Neuromechanics of muscle synergies for posture and movement

Ethnokinesiology: towards a neuromechanical understanding of cultural differences in movement

Each individual's movements are sculpted by constant interactions between sensorimotor and sociocultural factors. A theoretical framework grounded in motor control mechanisms articulating how sociocultural and biological signals converge to shape movement is currently missing. Here, we propose a framework for the emerging field of ethnokinesiology aiming to provide a conceptual space and vocabulary to help bring together researchers at this intersection. We offer a first-level schema for generating and testing hypotheses about cultural differences in movement to bridge gaps between the rich observations of cross-cultural movement variations and neurophysiological and biomechanical accounts of movement. We explicitly dissociate two interacting feedback loops that determine culturally relevant movement: one governing sensorimotor tasks regulated by neural signals internal to the body, the other governing ecological tasks generated through actions in the environment producing ecological consequences. A key idea is the emergence of individual-specific and culturally influenced motor concepts in the nervous system, low-dimensional functional mappings between sensorimotor and ecological task spaces. Motor accents arise from perceived differences in motor concept topologies across cultural contexts. We apply the framework to three examples: speech, gait and grasp. Finally, we discuss how ethnokinesiological studies may inform personalized motor skill training and rehabilitation, and challenges moving forward.This article is part of the theme issue 'Minds in movement: embodied cognition in the age of artificial intelligence'.

Adaptive Adjustments in Lower Limb Muscle Coordination during Single-Leg Landing Tasks in Latin Dancers

Previous research has primarily focused on evaluating the activity of individual muscles in dancers, often neglecting their synergistic interactions. Investigating the differences in lower limb muscle synergy during landing between dancers and healthy controls will contribute to a comprehensive understanding of their neuromuscular control patterns. This study enrolled 22 Latin dancers and 22 healthy participants, who performed a task involving landing from a 30 cm high platform. The data were collected using Vicon systems, force plates, and electromyography (EMG). The processed EMG data were subjected to non-negative matrix factorization (NNMF) for decomposition, followed by classification using K-means clustering algorithm and Pearson correlation coefficients. Three synergies were extracted for both Latin dancers and healthy participants. Synergy 1 showed increased contributions from the tibialis anterior (p < 0.001) and medial gastrocnemius (p = 0.024) in Latin dancers compared to healthy participants. Synergy 3 highlighted significantly greater contributions from the vastus lateralis in healthy participants compared to Latin dancers (p = 0.039). This study demonstrates that Latin dancers exhibit muscle synergies similar to those observed in healthy controls, revealing specific adjustments in the tibialis anterior and medial gastrocnemius muscles among dancers. This research illustrates how dancers optimize control strategies during landing tasks, offering a novel perspective for comprehensively understanding dancers' neuromuscular control patterns.

Muscle synergies for multidirectional isometric force generation during maintenance of upright standing posture

Muscle synergies are defined as coordinated recruitment of groups of muscles with specific activation balances and time profiles aimed at generating task-specific motor commands. While muscle synergies in postural control have been investigated primarily in reactive balance conditions, the neuromechanical contribution of muscle synergies during voluntary control of upright standing is still unclear. In this study, muscle synergies were investigated during the generation of isometric force at the trunk during the maintenance of standing posture. Participants were asked to maintain the steady-state upright standing posture while pulling forces of different magnitudes were applied at the level at the waist in eight horizontal directions. Muscle synergies were extracted by nonnegative matrix factorization from sixteen lower limb and trunk muscles. An average of 5-6 muscle synergies were sufficient to account for a wide variety of EMG waveforms associated with changes in the magnitude and direction of pulling forces. A cluster analysis partitioned the muscle synergies of the participants into a large group of clusters according to their similarity, indicating the use of a subjective combination of muscles to generate a multidirectional force vector in standing. Furthermore, we found a participant-specific distribution in the values of cosine directional tuning parameters of synergy amplitude coefficients, suggesting the existence of individual neuromechanical strategies to stabilize the whole-body posture. Our findings provide a starting point for the development of novel diagnostic tools to assess muscle coordination in postural control and lay the foundation for potential applications of muscle synergies in rehabilitation.

