprostheses (MNPs). An implantable MNP can directly infer motor intent by detecting brain signals and transmitting the motor signal out of the brain to generate a motor output and subsequently control computer actions. This physiological function is typically performed by the motor neurons in the human body. To evaluate the use of these implanted technologies, there is a need for an objective measurement of the effectiveness of MNPs in restoring motor outputs. Here, we propose the concept of digital motor outputs (DMOs) to address this: a motor output decoded directly from a neural recording during an attempted limb or orofacial movement is transformed into a command that controls an electronic device. Digital motor outputs are diverse and can be categorized as discrete or continuous representations of motor control, and the clinical utility of the control of a single, discrete DMO has been reported in multiple studies. This sets the stage for the DMO to emerge as a quantitative measure of MNP performance.

Computational study of extrinsic factors affecting ACL strain during single-leg jump landing

BACKGROUND

Non-contact anterior cruciate ligament (ACL) injuries are a major concern in sport-related activities due to dynamic knee movements. There is a paucity of finite element (FE) studies that have accurately replicated the knee geometry, kinematics, and muscle forces during dynamic activities. The objective of this study was to develop and validate a knee FE model and use it to quantify the relationships between sagittal plane knee kinematics, kinetics and the resulting ACL strain.

METHODS

3D images of a cadaver knee specimen were segmented (bones, cartilage, and meniscus) and meshed to develop the FE model. Knee ligament insertion sites were defined in the FE model via experimental digitization of the specimen's ligaments. The response of the model was validated against multiple physiological knee movements using published experimental data. Single-leg jump landing motions were then simulated on the validated model with muscle forces and kinematic inputs derived from motion capture and rigid body modelling of ten participants.

RESULTS

The maximum ACL strain measured with the model during jump landing was 3.5 ± 2.2%, comparable to published experimental results. Bivariate analysis showed no significant correlation between body weight, ground reaction force and sagittal plane parameters (such as joint flexion angles, joint moments, muscle forces, and joint velocity) and ACL strain. Multivariate regression analysis showed increasing trunk, hip and ankle flexion angles decreases ACL strain (R2 = 90.04%, p < 0.05).

CONCLUSIONS

Soft landing decreases ACL strain and the relationship could be presented through an empirical equation. The model and the empirical relation developed in this study could be used to better predict ACL injury risk and prevention strategies during dynamic activities.

Does movement preparation enhance attending to bodily sensations in the back in people with persistent low back pain?

Attention has been proposed to play an important role in persisting pain, with excessive attentional processes towards pain information leading to worse pain outcomes and maladaptive behaviors. Nevertheless, research on somatosensory attending during the anticipation of pain-related movements is still scarce. This study investigated if individuals with chronic and recurrent lower back pain compared to pain-free controls, show enhanced attending to somatosensory information in the back while anticipating back-recruiting movements. 43 healthy control, 33 recurrent (RLBP) and 33 chronic low back (CLBP) pain sufferers were asked to perform back-recruiting movements. Before the movement initiation cue, a task-irrelevant tactile stimulus was administered to participants' lower back to elicit somatosensory evoked potentials (SEPs), used as an index of somatosensory attending. In contrast to our hypothesis, most identified SEP components did not differ across groups. The only exception was the P175 amplitude which was larger for the CLBP group compared to individuals with RLBP and healthy controls. The current study did not find robust evidence of enhanced somatosensory attending to the back in people with persisting lower back pain. The finding that CLBP, but not RLBP individuals, had larger amplitudes to the P175 component, is discussed as possibly reflecting a higher state of emotional arousal in these patients when having to prepare the back-recruiting movements.

Prechtl's method to assess general movements: Inter-rater reliability during the preterm period

INTRODUCTION

Prechtl's method (GMA) is a test for the functional assessment of the young nervous system. It involves a global and a detailed assessment of the general movements (GMs) and has demonstrated validity. Data on the reliability of both assessments in the preterm period are scarce. This study aimed to evaluate the inter-rater reliability for the global and detailed assessments of the preterm writhing GMA.

MATERIALS AND METHODS

The study participants were 69 infants born at <37 gestational weeks and admitted to the neonatal intensive care unit. They were randomly assigned to five pairs of raters. Raters assessed infants' GMs using preterm videos. Outcome variables were (a) the GMs classification (normal versus abnormal; normal versus abnormal subcategories) and (b) the general movements optimality score (GMOS), obtained through the global and detailed assessments. The Gwet's AC1 and the intraclass correlation coefficient (ICC) were calculated for the GMs classification and the GMOS, respectively.

RESULTS

The global assessment presented an AC1 = 0.84 [95% CI = 0.54,1] for the GMs binary classification and an AC1 = 0.67 [95% CI = 0.38,0.89] for the GMs classification with abnormal subcategories. The detailed assessment presented an ICC = 0.72 [95% CI = 0.39,0.90] for the GMOS.

CONCLUSIONS

Inter-rater reliability was high and substantial for the global assessment and good for the detailed assessment. However, the small sample size limited the precision of these estimates. Future research should involve larger samples of preterm infants to improve estimate precision. Challenging items such as assessing the neck and trunk, poor repertoire GMs, and tremulous movements may impact the preterm writhing GMA's inter-rater reliability. Therefore, ongoing training and calibration among raters is necessary. Further investigation in clinical settings can enhance our understanding of the preterm writhing GMA's reliability.

Affordances for throwing: An uncontrolled manifold analysis

Movement systems are massively redundant, and there are always multiple movement solutions to any task demand; motor abundance. Movement consequently exhibits 'repetition without repetition', where movement outcomes are preserved but the kinematic details of the movement vary across repetitions. The uncontrolled manifold (UCM) concept is one of several methods that analyses movement variability with respect to task goals, to quantify repetition without repetition and test hypotheses about the control architecture producing a given abundant response to a task demand. However, like all these methods, UCM is under-constrained in how it decomposes a task and performance. In this paper, we propose and test a theoretical framework for constraining UCM analysis, specifically the perception of task-dynamical affordances. Participants threw tennis balls to hit a target set at 5m, 10m or 15m, and we performed UCM analysis on the shoulder-elbow-wrist joint angles with respect to variables derived from an affordance analysis of this task as well as more typical biomechanical variables. The affordance-based UCM analysis performed well, although data also showed thrower dynamics (effectivities) need to be accounted for as well. We discuss how the theoretical framework of affordances and affordance-based control can be connected to motor abundance methods in the future.

A six degrees-of-freedom cable-driven robotic platform for head-neck movement

This paper introduces a novel cable-driven robotic platform that enables six degrees-of-freedom (DoF) natural head-neck movements. Poor postural control of the head-neck can be a debilitating symptom of neurological disorders such as amyotrophic lateral sclerosis and cerebral palsy. Current treatments using static neck collars are inadequate, and there is a need to develop new devices to empower movements and facilitate physical rehabilitation of the head-neck. State-of-the-art neck exoskeletons using lower DoF mechanisms with rigid linkages are limited by their hard motion constraints imposed on head-neck movements. By contrast, the cable-driven robot presented in this paper does not constrain motion and enables wide-range, 6-DoF control of the head-neck. We present the mechatronic design, validation, and control implementations of this robot, as well as a human experiment to demonstrate a potential use case of this versatile robot for rehabilitation. Participants were engaged in a target reaching task while the robot applied both assistive and resistive moments on the head during the task. Our results show that neck muscle activation increased by 19% when moving the head against resistance and decreased by 28-43% when assisted by the robot. Overall, these results provide a scientific justification for further research in enabling movement and identifying personalized rehabilitation for motor training. Beyond rehabilitation, other applications such as applying force perturbations on the head to study sensory integration and applying traction to achieve pain relief may benefit from the innovation of this robotic platform which is capable of applying controlled 6-DoF forces/moments on the head.

Evaluation of physiological response and synchronisation errors during synchronous and pseudosynchronous stimulation trials

Rhythm perception and synchronisation is musical ability with neural basis defined as the ability to perceive rhythm in music and synchronise body movements with it. The study aimed to check the errors of synchronisation and physiological response as a reaction of the subjects to metrorhythmic stimuli of synchronous and pseudosynchronous stimulation (synchronisation with an externally controlled rhythm, but in reality controlled or produced tone by tapping) Nineteen subjects without diagnosed motor disorders participated in the study. Two tests were performed, where the electromyography signal and reaction time were recorded using the NORAXON system. In addition, physiological signals such as electrodermal activity and blood volume pulse were measured using the Empatica E4. Study 1 consisted of adapting the finger tapping test in pseudosynchrony with a given metrorhythmic stimulus with a selection of preferred, choices of decreasing and increasing tempo. Study 2 consisted of metrorhythmic synchronisation during the heel stomping test. Numerous correlations and statistically significant parameters were found between the response of the subjects with respect to their musical education, musical and sports activities. Most of the differentiating characteristics shown evidence of some group division in the undertaking of musical activities. The use of detailed analyses of synchronisation errors can contribute to the development of methods to improve the rehabilitation process of subjects with motor dysfunction, and this will contribute to the development of an expert system that considers personalised musical preferences.

Use of functional magnetic resonance imaging to identify cortical loci for lower limb movements and their efficacy for individuals after stroke

BACKGROUND

Identification of cortical loci for lower limb movements for stroke rehabilitation is crucial for better rehabilitation outcomes via noninvasive brain stimulation by targeting the fine-grained cortical loci of the movements. However, identification of the cortical loci for lower limb movements using functional MRI (fMRI) is challenging due to head motion and difficulty in isolating different types of movement. Therefore, we developed a custom-made MR-compatible footplate and leg cushion to identify the cortical loci for lower limb movements and conducted multivariate analysis on the fMRI data. We evaluated the validity of the identified loci using both fMRI and behavioral data, obtained from healthy participants as well as individuals after stroke.

METHODS

We recruited 33 healthy participants who performed four different lower limb movements (ankle dorsiflexion, ankle rotation, knee extension, and toe flexion) using our custom-built equipment while fMRI data were acquired. A subgroup of these participants (Dataset 1; n = 21) was used to identify the cortical loci associated with each lower limb movement in the paracentral lobule (PCL) using multivoxel pattern analysis and representational similarity analysis. The identified cortical loci were then evaluated using the remaining healthy participants (Dataset 2; n = 11), for whom the laterality index (LI) was calculated for each lower limb movement using the cortical loci identified for the left and right lower limbs. In addition, we acquired a dataset from 15 individuals with chronic stroke for regression analysis using the LI and the Fugl-Meyer Assessment (FMA) scale.

RESULTS

The cortical loci associated with the lower limb movements were hierarchically organized in the medial wall of the PCL following the cortical homunculus. The LI was clearer using the identified cortical loci than using the PCL. The healthy participants (mean ± standard deviation: 0.12 ± 0.30; range: - 0.63 to 0.91) exhibited a higher contralateral LI than the individuals after stroke (0.07 ± 0.47; - 0.83 to 0.97). The corresponding LI scores for individuals after stroke showed a significant positive correlation with the FMA scale for paretic side movement in ankle dorsiflexion (R2 = 0.33, p = 0.025) and toe flexion (R2 = 0.37, p = 0.016).

CONCLUSIONS

The cortical loci associated with lower limb movements in the PCL identified in healthy participants were validated using independent groups of healthy participants and individuals after stroke. Our findings suggest that these cortical loci may be beneficial for the neurorehabilitation of lower limb movement in individuals after stroke, such as in developing effective rehabilitation interventions guided by the LI scores obtained for neuronal activations calculated from the identified cortical loci across the paretic and non-paretic sides of the brain.

Tactile shape discrimination for moving stimuli

In this study, we explored spatial-temporal dependencies and their impact on the tactile perception of moving objects. Building on previous research linking visual perception and human movement, we examined if an imputed motion mechanism operates within the tactile modality. We focused on how biological coherence between space and time, characteristic of human movement, influences tactile perception. An experiment was designed wherein participants were stimulated on their right palm with tactile patterns, either ambiguous (incongruent conditions) or non-ambiguous (congruent conditions) relative to a biological motion law (two-thirds power law) and asked to report perceived shape and associated confidence. Our findings reveal that introducing ambiguous tactile patterns (1) significantly diminishes tactile discrimination performance, implying motor features of shape recognition in vision are also observed in the tactile modality, and (2) undermines participants' response confidence, uncovering the accessibility degree of information determining the tactile percept's conscious representation. Analysis based on the Hierarchical Drift Diffusion Model unveiled the sensitivity of the evidence accumulation process to the stimulus's informational ambiguity and provides insight into tactile perception as predictive dynamics for reducing uncertainty. These discoveries deepen our understanding of tactile perception mechanisms and underscore the criticality of predictions in sensory information processing.

Subthalamic stimulation modulates context-dependent effects of beta bursts during fine motor control

Increasing evidence suggests a considerable role of pre-movement beta bursts for motor control and its impairment in Parkinson's disease. However, whether beta bursts occur during precise and prolonged movements and if they affect fine motor control remains unclear. To investigate the role of within-movement beta bursts for fine motor control, we here combine invasive electrophysiological recordings and clinical deep brain stimulation in the subthalamic nucleus in 19 patients with Parkinson's disease performing a context-varying task that comprised template-guided and free spiral drawing. We determined beta bursts in narrow frequency bands around patient-specific peaks and assessed burst amplitude, duration, and their immediate impact on drawing speed. We reveal that beta bursts occur during the execution of drawing movements with reduced duration and amplitude in comparison to rest. Exclusively when drawing freely, they parallel reductions in acceleration. Deep brain stimulation increases the acceleration around beta bursts in addition to a general increase in drawing velocity and improvements of clinical function. These results provide evidence for a diverse and task-specific role of subthalamic beta bursts for fine motor control in Parkinson's disease; suggesting that pathological beta bursts act in a context dependent manner, which can be targeted by clinical deep brain stimulation.