Three Levels of Neural Control Contributing to Performance-stabilizing Synergies in Multi-finger Tasks

We tested a hypothesis on force-stabilizing synergies during four-finger accurate force production at three levels: (1) The level of the reciprocal and coactivation commands, estimated as the referent coordinate and apparent stiffness of all four fingers combined; (2) The level of individual finger forces; and (3) The level of firing of individual motor units (MU). Young, healthy participants performed accurate four-finger force production at a comfortable, non-fatiguing level under visual feedback on the total force magnitude. Mechanical reflections of the reciprocal and coactivation commands were estimated using small, smooth finger perturbations applied by the "inverse piano" device. Firing frequencies of motor units in the flexor digitorum superficialis (FDS) and extensor digitorum communis (EDC) were estimated using surface recording. Principal component analysis was used to identify robust MU groups (MU-modes) with parallel changes in the firing frequency. The framework of the uncontrolled manifold hypothesis was used to compute synergy indices in the spaces of referent coordinate and apparent stiffness, finger forces, and MU-mode magnitudes. Force-stabilizing synergies were seen at all three levels. They were present in the MU-mode spaces defined for MUs in FDS, in EDC, and pooled over both muscles. No effects of hand dominance were seen. The synergy indices defined at different levels of analysis showed no correlations across the participants. The findings are interpreted within the theory of control with spatial referent coordinates for the effectors. We conclude that force stabilization gets contributions from three levels of neural control, likely associated with cortical, subcortical, and spinal circuitry.

NeuroMotion: Open-source platform with neuromechanical and deep network modules to generate surface EMG signals during voluntary movement

Neuromechanical studies investigate how the nervous system interacts with the musculoskeletal (MSK) system to generate volitional movements. Such studies have been supported by simulation models that provide insights into variables that cannot be measured experimentally and allow a large number of conditions to be tested before the experimental analysis. However, current simulation models of electromyography (EMG), a core physiological signal in neuromechanical analyses, remain either limited in accuracy and conditions or are computationally heavy to apply. Here, we provide a computational platform to enable future work to overcome these limitations by presenting NeuroMotion, an open-source simulator that can modularly test a variety of approaches to the full-spectrum synthesis of EMG signals during voluntary movements. We demonstrate NeuroMotion using three sample modules. The first module is an upper-limb MSK model with OpenSim API to estimate the muscle fibre lengths and muscle activations during movements. The second module is BioMime, a deep neural network-based EMG generator that receives nonstationary physiological parameter inputs, like the afore-estimated muscle fibre lengths, and efficiently outputs motor unit action potentials (MUAPs). The third module is a motor unit pool model that transforms the muscle activations into discharge timings of motor units. The discharge timings are convolved with the output of BioMime to simulate EMG signals during the movement. We first show how MUAP waveforms change during different levels of physiological parameter variations and different movements. We then show that the synthetic EMG signals during two-degree-of-freedom hand and wrist movements can be used to augment experimental data for regressing joint angles. Ridge regressors trained on the synthetic dataset were directly used to predict joint angles from experimental data. In this way, NeuroMotion was able to generate full-spectrum EMG for the first use-case of human forearm electrophysiology during voluntary hand, wrist, and forearm movements. All intermediate variables are available, which allows the user to study cause-effect relationships in the complex neuromechanical system, fast iterate algorithms before collecting experimental data, and validate algorithms that estimate non-measurable parameters in experiments. We expect this modular platform will enable validation of generative EMG models, complement experimental approaches and empower neuromechanical research.

Synaptic architecture of leg and wing premotor control networks in Drosophila

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles1. MN activity is coordinated by complex premotor networks that facilitate the contribution of individual muscles to many different behaviours2-6. Here we use connectomics7 to analyse the wiring logic of premotor circuits controlling the Drosophila leg and wing. We find that both premotor networks cluster into modules that link MNs innervating muscles with related functions. Within most leg motor modules, the synaptic weights of each premotor neuron are proportional to the size of their target MNs, establishing a circuit basis for hierarchical MN recruitment. By contrast, wing premotor networks lack proportional synaptic connectivity, which may enable more flexible recruitment of wing steering muscles. Through comparison of the architecture of distinct motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.

Muscle synergies are shared across fundamental subtasks in complex movements of skateboarding

A common theory of motor control posits that movement is controlled by muscle synergies. However, the behavior of these synergies during highly complex movements remains largely unexplored. Skateboarding is a hardly researched sport that requires rapid motor control to perform tricks. The objectives of this study were to investigate three key areas: (i) whether motor complexity differs between skateboard tricks, (ii) the inter-participant variability in synergies, and (iii) whether synergies are shared between different tricks. Electromyography data from eight muscles per leg were collected from seven experienced skateboarders performing three different tricks (Ollie, Kickflip, 360°-flip). Synergies were extracted using non-negative matrix factorization. The number of synergies (NoS) was determined using two criteria based on the total variance accounted for (tVAF > 90% and adding an additional synergy does not increase tVAF > 1%). In summary: (i) NoS and tVAF did not significantly differ between tricks, indicating similar motor complexity. (ii) High inter-participant variability exists across participants, potentially caused by the low number of constraints given to perform the tricks. (iii) Shared synergies were observed in every comparison of two tricks. Furthermore, each participant exhibited at least one synergy vector, which corresponds to the fundamental 'jumping' task, that was shared through all three tricks.