Multiplicative joint coding in preparatory activity for reaching sequence in macaque motor cortex

Although the motor cortex has been found to be modulated by sensory or cognitive sequences, the linkage between multiple movement elements and sequence-related responses is not yet understood. Here, we recorded neuronal activity from the motor cortex with implanted micro-electrode arrays and single electrodes while monkeys performed a double-reach task that was instructed by simultaneously presented memorized cues. We found that there existed a substantial multiplicative component jointly tuned to impending and subsequent reaches during preparation, then the coding mechanism transferred to an additive manner during execution. This multiplicative joint coding, which also spontaneously emerged in recurrent neural networks trained for double reach, enriches neural patterns for sequential movement, and might explain the linear readout of elemental movements.

Slowing of Movements in Healthy Aging as a Rational Economic Response to an Elevated Effort Landscape

Why do we move slower as we grow older? The reward circuits of the brain, which tend to invigorate movements, decline with aging, raising the possibility that reduced vigor is due to the diminishing value that our brain assigns to movements. However, as we grow older, it also becomes more effortful to make movements. Is age-related slowing principally a consequence of increased effort costs from the muscles, or reduced valuation of reward by the brain? Here, we first quantified the cost of reaching via metabolic energy expenditure in human participants (male and female), and found that older adults consumed more energy than the young at a given speed. Thus, movements are objectively more costly for older adults. Next, we observed that when reward increased, older adults, like the young, responded by initiating their movements earlier. Yet, unlike the young, they were unwilling to increase their movement speed. Was their reluctance to reach quicker for rewards due to the increased effort costs, or because they ascribed less value to the movement? Motivated by a mathematical model, we next made the young experience a component of aging by making their movements more effortful. Now the young responded to reward by reacting faster but chose not to increase their movement speed. This suggests that slower movements in older adults are partly driven by an adaptive response to an elevated effort landscape. Moving slower may be a rational economic response the brain is making to mitigate the elevated effort costs that accompany aging.

Impaired proprioception and magnified scaling of proprioceptive error responses in chronic stroke

BACKGROUND

Previous work has shown that ~ 50-60% of individuals have impaired proprioception after stroke. Typically, these studies have identified proprioceptive impairments using a narrow range of reference movements. While this has been important for identifying the prevalence of proprioceptive impairments, it is unknown whether these error responses are consistent for a broad range of reference movements. The objective of this study was to characterize proprioceptive accuracy as function of movement speed and distance in stroke.

METHODS

Stroke (N = 25) and controls (N = 21) completed a robotic proprioception test that varied movement speed and distance. Participants mirror-matched various reference movement speeds (0.1-0.4 m/s) and distances (7.5-17.5 cm). Spatial and temporal parameters known to quantify proprioception were used to determine group differences in proprioceptive accuracy, and whether patterns of proprioceptive error were consistent across testing conditions within and across groups.

RESULTS

Overall, we found that stroke participants had impaired proprioception compared to controls. Proprioceptive errors related to tested reference movement scaled similarly to controls, but some errors showed amplified scaling (e.g., significantly overshooting or undershooting reference speed). Further, interaction effects were present for speed and distance reference combinations at the extremes of the testing distribution.

CONCLUSIONS

We found that stroke participants have impaired proprioception and that some proprioceptive errors were dependent on characteristics of the movement (e.g., speed) and that reference movements at the extremes of the testing distribution resulted in significantly larger proprioceptive errors for the stroke group. Understanding how sensory information is utilized across a broad spectrum of movements after stroke may aid design of rehabilitation programs.

Continuous Motion Intention Prediction Using sEMG for Upper-Limb Rehabilitation: A Systematic Review of Model-Based and Model-Free Approaches

Upper limb functional impairments persisting after stroke significantly affect patients' quality of life. Precise adjustment of robotic assistance levels based on patients' motion intentions using sEMG signals is crucial for active rehabilitation. This paper systematically reviews studies on continuous prediction of upper limb single joints and multi-joint combinations motion intention using Model-Based (MB) and Model-Free (MF) approaches over the past decade, based on 186 relevant studies screened from six major electronic databases. The findings indicate ongoing challenges in terms of subject composition, algorithm robustness and generalization, and algorithm feasibility for practical applications. Moreover, it suggests integrating the strengths of both MB and MF approaches to improve existing algorithms. Therefore, future research should further explore personalized MB-MF combination methods incorporating deep learning, attention mechanisms, muscle synergy features, motor unit features, and closed-loop feedback to achieve precise, real-time, and long-duration prediction of multi-joint complex movements, while further refining the transfer learning strategy for rapid algorithm deployment across days and subjects. Overall, this review summarizes the current research status, significant findings, and challenges, aiming to inspire future research on predicting upper limb motion intentions based on sEMG.

Selective Action Prediction in Infancy Depending on Linguistic Cues: An EEG and Eyetracker Study

Humans' capacity to predict actions and to socially categorize individuals is at the basis of social cognition. Such capacities emerge in early infancy. By 6 months of age, infants predict others' reaching actions considering others' epistemic state. At a similar age, infants are biased to attend to and interact with more familiar individuals, considering adult-like social categories such as the language people speak. We report that these two core processes are interrelated early on in infancy. In a belief-based action prediction task, 6-month-old infants (males and females) presented with a native speaker generated online predictions about the agent's actions, as revealed by the activation of participants' sensorimotor areas before the agent's movement. However, infants who were presented with a foreign speaker did not recruit their motor system before the agent's action. The eyetracker analysis provided further evidence that linguistic group familiarity influences how infants predict others' actions, as only infants presented with a native speaker modified their attention to the stimuli as a function of the agent's forthcoming behavior. The current findings suggest that infants' emerging capacity to predict others' actions is modulated by social cues, such as others' linguistic group. A facilitation to predict and encode the actions of native speakers relative to foreign speakers may explain, in part, why infants preferentially attend to, imitate, and learn from the actions of native speakers.

Unraveling motor imagery brain patterns using explainable artificial intelligence based on Shapley values

BACKGROUND AND OBJECTIVE

Motor imagery (MI) based brain-computer interfaces (BCIs) are widely used in rehabilitation due to the close relationship that exists between MI and motor execution (ME). However, the underlying brain mechanisms of MI remain not well understood. Most MI-BCIs use the sensorimotor rhythms elicited in the primary motor cortex (M1) and somatosensory cortex (S1), which consist of an event-related desynchronization followed by an event-related synchronization. Consequently, this has resulted in systems that only record signals around M1 and S1. However, MI could involve a more complex network including sensory, association, and motor areas. In this study, we hypothesize that the superior accuracies achieved by new deep learning (DL) models applied to MI decoding rely on focusing on a broader MI activation of the brain. Parallel to the success of DL, the field of explainable artificial intelligence (XAI) has seen continuous development to provide explanations for DL networks success. The goal of this study is to use XAI in combination with DL to extract information about MI brain activation patterns from non-invasive electroencephalography (EEG) signals.