Patterns and assessment of spastic hemiplegic gait

Hemiparetic gait disorders are common in stroke survivors. A circumductory gait is often considered the typical hemiparetic gait. In clinical practice, a wide spectrum of abnormal gait patterns is observed, depending on the severity of weakness and spasticity, and the anatomical distribution of spasticity. Muscle strength is the key determinant of gait disorders in hemiparetic stroke survivors. Spasticity and its associated involuntary activation of synergistic spastic muscles often alter posture of involved joint(s) and subsequently the alignment of hip, knee, and ankle joints, resulting in abnormal gait patterns. Due to combinations of various levels of muscle weakness and spasticity and their interactions with ground reaction force, presentations of gait disorders are variable. From a neuromechanical perspective, a stepwise visual gait analysis approach is proposed to identify primary underlying causes. In this approach, the pelvic and hip joint movement is examined first. The pelvic girdle constitutes three kinematic determinants. Its abnormality determines the body vector and compensatory kinetic chain reactions in the knee and ankle joints. The second step is to assess the ankle and foot complex abnormality. The last step is to examine abnormality of the knee joint. Assessment of muscle strength and spasticity of hip, knee, and ankle/foot joints needs to be performed before these steps. Lidocaine nerve blocks can be a useful diagnostic tool. Recognizing different patterns and identifying the primary causes are critical to developing clinical interventions to improve gait functions.

Arm muscle synergies enhance hand posture prediction in combination with forearm muscle synergies

Objective.We analyze and interpret arm and forearm muscle activity in relation with the kinematics of hand pre-shaping during reaching and grasping from the perspective of human synergistic motor control.Approach.Ten subjects performed six tasks involving reaching, grasping and object manipulation. We recorded electromyographic (EMG) signals from arm and forearm muscles with a mix of bipolar electrodes and high-density grids of electrodes. Motion capture was concurrently recorded to estimate hand kinematics. Muscle synergies were extracted separately for arm and forearm muscles, and postural synergies were extracted from hand joint angles. We assessed whether activation coefficients of postural synergies positively correlate with and can be regressed from activation coefficients of muscle synergies. Each type of synergies was clustered across subjects.Main results.We found consistency of the identified synergies across subjects, and we functionally evaluated synergy clusters computed across subjects to identify synergies representative of all subjects. We found a positive correlation between pairs of activation coefficients of muscle and postural synergies with important functional implications. We demonstrated a significant positive contribution in the combination between arm and forearm muscle synergies in estimating hand postural synergies with respect to estimation based on muscle synergies of only one body segment, either arm or forearm (p< 0.01). We found that dimensionality reduction of multi-muscle EMG root mean square (RMS) signals did not significantly affect hand posture estimation, as demonstrated by comparable results with regression of hand angles from EMG RMS signals.Significance.We demonstrated that hand posture prediction improves by combining activity of arm and forearm muscles and we evaluate, for the first time, correlation and regression between activation coefficients of arm muscle and hand postural synergies. Our findings can be beneficial for myoelectric control of hand prosthesis and upper-limb exoskeletons, and for biomarker evaluation during neurorehabilitation.

Corticospinal excitability during motor preparation of upper extremity reaches reflects flexor muscle synergies: A novel principal component-based motor evoked potential analyses

Background

Previous research has shown that noninvasive brain stimulation can be used to study how the central nervous system (CNS) prepares the execution of a motor task. However, these previous studies have been limited to a single muscle or single degree of freedom movements (e.g., wrist flexion). It is currently unclear if the findings of these studies generalize to multi-joint movements involving multiple muscles, which may be influenced by kinematic redundancy and muscle synergies.

Objective

The objective of this study was to characterize corticospinal excitability during motor preparation in the cortex prior to functional upper extremity reaches.

Methods

20 participants without neurological impairments volunteered for this study. During the experiment, the participants reached for a cup in response to a visual "Go Cue". Prior to movement onset, we used transcranial magnetic stimulation (TMS) to stimulate the motor cortex and measured the changes in motor evoked potentials (MEPs) in several upper extremity muscles. We varied each participant's initial arm posture and used a novel synergy-based MEP analysis to examine the effect of muscle coordination on MEPs. Additionally, we varied the timing of the stimulation between the Go Cue and movement onset to examine the time course of motor preparation.

Results

We found that synergies with strong proximal muscle (shoulder and elbow) components emerged as the stimulation was delivered closer to movement onset, regardless of arm posture, but MEPs in the distal (wrist and finger) muscles were not facilitated. We also found that synergies varied with arm posture in a manner that reflected the muscle coordination of the reach.