METHODS

We applied an adaptation of Shapley additive explanations (SHAP) to EEGSym, a state-of-the-art DL network with exceptional transfer learning capabilities for inter-subject MI classification. We obtained the SHAP values from two public databases comprising 171 users generating left and right hand MI instances with and without real-time feedback.

RESULTS

We found that EEGSym based most of its prediction on the signal of the frontal electrodes, i.e. F7 and F8, and on the first 1500 ms of the analyzed imagination period. We also found that MI involves a broad network not only based on M1 and S1, but also on the prefrontal cortex (PFC) and the posterior parietal cortex (PPC). We further applied this knowledge to select a 8-electrode configuration that reached inter-subject accuracies of 86.5% ± 10.6% on the Physionet dataset and 88.7% ± 7.0% on the Carnegie Mellon University's dataset.

CONCLUSION

Our results demonstrate the potential of combining DL and SHAP-based XAI to unravel the brain network involved in producing MI. Furthermore, SHAP values can optimize the requirements for out-of-laboratory BCI applications involving real users.

Across-task binding: The development of a representation in learning a continuous movement sequence

Across-task binding is defined as the stimulus/response of one task being linked to the response of another task. The purpose of the present experiment was to determine across-task binding in a continuous movement sequence task with an auditory task of high and low pitch tones and the development of a movement sequence representation. According to the two systems theory of sequence learning, we expected that the developed representation in the across-task binding context relies on the multi-dimensional system rather than on the unidimensional system which is restricted to a set of modules where each module processed information along one task/dimension. An inter-manual transfer design was used to disentangle the sequence representations. The mirror transfer test required the same pattern of muscle activation and joint angles (motor coordinates) in the contralateral limb as experienced during the acquisition phase, while in the non-mirror transfer test, the visual-spatial locations (spatial coordinates) of the target waveform were reinstated. The main finding was that consistently combining visual-spatial positions in a sequence and auditory dimensions such as the tone pitch does not rely on a multidimensional system as predicted by the two-systems theory.

Convolutional neural networks reveal properties of reach-to-grasp encoding in posterior parietal cortex

Deep neural networks (DNNs) are widely adopted to decode motor states from both non-invasively and invasively recorded neural signals, e.g., for realizing brain-computer interfaces. However, the neurophysiological interpretation of how DNNs make the decision based on the input neural activity is limitedly addressed, especially when applied to invasively recorded data. This reduces decoder reliability and transparency, and prevents the exploitation of decoders to better comprehend motor neural encoding. Here, we adopted an explainable artificial intelligence approach - based on a convolutional neural network and an explanation technique - to reveal spatial and temporal neural properties of reach-to-grasping from single-neuron recordings of the posterior parietal area V6A. The network was able to accurately decode 5 different grip types, and the explanation technique automatically identified the cells and temporal samples that most influenced the network prediction. Grip encoding in V6A neurons already started at movement preparation, peaking during movement execution. A difference was found within V6A: dorsal V6A neurons progressively encoded more for increasingly advanced grips, while ventral V6A neurons for increasingly rudimentary grips, with both subareas following a linear trend between the amount of grip encoding and the level of grip skills. By revealing the elements of the neural activity most relevant for each grip with no a priori assumptions, our approach supports and advances current knowledge about reach-to-grasp encoding in V6A, and it may represent a general tool able to investigate neural correlates of motor or cognitive tasks (e.g., attention and memory tasks) from single-neuron recordings.

Moving stimuli enhance beat timing and sensorimotor coupling in vision

Vision has long been known for its inefficiency in beat perception and synchronization. However, this has been challenged by the finding that moving stimuli (bouncing ball or moving bar) can significantly improve visual beat synchronization. The present study examined two possible mechanisms for this phenomenon: visual motion facilitates temporal processing or promotes sensorimotor coupling. Instead of a single visual object (such as a ball or bar), random-dot kinematograms (RDKs) were used to construct visual motion sequences to avoid confounding factors, such as changes in trajectory and velocity. Experiment 1 showed that RDKs improved beat-timing discrimination compared with visual flashes, but auditory tones were still superior to RDKs. In Experiment 2, synchronized movements improved auditory-tone beat timing but impaired visual-flash beat timing, with no effect on RDK beat timing. Experiment 3 indicated that the regression slope of the phase correction response in RDKs was higher than that in visual flashes but still lower than that in auditory tones. The results showed that moving stimuli enhances both temporal processing (Experiment 1) and sensorimotor coupling (Experiments 2 and 3) in vision, but to a lesser degree, with audition retaining an advantage. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

How Does Postural Control in Patients with Functional Motor Disorders Adapt to Multitasking-Based Immersive Virtual Reality?

BACKGROUND

Motor symptoms in functional motor disorders (FMDs) refer to involuntary, but learned, altered movement patterns associated with aberrant self-focus, sense of agency, and belief/expectations. These conditions commonly lead to impaired posture control, raising the likelihood of falls and disability. Utilizing visual and cognitive tasks to manipulate attentional focus, virtual reality (VR) integrated with posturography is a promising tool for exploring postural control disorders.

OBJECTIVES

To investigate whether postural control can be adapted by manipulating attentional focus in a 3D immersive VR environment.

METHODS

We compared postural parameters in 17 FMDs patients and 19 age-matched healthy controls over a single session under four increasingly more complex and attention-demanding conditions: simple fixation task (1) in the real room and (2) in 3D VR room-like condition; complex fixation task in a 3D VR city-like condition (3) avoiding distractors and (4) counting them. Dual-task effect (DTE) measured the relative change in performance induced by the different attention-demanding conditions on postural parameters.

RESULTS

Patients reduced sway area and mediolateral center of pressure displacement velocity DTE compared to controls (all, P < 0.049), but only under condition 4. They also showed a significant reduction in the sway area DTE under condition 4 compared to condition 3 (P = 0.025).

CONCLUSIONS

This study provides novel preliminary evidence for the value of a 3D immersive VR environment combined with different attention-demanding conditions in adapting postural control in patients with FMDs. As supported by quantitative and objective posturographic measures, our findings may inform interventions to explore FMDs pathophysiology.