Conclusions

We believe that these findings provide useful insight into the way the CNS plans motor skills.

NSF DARE-transforming modeling in neurorehabilitation: a patient-in-the-loop framework

In 2023, the National Science Foundation (NSF) and the National Institute of Health (NIH) brought together engineers, scientists, and clinicians by sponsoring a conference on computational modelling in neurorehabiilitation. To facilitate multidisciplinary collaborations and improve patient care, in this perspective piece we identify where and how computational modelling can support neurorehabilitation. To address the where, we developed a patient-in-the-loop framework that uses multiple and/or continual measurements to update diagnostic and treatment model parameters, treatment type, and treatment prescription, with the goal of maximizing clinically-relevant functional outcomes. This patient-in-the-loop framework has several key features: (i) it includes diagnostic and treatment models, (ii) it is clinically-grounded with the International Classification of Functioning, Disability and Health (ICF) and patient involvement, (iii) it uses multiple or continual data measurements over time, and (iv) it is applicable to a range of neurological and neurodevelopmental conditions. To address the how, we identify state-of-the-art and highlight promising avenues of future research across the realms of sensorimotor adaptation, neuroplasticity, musculoskeletal, and sensory & pain computational modelling. We also discuss both the importance of and how to perform model validation, as well as challenges to overcome when implementing computational models within a clinical setting. The patient-in-the-loop approach offers a unifying framework to guide multidisciplinary collaboration between computational and clinical stakeholders in the field of neurorehabilitation.

Influence of Backpack Carriage and Walking Speed on Muscle Synergies in Healthy Children

Four to five muscle synergies account for children's locomotion and appear to be consistent across alterations in speed and slopes. Backpack carriage induces alterations in gait kinematics in healthy children, raising questions regarding the clinical consequences related to orthopedic and neurological diseases and ergonomics. However, to support clinical decisions and characterize backpack carriage, muscle synergies can help with understanding the alterations induced in this condition at the motor control level. In this study, we investigated how children adjust the recruitment of motor patterns during locomotion, when greater muscular demands are required (backpack carriage). Twenty healthy male children underwent an instrumental gait analysis and muscle synergies extraction during three walking conditions: self-selected, fast and load conditions. In the fast condition, a reduction in the number of synergies (three to four) was needed for reconstructing the EMG signal with the same accuracy as in the other conditions (three to five). Synergies were grouped in only four clusters in the fast condition, while five clusters were needed for the self-selected condition. The right number of clusters was not clearly identified in the load condition. Speed and backpack carriage altered nearly every spatial-temporal parameter of gait, whereas kinematic alterations reflected mainly hip and pelvis adaptations. Although the synergistic patterns were consistent across conditions, indicating a similar motor pattern in different conditions, the fast condition required fewer synergies for reconstructing the EMG signal with the same level of accuracy.

Two classes of action-stabilizing synergies reflecting spinal and supraspinal circuitry

We explored force-stabilizing synergies during accurate four-finger constant force production tasks in spaces of finger modes (commands to fingers computed to account for the finger interdependence) and of motor unit (MU) firing frequencies. The main specific hypothesis was that the multifinger synergies would disappear during unintentional force drifts without visual feedback on the force magnitude, whereas MU-based synergies would be robust to such drifts. Healthy participants performed four-finger accurate cyclical force production trials followed by trials of constant force production. Individual MUs were identified in the flexor digitorum superficialis (FDS) and extensor digitorum communis (EDC). Principal component analysis was applied to motor unit frequencies to identify robust MU groups (MU-modes) with parallel scaling of the firing frequencies in FDS, in EDC, and the combined MUs of FDS + EDC. The framework of the uncontrolled manifold hypothesis was used to quantify force-stabilizing synergies when visual feedback on the force magnitude was available and 15 s after turning the visual feedback off. Removing visual feedback led to a force drift toward lower magnitudes, accompanied by the disappearance of multifinger synergies. In contrast, MU-mode synergies were minimally affected by removing visual feedback off and continued to be robust for the FDS and for the EDC, while being absent for the (FDS + EDC) analysis. We interpret the findings within the theory of hierarchical control of action with spatial referent coordinates. The qualitatively different behavior of the multifinger and MU-mode-based synergies likely reflects the difference in the involved neural circuitry, supraspinal for the former and spinal for the latter.NEW & NOTEWORTHY Two types of synergies, in the space of commands to individual fingers and in the space of motor unit groups, show qualitatively different behaviors during accurate multifinger force-production tasks. After removing visual feedback, finger force synergies disappear, whereas motor unit-based synergies persist. These results point at different neural circuitry involved in these two basic classes of synergies: supraspinal for multieffector synergies, and spinal for motor unit-based synergies.