The control of the arm's equilibrium position

To generate a force, the brain activates muscles that act like springs to pull the arm toward a new equilibrium position. The equilibrium position (EP) is central to our understanding of the biological control of viscoelastic muscles. Although there is evidence of the EP during the control of limb posture, EPs have not been directly identified when the limb exerts a force against the environment. Here, we asked participants to apply a constant force in one of eight directions against a point-like constraint. This constraint was released abruptly to observe the final position to which the arm converged. Importantly, the same force magnitude was maintained while changing the arm's stiffness by modulating the strength of the hand's power grasp. The final position moved further away from the constraint as the arm became less stiff and was inversely proportional to the arm's stiffness, thereby confirming that the final position was the arm's EP. These results demonstrate how the EP changes with the arm's stiffness to produce a desired force in different directions.NEW & NOTEWORTHY According to numerous theories, the brain controls posture and movement by activating muscles that attract the limb toward a so-called equilibrium position, but the universality of this mechanism has not been shown for different motor behaviors. Here, we show that even when pushing or pulling against the environment, the brain achieves the desired force through an equilibrium position that lies beyond the physical constraint.

Multisensory perception depends on the reliability of the type of judgment

The brain engages the processes of multisensory integration and recalibration to deal with discrepant multisensory signals. These processes consider the reliability of each sensory input, with the more reliable modality receiving the stronger weight. Sensory reliability is typically assessed via the variability of participants' judgments, yet these can be shaped by factors both external and internal to the nervous system. For example, motor noise and participant's dexterity with the specific response method contribute to judgment variability, and different response methods applied to the same stimuli can result in different estimates of sensory reliabilities. Here we ask how such variations in reliability induced by variations in the response method affect multisensory integration and sensory recalibration, as well as motor adaptation, in a visuomotor paradigm. Participants performed center-out hand movements and were asked to judge the position of the hand or rotated visual feedback at the movement end points. We manipulated the variability, and thus the reliability, of repeated judgments by asking participants to respond using either a visual or a proprioceptive matching procedure. We find that the relative weights of visual and proprioceptive signals, and thus the asymmetry of multisensory integration and recalibration, depend on the reliability modulated by the judgment method. Motor adaptation, in contrast, was insensitive to this manipulation. Hence, the outcome of multisensory binding is shaped by the noise introduced by sensorimotor processing, in line with perception and action being intertwined.NEW & NOTEWORTHY Our brain tends to combine multisensory signals based on their respective reliability. This reliability depends on sensory noise in the environment, noise in the nervous system, and, as we show here, variability induced by the specific judgment procedure.

Motor neurons generate pose-targeted movements via proprioceptive sculpting

Motor neurons are the final common pathway1 through which the brain controls movement of the body, forming the basic elements from which all movement is composed. Yet how a single motor neuron contributes to control during natural movement remains unclear. Here we anatomically and functionally characterize the individual roles of the motor neurons that control head movement in the fly, Drosophila melanogaster. Counterintuitively, we find that activity in a single motor neuron rotates the head in different directions, depending on the starting posture of the head, such that the head converges towards a pose determined by the identity of the stimulated motor neuron. A feedback model predicts that this convergent behaviour results from motor neuron drive interacting with proprioceptive feedback. We identify and genetically2 suppress a single class of proprioceptive neuron3 that changes the motor neuron-induced convergence as predicted by the feedback model. These data suggest a framework for how the brain controls movements: instead of directly generating movement in a given direction by activating a fixed set of motor neurons, the brain controls movements by adding bias to a continuing proprioceptive-motor loop.

Integrating across behaviors and timescales to understand the neural control of movement

The nervous system evolved to enable navigation throughout the environment in the pursuit of resources. Evolutionarily newer structures allowed increasingly complex adaptations but necessarily added redundancy. A dominant view of movement neuroscientists is that there is a one-to-one mapping between brain region and function. However, recent experimental data is hard to reconcile with the most conservative interpretation of this framework, suggesting a degree of functional redundancy during the performance of well-learned, constrained behaviors. This apparent redundancy likely stems from the bidirectional interactions between the various cortical and subcortical structures involved in motor control. We posit that these bidirectional connections enable flexible interactions across structures that change depending upon behavioral demands, such as during acquisition, execution or adaptation of a skill. Observing the system across both multiple actions and behavioral timescales can help isolate the functional contributions of individual structures, leading to an integrated understanding of the neural control of movement.

Perturbation Variability Does Not Influence Implicit Sensorimotor Adaptation

Implicit adaptation has been regarded as a rigid process that automatically operates in response to movement errors to keep the sensorimotor system precisely calibrated. This hypothesis has been challenged by recent evidence suggesting flexibility in this learning process. One compelling line of evidence comes from work suggesting that this form of learning is context-dependent, with the rate of learning modulated by error history. Specifically, learning was attenuated in the presence of perturbations exhibiting high variance compared to when the perturbation is fixed. However, these findings are confounded by the fact that the adaptation system corrects for errors of different magnitudes in a non-linear manner, with the adaptive response increasing in a proportional manner to small errors and saturating to large errors. Through simulations, we show that this non-linear motor correction function is sufficient to explain the effect of perturbation variance without referring to an experience-dependent change in error sensitivity. Moreover, by controlling the distribution of errors experienced during training, we provide empirical evidence showing that there is no measurable effect of perturbation variance on implicit adaptation. As such, we argue that the evidence to date remains consistent with the rigidity assumption.

Cerebellar Transcranial Direct Current Stimulation Modulates Anticipatory Postural Adjustments in Healthy Adults

During forward swinging of the arm, the central nervous system must anticipate the effect of upraising upon the body. Little is known about the cerebellar network that coordinates these anticipatory postural adjustments (APAs). Stimulating different cerebellar regions with transcranial direct current stimulation (tDCS) and with different polarities modulated the APAs. We used surface electromyography (sEMG) to measure muscle activities in a bilateral rapid shoulder flexion task. The onset of APAs was altered after tDCS over the vermis, while the postural stability and the kinematics of arm raising were not affected. To our knowledge, this is the first human cerebellar-tDCS (c-tDCS) study to separate cerebellar involvement in core muscle APAs in bilateral rapid shoulder flexion. These data contribute to our understanding of the cerebellar network supporting APAs in healthy adults. Modulated APAs of the erector spinae by tDCS on the vermis may be related to altered cerebellar brain inhibition (CBI), suggesting the importance of the vermal-cerebral connections in APAs regulation.

Sleep bruxism and associated physiological events in children with obstructive sleep apnea: a polysomnographic study

STUDY OBJECTIVES

The aim of this study was to evaluate the physiological events associated with sleep bruxism (Sleep Bruxism [SB]; presence of mandibular movement activity) and the control window (4 minutes prior to SB event, where no mandibular movement activity was detected) in a polysomnography study in children with mild sleep apnea.

METHODS

Polysomnography data from children aged 4 to 9 years old diagnosed with mild sleep apnea were analyzed by 2 trained examiners. The mandibular movement activity (bruxism event; SB) was classified into phasic and tonic. The control window was selected 4 minutes prior to the SB event. All physiological events were recorded in both bruxism and control windows, including sleep phase (N1, N2, N3, and rapid eye movement), arousal, leg movements, tachycardia, bradycardia, oxygen desaturation, and number of obstructive and central sleep apnea events. The moment in which those phenomena occurred when associated with SB was also analyzed (before/after). Data were analyzed using 95% confidence intervals (α = 5%).

RESULTS

A total of 661 mandibular movements were analyzed and classified as tonic (n = 372) or phasic (n = 289). The mean apnea-hypopnea index was 1.99 (SD = 1.27) events/h. The frequency of leg movements, microarousal, and tachycardia was increased in SB events when compared with the control window (P < .05). There was an increase in bradycardia frequency in the control window when compared with SB (in both tonic and phasic events). The frequency of obstructive and central apnea during SB was lower when compared with the other physiological phenomena.

CONCLUSIONS

There is a difference in the physiological parameters evaluated in children with mild sleep apnea when comparing the 2 windows (SB and control). Sleep bruxism is associated with other physiological phenomena, such as leg movements, tachycardia, and microarousal. The use of a control window (where no mandibular activity was detected) was representative since it did not show activation of the sympathetic nervous system.

CITATION

Bonacina CF, Soster LMSFA, Bueno C, et al. Sleep bruxism and associated physiological events in children with obstructive sleep apnea: a polysomnographic study. J Clin Sleep Med. 2024;20(4):565-573.

Determining the effects of AR/VR HMD design parameters (mass and inertia) on cervical spine joint torques

This study aimed to determine gravitational and dynamic torques and muscle activity of the neck across a series of design parameters of head mounted displays (mass, center of mass, and counterweights) associated with virtual and augmented reality (VR/AR). Twenty young adult participants completed five movement types (Slow and Fast Flexion/Extension and Rotation, and Search) while wearing a custom-designed prototype headset that varied the three design parameters: display mass (0, 200, 500, and 750 g), distance of the display's center of mass in front of the eyes (approximately 1, 3, and 5 cm anteriorly), and counterweights of 0, 166, 332, and 500 g to balance the display mass of 500 g at 7 cm. Inverse dynamics of a link segment model of the head and headset provided estimates of the torques about the joint between the skull and the occiput-first cervical vertebrae (OC1) and joint between the C7 and T1 vertebrae (C7). Surface electromyography (EMG) measured bilateral muscle activity of the splenius and upper trapezius muscles. Adding 750 g of display mass nearly doubled root mean square joint torques across all movement types. Increasing the distance of the display mass in front of the eyes by 4 cm increased torques about OC1 for the Slow and Fast Rotation and Search movements by approximately 20%. Adding a counterweight decreased torques about OC1 during the rotation and search tasks but did not decrease the torques experienced in the lower cervical spine (C7). For the flexion/extension axis, the magnitude of the dynamic torque component was 20% or less of the total torque experienced whereas for the rotation axis the magnitude of the dynamic torque component was greater than 50% of the total torque. Surface EMG root mean square values significantly varied across movement types with the fast rotation having the largest values; however, they did not vary significantly across the headset configurations.

Preparatory activity and the expansive null-space

The study of the cortical control of movement experienced a conceptual shift over recent decades, as the basic currency of understanding shifted from single-neuron tuning towards population-level factors and their dynamics. This transition was informed by a maturing understanding of recurrent networks, where mechanism is often characterized in terms of population-level factors. By estimating factors from data, experimenters could test network-inspired hypotheses. Central to such hypotheses are 'output-null' factors that do not directly drive motor outputs yet are essential to the overall computation. In this Review, we highlight how the hypothesis of output-null factors was motivated by the venerable observation that motor-cortex neurons are active during movement preparation, well before movement begins. We discuss how output-null factors then became similarly central to understanding neural activity during movement. We discuss how this conceptual framework provided key analysis tools, making it possible for experimenters to address long-standing questions regarding motor control. We highlight an intriguing trend: as experimental and theoretical discoveries accumulate, the range of computational roles hypothesized to be subserved by output-null factors continues to expand.

Movement-goal relevant object shape properties act as poor but viable cues for the attribution of motor errors to external objects

When a context change is detected during motor learning, motor memories-internal models for executing movements within some context-may be created or existing motor memories may be activated and modified. Assigning credit to plausible causes of errors can allow for fast retrieval and activation of a motor memory, or a combination of motor memories, when the presence of such causes is detected. Features of the movement-context intrinsic to the movement dynamics, such as posture of the end effector, are often effective cues for detecting context change whereas features extrinsic to the movement dynamics, such as the colour of an object being moved, are often not. These extrinsic cues are typically not relevant to the motor task at hand and can be safely ignored by the motor system. We conducted two experiments testing if extrinsic but movement-goal relevant object-shape cues during an object-transport task can act as viable contextual cues for error assignment to the object, and the creation of new, object-shape-associated motor memories. In the first experiment we find that despite the object-shape cues, errors are primarily attributed to the hand transporting the object. In a second experiment, we find participants can execute differing movements cued by the object shape in a dual adaptation task, but the extent of adaptation is small, suggesting that movement-goal relevant object-shape properties are poor but viable cues for creating context specific motor memories.

Task-driven neural network models predict neural dynamics of proprioception

Proprioception tells the brain the state of the body based on distributed sensory neurons. Yet, the principles that govern proprioceptive processing are poorly understood. Here, we employ a task-driven modeling approach to investigate the neural code of proprioceptive neurons in cuneate nucleus (CN) and somatosensory cortex area 2 (S1). We simulated muscle spindle signals through musculoskeletal modeling and generated a large-scale movement repertoire to train neural networks based on 16 hypotheses, each representing different computational goals. We found that the emerging, task-optimized internal representations generalize from synthetic data to predict neural dynamics in CN and S1 of primates. Computational tasks that aim to predict the limb position and velocity were the best at predicting the neural activity in both areas. Since task optimization develops representations that better predict neural activity during active than passive movements, we postulate that neural activity in the CN and S1 is top-down modulated during goal-directed movements.

Modulation of somatosensory signal transmission in the primate cuneate nucleus during voluntary hand movement

Primate hands house an array of mechanoreceptors and proprioceptors, which are essential for tactile and kinematic information crucial for daily motor action. While the regulation of these somatosensory signals is essential for hand movements, the specific central nervous system (CNS) location and mechanism remain unclear. Our study demonstrates the attenuation of somatosensory signals in the cuneate nucleus during voluntary movement, suggesting significant modulation at this initial relay station in the CNS. The attenuation is comparable to the cerebral cortex but more pronounced than in the spinal cord, indicating the cuneate nuclei's role in somatosensory perception modulation during movement. Moreover, our findings suggest that the descending motor tract may regulate somatosensory transmission in the cuneate nucleus, enhancing relevant signals and suppressing unnecessary ones for the regulation of movement. This process of recurrent somatosensory modulation between cortical and subcortical areas could be a basic mechanism for modulating somatosensory signals to achieve active perception.