Determining the Relationship between Squat Jump Performance and Knee Angle in Female University Students

The Squat Jump (SJ) test is widely recognized as a reliable test for assessing lower-limb explosive strength. However, uncertainty persists in the literature regarding the optimal starting positions for maximizing vertical jump performance. This uncertainty is exacerbated by a disproportionate focus on athletes in existing studies, with insufficient consideration being given to non-athletic women. To address this gap, this study investigated the influence of leg starting angle on explosive jump height in a homogeneous sample of non-athletic women. Thirty-two female students enrolled in a Sports Science master's degree program at the University of Salerno participated in the study. Descriptive statistics were employed to summarize data on various variables, and Pearson's correlations were calculated to assess the relationship between knee angle in the starting position and achieved jump height. The study revealed that different starting positions had a noteworthy impact on jump height among the participants. A strong negative correlation (-0.701) was identified between Squat Jump elevation and the knee angle in the starting position. Notably, 62.5% of the subjects opted for a starting knee position of approximately 70 degrees, with all of them consistently achieving a jump height associated with this specific angle. These findings provide valuable insights into the relationship between leg starting angle and explosive jump height in non-athletic women. The observed correlation underscores the significance of the starting position in Squat Jump performance. The prevalence of a specific knee angle choice among participants suggests potential implications for training and performance optimization in this sample.

Muscular Strategies for Correcting the Pelvic Position to Improve Posture-An Exploratory Study

The correction of postural weaknesses through the better positioning of the pelvis is an important approach in sports therapy and physiotherapy. The pelvic position in the sagittal plane is largely dependent on the muscular balance of the ventral and dorsal muscle groups. The aim of this exploratory study was to examine whether healthy persons use similar muscular activation patterns to correct their pelvic position or whether there are different motor strategies. The following muscles were recorded in 41 persons using surface electromyography (EMG): M. trapezius pars ascendens, M. erector spinae pars lumbalis, M. gluteus maximus, M. biceps femoris, M. rectus abdominis, and M. obliquus externus. The participants performed 10 voluntary pelvic movements (retroversion of the pelvis). The anterior pelvic tilt was measured videographically via marker points on the anterior and posterior superior iliac spine. The EMG data were further processed and normalized to the maximum voluntary contraction. A linear regression analysis was conducted to assess the relationship between changes in the pelvic tilt and muscle activities. Subsequently, a Ward clustering analysis was applied to detect potential muscle activation patterns. The differences between the clusters and the pelvic tilt were examined using ANOVA. Cluster analysis revealed the presence of four clusters with different muscle activation patterns in which the abdominal muscles and dorsal muscle groups were differently involved. However, the gluteus maximus muscle was involved in every activation pattern. It also had the strongest correlation with the changes in pelvic tilt. Different individual muscle patterns are used by different persons to correct pelvic posture, with the gluteus maximus muscle apparently playing the most important role. This can be important for therapy, as different muscle strategies should be trained depending on the individually preferred motor patterns.

Few sex-specific effects of fatigue on muscle synergies in a repetitive pointing task

Previous studies have identified some sex differences in how individual muscles change their activation during repetitive multi-joint arm motion-induced fatigue. However, little is known about how indicators of multi-muscle coordination change with fatigue in males and females. Fifty-six (29 females) asymptomatic young adults performed a repetitive, forward-backward pointing task until scoring 8/10 on a Borg CR10 scale while surface electromyographic activity of upper trapezius, anterior deltoid, biceps brachii, and triceps brachii was recorded. Activation coefficient, synergy structure, and relative weight of each muscle within synergies were calculated using the non-negative matrix factorization method. Two muscle synergies were extracted from the fatiguing task. The synergy structures were mostly preserved after fatigue, while the activation coefficients were altered. A significant Sex × Fatigue interaction effect showed more use of the anterior deltoid in males especially before fatigue in synergy 1 during shoulder stabilization (p = 0.04). As for synergy 2, it was characterized by variations in the relative weight of biceps, which was higher by 16 % in females compared to males (p = 0.04), and increased with fatigue (p = 0.03) during the elbow flexion acceleration phase and the deceleration phase of the backward pointing movement. Findings suggest that both sexes adapted to fatigue similarly, using fixed synergy structures, with alterations in synergy activation patterns and relative weights of individual muscles. Results support previous findings of an important role for the biceps and anterior deltoid in explaining sex differences in patterns of repetitive motion-induced upper limb fatigue.