Physics-Informed Deep Learning for Muscle Force Prediction With Unlabeled sEMG Signals

Computational biomechanical analysis plays a pivotal role in understanding and improving human movements and physical functions. Although physics-based modeling methods can interpret the dynamic interaction between the neural drive to muscle dynamics and joint kinematics, they suffer from high computational latency. In recent years, data-driven methods have emerged as a promising alternative due to their fast execution speed, but label information is still required during training, which is not easy to acquire in practice. To tackle these issues, this paper presents a novel physics-informed deep learning method to predict muscle forces without any label information during model training. In addition, the proposed method could also identify personalized muscle-tendon parameters. To achieve this, the Hill muscle model-based forward dynamics is embedded into the deep neural network as the additional loss to further regulate the behavior of the deep neural network. Experimental validations on the wrist joint from six healthy subjects are performed, and a fully connected neural network (FNN) is selected to implement the proposed method. The predicted results of muscle forces show comparable or even lower root mean square error (RMSE) and higher coefficient of determination compared with baseline methods, which have to use the labeled surface electromyography (sEMG) signals, and it can also identify muscle-tendon parameters accurately, demonstrating the effectiveness of the proposed physics-informed deep learning method.

Irregularity of instantaneous gamma frequency in the motor control network characterize visuomotor and proprioceptive information processing

Objective.The study aims to characterize movements with different sensory goals, by contrasting the neural activity involved in processing proprioceptive and visuo-motor information. To accomplish this, we have developed a new methodology that utilizes the irregularity of the instantaneous gamma frequency parameter for characterization.Approach.In this study, eight essential tremor patients undergoing an awake deep brain stimulation implantation surgery repetitively touched the clinician's finger (forward visually-guided/FV movement) and then one's own chin (backward proprioceptively-guided/BP movement). Neural electrocorticographic recordings from the motor (M1), somatosensory (S1), and posterior parietal cortex (PPC) were obtained and band-pass filtered in the gamma range (30-80 Hz). The irregularity of the inter-event intervals (IEI; inverse of instantaneous gamma frequency) were examined as: (1) auto-information of the IEI time series and (2) correlation between the amplitude and its proceeding IEI. We further explored the network connectivity after segmenting the FV and BP movements by periods of accelerating and decelerating forces, and applying the IEI parameter to transfer entropy methods.Main results.Conceptualizing that the irregularity in IEI reflects active new information processing, we found the highest irregularity in M1 during BP movement, highest in PPC during FV movement, and the lowest during rest at all sites. Also, connectivity was the strongest from S1 to M1 and from S1 to PPC during FV movement with accelerating force and weakest during rest.Significance. We introduce a novel methodology that utilize the instantaneous gamma frequency (i.e. IEI) parameter in characterizing goal-oriented movements with different sensory goals, and demonstrate its use to inform the directional connectivity within the motor cortical network. This method successfully characterizes different movement types, while providing interpretations to the sensory-motor integration processes.

Dopamine neuron activity encodes the length of upcoming contralateral movement sequences

Dopaminergic neurons (DANs) in the substantia nigra pars compacta (SNc) have been related to movement speed, and loss of these neurons leads to bradykinesia in Parkinson's disease (PD). However, other aspects of movement vigor are also affected in PD; for example, movement sequences are typically shorter. However, the relationship between the activity of DANs and the length of movement sequences is unknown. We imaged activity of SNc DANs in mice trained in a freely moving operant task, which relies on individual forelimb sequences. We uncovered a similar proportion of SNc DANs increasing their activity before either ipsilateral or contralateral sequences. However, the magnitude of this activity was higher for contralateral actions and was related to contralateral but not ipsilateral sequence length. In contrast, the activity of reward-modulated DANs, largely distinct from those modulated by movement, was not lateralized. Finally, unilateral dopamine depletion impaired contralateral, but not ipsilateral, sequence length. These results indicate that movement-initiation DANs encode more than a general motivation signal and invigorate aspects of contralateral movements.

Online Monitoring for Human Sit-to-Stand Movement Based on Karush-Kuhn-Tucker Optimized Zonotope Set-Membership Filter

As the global aging population continues to grow, there has been a significant increase in the number of fall-related injuries among the elderly, primarily due to reduced muscle strength and balance control, especially during sit-to-stand (STS) movements. Intelligent wearable robots have the potential to provide fall prevention assistance to individuals at risk, but an accurate and timely assessment of human movement stability is essential. This article presents a fall prediction algorithm for STS movements based on the Karush-Kuhn-Tucker (KKT) optimized zonotope set-membership filter (KKT-ZSMF), enabling real-time assessment of human stability. To quantify the feasible stability region of human STS movement, a mathematical model is proposed based on dynamic stability theory. Additionally, an online fall-prediction approach is developed, utilizing the zonotope set-membership filter to iteratively update the set that represents the instantaneous stability region. The approach incorporates a KKT optimization algorithm to compute the optimal convex hull, thereby enhancing the accuracy and efficiency of the set-membership filter. Experimental validation is conducted with the participation of 13 subjects including 5 elderly subjects, comparing the performance of the proposed KKT-ZSMF algorithm with other relevant methods. The results confirm the accuracy and real-time performance of the KKT-ZSMF algorithm for predicting human STS movement stability, achieving an overall prediction accuracy of 93.49% and a runtime of no more than 7.91 ms. These findings demonstrate the suitability of the algorithm for fall prevention assistance in daily activities.

Musculoskeletal model degrees of Freedom: Frontal plane constraints are hindering our understanding of human movement

Induced acceleration analyses have expanded our understanding on the contributions of muscle forces to center of mass and segmental kinematics during a myriad of tasks. While these techniques have identified a subset of major muscle that contribute to locomotion, most analyses have included models with only one frontal plane degree of freedom (dof) actuated by the hip joint. The purpose of this study was to define the impact of including knee and subtalar joint frontal plane dof on model superposition accuracy and muscle specific contributions to mediolateral accelerations. Induced acceleration analyses were performed using OpenSim with the Lai model on a freely available dataset of one subject running at 4 m/s. Analyses were performed on four models (standard, with subtalar joint, with frontal plane knee, and combined frontal plane knee with subtalar) with the kinematic constraint and perturbation analyses. Root mean square error and correlations were computed against experimental kinematics. Adding frontal plane dofs improved mediolateral acceleration correlations on average by > 0.25 while only minimally impacting errors. The constraints method performed better than the perturbation method for mediolateral accelerations. Including frontal plane knee dof resulted in muscle and method specific responses. All muscles presented with a complete flip of polarity for constraint method, imparted by allowing the medial/lateral muscles to contribute according to their anatomical function. Only the gluteus medius flipped for the perturbation method. This study provides significant support for the inclusion of frontal plane knee and subtalar dof and the need for reevaluation of muscle contributions via induced acceleration.