Balance and Muscle Synergies During a Single-Limb Stance Task in Individuals With Chronic Ankle Instability

The aim of this study was to investigate balance performance and muscle synergies during a Single-Limb Stance (SLS) task in individuals with Chronic Ankle Instability (CAI) and a group of healthy controls. Twenty individuals with CAI and twenty healthy controls were asked to perform a 30-second SLS task in Open-Eyes (OE) and Closed-Eyes (CE) conditions while standing on a force platform with the injured or the dominant limb, respectively. The activation of 13 muscles of the lower limb, hip, and back was recorded by means of surface electromyography. Balance performance was assessed by identifying the number and the duration of SLS epochs, and the Root-Mean-Square (RMS) in Antero-Posterior (AP) and Medio-Lateral (ML) directions of the body-weight normalized ground reaction forces. The optimal number of synergies, weight vectors, and activation coefficients were also analyzed. CAI group showed a higher number and a shorter duration of SLS epochs and augmented ground reaction force RMS in both AP and ML directions compared to controls. Both groups showed an increase in the RMS in AP and ML forces in CE compared to OE. Both groups showed 4 optimal synergies in CE, while controls showed 5 synergies in OE. CAI showed a significantly higher weight of knee flexor muscles in both OE and CE. In conclusion, muscle synergies analysis provided an in-depth knowledge of motor control mechanisms in CAI individuals. They showed worse balance performance, a lower number of muscle synergies in a CE condition and abnormal knee flexor muscle activation compared to healthy controls.

Effects of fatigue on intramuscle force-stabilizing synergies

We applied the recently introduced concept of intramuscle synergies in spaces of motor units (MUs) to quantify indexes of such synergies in the tibialis anterior during ankle dorsiflexion force production tasks and their changes with fatigue. We hypothesized that MUs would be organized into robust groups (MU modes), which would covary across trials to stabilize force magnitude, and the indexes of such synergies would drop under fatigue. Healthy, young subjects (n = 15; 8 females) produced cyclical, isometric dorsiflexion forces while surface electromyography was used to identify action potentials of individual MUs. Principal component analysis was used to define MU modes. The framework of the uncontrolled manifold (UCM) was used to analyze intercycle variance and compute the synergy index, ΔVZ. Cyclical force production tasks were repeated after a nonfatiguing exercise (control) and a fatiguing exercise. Across subjects, fatigue led, on average, to a 43% drop in maximal force and fewer identified MUs per subject (29.6 ± 2.1 vs. 32.4 ± 2.1). The first two MU modes accounted for 81.2 ± 0.08% of variance across conditions. Force-stabilizing synergies were present across all conditions and were diminished after fatiguing exercise (1.49 ± 0.40) but not control exercise (1.76 ± 0.75). Decreased stability after fatigue was caused by an increase in the amount of variance orthogonal to the UCM. These findings contrast with earlier studies of multieffector synergies demonstrating increased synergy index under fatigue. We interpret the results as reflections of a drop in the gain of spinal reflex loops under fatigue. The findings corroborate an earlier hypothesis on the spinal nature of intramuscle synergies.NEW & NOTEWORTHY Across multielement force production tasks, fatigue of an element leads to increased indexes of force stability (synergy indexes). Here, however, we show that groups of motor units in the tibialis anterior show decreased indexes of force-stabilizing synergies after fatiguing exercise. These findings align intramuscle synergies with spinal mechanisms, in contrast to the supraspinal control of multimuscle synergies.

Multipoint surface electromyography measurement using bull's-eye electrodes for wide-area topographic analysis

BACKGROUND

Surface electromyography (sEMG) is primarily used to analyze individual and neighboring muscle activity. However, using a broader approach can enable simultaneous measurement of multiple muscles, which is essential for understanding muscular coordination. Using the "bull's-eye electrode," which allows bipolar derivation without directional dependence, enables wide-area multipoint sEMG measurements. This study aims to establish a multipoint measurement system and demonstrate its effectiveness and evaluates forearm fatigue and created topographic maps during a grasping task.

METHODS

Nine healthy adults with no recent arm injuries or illnesses participated in this study. They performed grasping tasks using their dominant hand, while bull's-eye electrodes recorded their muscle activity. To validate the effectiveness of the system, we calculated the root mean squares of muscle activity and entropy, an indicator of muscle activity distribution, and compared them over time.

RESULTS

The entropy analysis demonstrated a significant time-course effect with increased entropy over time, suggesting increased forearm muscle uniformity, which is possibly indicative of fatigue. Topographic maps visually displayed muscle activity, revealing notable intersubject variations.

DISCUSSION

Bull's-eye electrodes facilitated the capture of nine homogeneous muscle activity points, enabling the creation of topographic images. The entropy increased progressively, suggesting an adaptive muscle coordination response to fatigue. Despite some limitations, such as inadequate measurement of the forearm muscles' belly, the system is an unconventional measurement method.

CONCLUSION

This study established a robust system for wide-area multipoint sEMG measurements using a bull's-eye electrode setup. This system effectively evaluates muscle fatigue and provides a comprehensive topographic view of muscle activity. These results mark a significant step towards developing a future multichannel sEMG system with enhanced measurement points and improved wearability.

TRIAL REGISTRATION

This study was approved by the Ethics Committee of Chiba University Graduate School of Engineering (acceptance number: R4-12, Acceptance date: November 04, 2022).

Does Spasticity Correlate With Motor Impairment in the Upper and Lower Limbs in Ambulatory Chronic Stroke Survivors?

OBJECTIVE

This study aimed to explore correlations between spasticity and motor impairments in the upper and lower limbs in ambulatory chronic stroke survivors.

DESIGN

We performed clinical assessments in 28 ambulatory chronic stroke survivors with spastic hemiplegia (female: 12; male: 16; mean ages = 57.8 ± 11.8 yrs; 76 ± 45 mos after stroke).

RESULTS

In the upper limb, spasticity index and Fugl-Meyer Motor Assessment showed a significant correlation. Spasticity index for the upper limb showed a significant negative correlation with handgrip strength of the affected side ( r = -0.4, P = 0.035) while Fugl-Meyer Motor Assessment for the upper limb had a significant positive correlation ( r = 0.77, P < 0.001). In the LL, no correlation was found between SI_LL and FMA_LL. There was a significant and high correlation between timed up and go test and gait speed ( r = 0.93, P < 0.001). Gait speed was positively correlated with Spasticity index for the lower limb ( r = 0.48, P = 0.01), and negatively correlated with Fugl-Meyer Motor Assessment for the lower limb ( r = -0.57, P = 0.002). Age and time since stroke showed no association in analyses for both upper limb and lower limb.

CONCLUSIONS

Spasticity has a negative correlation on motor impairment in the upper limb but not in the lower limb. Motor impairment was significantly correlated with grip strength in the upper limb and gait performance in the lower limb of ambulatory stroke survivors.

Consistent control information driven musculoskeletal model for multiday myoelectric control

Objective.Musculoskeletal model (MM)-based myoelectric interface has aroused great interest in human-machine interaction. However, the performance of electromyography (EMG)-driven MM in long-term use would be degraded owing to the inherent non-stationary characteristics of EMG signals. Here, to improve the estimation performance without retraining, we proposed a consistent muscle excitation extraction approach based on an improved non-negative matrix factorization (NMF) algorithm for MM when applied to simultaneous hand and wrist movement prediction.Approach.We added constraints andL2-norm regularization terms to the objective function of classic NMF regarding muscle weighting matrix and time-varying profiles, through which stable muscle synergies across days were identified. The resultant profiles of these synergies were then used to drive the MM. Both offline and online experiments were conducted to evaluate the performance of the proposed method in inter-day scenarios.Main results.The results demonstrated significantly better and more robust performance over several competitive methods in inter-day experiments, including machine learning methods, EMG envelope-driven MM, and classic NMF-based MM. Furthermore, the analysis of control information on different days revealed the effectiveness of the proposed method in obtaining consistent muscle excitations.Significance.The outcomes potentially provide a novel and promising pathway for the robust and zero-retraining control of myoelectric interfaces.

Clinical, Kinematic and Muscle Assessment of Bilateral Coordinated Upper-Limb Movements Following Cervical Spinal Cord Injury

Cervical spinal cord injury (cSCI) often results in bilateral impairment of the arms, leading to difficulties in performing daily activities. However, little is known about the neuromotor alterations that affect the ability of individuals with cSCI to perform coordinated movements with both arms. To address this issue, we developed and tested a functional assessment that integrates clinical, kinematic, and muscle activity measures, including the evaluation of bilateral arm movements. Twelve subjects with a C5-C7 spinal lesion and six unimpaired subjects underwent an evaluation that included three tests: the Manual Muscle Test, Range Of Motion test and Arm stabilisation test, a subsection of the "Van Lieshout arm/hand function test". During the latter, we recorded kinematic and muscle activity data from the upper-body during the execution of a set of movements that required participants to stabilize both arms against gravity at different configurations. Analytical methods, including muscle synergies, spinal maps, and Principal Component Analysis, were used to analyse the data. Clinical tests detected limitations in shoulder abduction-flexion of cSCI participants and alterations in elbows-wrists motor function. The instrumented assessment provided insight into how these limitations impacted the ability of cSCI participants to perform bilateral movements. They exhibited severe difficulty in performing movements involving over-the-shoulder motion and shoulder internal rotation due to altered patterns of activity of the scapular stabilizer muscles, latissimus dorsi, pectoralis, and triceps. Our findings shed light on the bilateral neuromotor changes that occur post-cSCI addressing not only motor deficits, but also the underlying abnormal, weak, or silent muscle activations.