The benefit of knowledge: postural response modulation by foreknowledge of equilibrium perturbation in an upper limb task

For whole-body sway patterns, a compound motor response following an external stimulus may comprise reflexes, postural adjustments (anticipatory or compensatory), and voluntary muscular activity. Responses to equilibrium destabilization may depend on both motor set and a subject`s expectation of the disturbing stimulus. To disentangle these influences on lower limb responses, we studied a model in which subjects (n = 14) were suspended in the air, without foot support, and performed a fast unilateral wrist extension (WE) in response to a passive knee flexion (KF) delivered by a robot. To characterize the responses, electromyographic activity of rectus femoris and reactive leg torque was obtained bilaterally in a series of trials, with or without the requirement of WE (motor set), and/or beforehand information about the upcoming velocity of KF (subject`s expectation). Some fast-velocity trials resulted in StartReact responses, which were used to subclassify leg responses. When subjects were uninformed about the upcoming KF, large rectus femoris responses concurred with a postural reaction in conditions without motor task, and with both postural reaction and postural adjustment when WE was required. WE in response to a low-volume acoustic signal elicited no postural adjustments. When subjects were informed about KF velocity and had to perform WE, large rectus femoris responses corresponded to anticipatory postural adjustment rather than postural reaction. In conclusion, when subjects are suspended in the air and have to respond with WE, the prepared motor set includes anticipatory postural adjustments if KF velocity is known, and additional postural reactions if KF velocity is unknown.

Inter-trial variability is higher in 3D markerless compared to marker-based motion capture: Implications for data post-processing and analysis

Markerless motion capture has recently attracted significant interest in clinical gait analysis and human movement science. Its ease of use and potential to streamline motion capture recordings bear great potential for out-of-the-laboratory measurements in large cohorts. While previous studies have shown that markerless systems can achieve acceptable accuracy and reliability for kinematic parameters of gait, they also noted higher inter-trial variability of markerless data. Since increased inter-trial variability can have important implications for data post-processing and analysis, this study compared the inter-trial variability of simultaneously recorded markerless and marker-based data. For this purpose, the data of 18 healthy volunteers were used who were instructed to simulate four different gait patterns: physiological, crouch, circumduction, and equinus gait. Gait analysis was performed using the smartphone-based markerless system OpenCap and a marker-based motion capture system. We compared the inter-trial variability of both systems and also evaluated if changes in inter-trial variability may depend on the analyzed gait pattern. Compared to the marker-based data, we observed an increase of inter-trial variability for the markerless system ranging from 6.6% to 22.0% for the different gait patterns. Our findings demonstrate that the markerless pose estimation pipelines can introduce additionally variability in the kinematic data across different gait patterns and levels of natural variability. We recommend using averaged waveforms rather than single ones to mitigate this problem. Further, caution is advised when using variability-based metrics in gait and human movement analysis based on markerless data as increased inter-trial variability can lead to misleading results.

Design and analysis of a compatible exoskeleton rehabilitation robot system based on upper limb movement mechanism

Rehabilitation robots are used to promote structural and functional recovery of the nervous system with repetitive, task-oriented training and have been gradually applied to clinical rehabilitation training. This paper proposes an upper limb exoskeleton rehabilitation robot system that could realize shoulder-elbow-wrist joint rehabilitation training. Firstly, a motion equivalent model was established based on the upper limb movement mechanism, the robot mechanism configuration was designed, and the optimization algorithm and spatial mechanism theory were used to optimize and analyze the structural parameters and human-machine compatibility of the robot, which will guide the design of the robot's model. Then, the robot kinematics were solved, and its maximum motion range, dexterity distribution, and daily motion trajectory were simulated. Finally, a system prototype was built to test the maximum range of robot-assisted human upper limb training by laser tracker, while the pressure of human-machine interaction during training was captured and analyzed by flexible sensors. The results show that the proposed rehabilitation robot could nearly completely cover the range of motion of upper limb joints and meet the needs of trajectory training, and the linear velocity dexterity and angular velocity dexterity in the motion space are maximum 0.55 and 0.89, and the human-machine interaction pressures during the training process are all less than 10 kPa. Besides, this paper also conducted a system evaluation based on the fuzzy comprehensive evaluation model, and the evaluation result was 0.39, with an excellent evaluation grade, it indirectly indicates that the robot's overall performance was good.

Modeling of human muscle and its deformation

There is a lack of volume preserving and reasonable deformation of human muscles during bones and joints movement in the field of digital orthopedics. A novel approach for modeling of human muscle and its deformation was put forward to effectively assist doctors in guiding patients to carry out rehabilitation exercises. Firstly, based on Magnetic Resonance Imaging (MRI) data, the generated slice images were used to extract the outer contour lines and then the corresponding contour lines and optimal matching points of the adjacent layer images were connected to construct the three-dimensional (3D) geometric models of the muscles; Secondly, the mapping relationship between parameters can be established through hierarchical definition of the muscle characteristics to realize the volume-preserving deformation of muscle; Finally, the movement of human joints can be realized based on the constraint range of joint movement, and the vector-valued dynamic fourth-order differential equation was proposed to make the characteristic curve dynamically simulate the process of muscle deformation, thereby forming the corresponding relationship between bone movement and muscle deformation. The effectiveness and feasibility of this method have been verified in our experiments with biceps brachii and triceps brachii as examples. The maximum volume errors of biceps brachii and triceps brachii during the deformation process were less than 0.6%, which can be ignored within a certain allowable error range, reflecting that the parametric method was used to realize the reasonable volume-preserving deformation of human muscle.

rTMS over the human medial parietal cortex impairs online reaching corrections

Indirect correlational evidence suggests that the posteromedial sector of the human parietal cortex (area hV6A) is involved in reaching corrections. We interfered with hV6A functions using repetitive transcranial magnetic stimulation (rTMS) while healthy participants performed reaching movements and in-flight adjustments of the hand trajectory in presence of unexpected target shifts. rTMS over hV6A specifically altered action reprogramming, causing deviations of the shifted trajectories, particularly along the vertical dimension (i.e., distance). This study provides evidence of the functional relevance of hV6A in action reprogramming while a sudden event requires a change in performance and shows that hV6A also plays a role in state estimation during reaching. These findings are in line with neurological data showing impairments in actions performed along the distance dimension when lesions occur in the dorsal posterior parietal cortex.

Scalable musculoskeletal model for dynamic simulations of upper body movement

A musculoskeletal (MSK) model is a valuable tool for assessing complex biomechanical problems, estimating joint torques during motion, optimizing motion in sports, and designing exoskeletons and prostheses. This study proposes an open-source upper body MSK model that supports biomechanical analysis of human motion. The MSK model of the upper body consists of 8 body segments (torso, head, left/right upper arm, left/right forearm, and left/right hand). The model has 20 degrees of freedom (DoFs) and 40 muscle torque generators (MTGs), which are constructed using experimental data. The model is adjustable for different anthropometric measurements and subject body characteristics: sex, age, body mass, height, dominant side, and physical activity. Joint limits are modeled using experimental dynamometer data within the proposed multi-DoF MTG model. The model equations are verified by simulating the joint range of motion (ROM) and torque; all simulation results have a good agreement with previously published research.