Age, Cognitive Task, and Arm Position Differently Affect Muscle Synergy Recruitment but have Similar Effects on Walking Balance

Age modifies walking balance and neuromuscular control. Cognitive and postural constraints can increase walking balance difficulty and magnify age-related differences. However, how such challenges affect neuromuscular control remains unknown. We determined the effects of age, cognitive task, and arm position on neuromuscular control of walking balance. Young (YA) and older adults (OA) walked on a 6-cm wide beam with and without arm crossing and a cognitive task. Walking balance was quantified by the distance walked on the beam. We also computed step speed, margin of stability, and cognitive errors. Neuromuscular control was determined through muscle synergies extracted from 13 right leg and trunk muscles. We analyzed neuromuscular complexity by the number of synergies and the variance accounted for by the first synergy, coactivity by the number of significantly active muscles in each synergy, and efficiency by the sum of the activation of each significantly active muscle in each synergy. OA vs. YA walked a 14% shorter distance, made 12 times more cognitive errors, and showed less complex and efficient neuromuscular control. Cognitive task reduced walking balance mainly in OA. Decreases in step speed and margin of stability, along with increased muscle synergy coactivity and reduced efficiency were observed in both age groups. Arm-crossing also reduced walking balance mostly in OA, but step speed decreased mainly in YA, in whom the margin of stability increased. Arm-crossing reduced the complexity of synergies. Age, cognitive task, and arm position affect differently muscle synergy recruitment but have similar effects on walking balance.

Linking neural circuits to the mechanics of animal behavior in Drosophila larval locomotion

The motions that make up animal behavior arise from the interplay between neural circuits and the mechanical parts of the body. Therefore, in order to comprehend the operational mechanisms governing behavior, it is essential to examine not only the underlying neural network but also the mechanical characteristics of the animal's body. The locomotor system of fly larvae serves as an ideal model for pursuing this integrative approach. By virtue of diverse investigation methods encompassing connectomics analysis and quantification of locomotion kinematics, research on larval locomotion has shed light on the underlying mechanisms of animal behavior. These studies have elucidated the roles of interneurons in coordinating muscle activities within and between segments, as well as the neural circuits responsible for exploration. This review aims to provide an overview of recent research on the neuromechanics of animal locomotion in fly larvae. We also briefly review interspecific diversity in fly larval locomotion and explore the latest advancements in soft robots inspired by larval locomotion. The integrative analysis of animal behavior using fly larvae could establish a practical framework for scrutinizing the behavior of other animal species.

Balance Control in Individuals with Hearing Impairment: A Systematic Review and Meta-Analysis

Comprehensive insights into balance control of individuals with hearing impairment are compared with individuals with hearing. Primary sources were obtained from 7 databases including PubMed, LILACS, SCOPUS, CINAHL, PEDro, CENTRAL, and Web of Science. The search period extended from inception until January 5, 2022. The systematic review included 24 studies and 27 trials, with a total of 2,148 participants. The meta-analysis showed a significant difference in the average balance control between individuals with hearing impairment and individuals with hearing, with individuals with hearing having a favorable advantage (p = 0.001). Additionally, average balance control was found to be in favor of individuals with hearing (p = 0.001) when comparing individuals with hearing impairment who participated in sports. Finally, individuals with hearing impairment who participated in sports demonstrated a significantly higher average difference in balance control (p = 0.001) when compared to sedentary people with hearing impairment. Our meta-analysis results indicate a balance defect in individuals with hearing impairment compared to individuals with hearing. In addition, with increasing age, the balance in individuals with hearing impairment improved. Additionally, the dependence of individuals with hearing impairment on the visual and proprioception systems to maintain balance increased. Finally, there was more dependence on the proprioception than the visual system, while individuals with hearing had stronger average balance control than individuals with hearing impairment who participated in sports, when compared to sedentary people with hearing impairment.

Integration of feedforward and feedback control in the neuromechanics of vertebrate locomotion: a review of experimental, simulation and robotic studies

Animal locomotion is the result of complex and multi-layered interactions between the nervous system, the musculo-skeletal system and the environment. Decoding the underlying mechanisms requires an integrative approach. Comparative experimental biology has allowed researchers to study the underlying components and some of their interactions across diverse animals. These studies have shown that locomotor neural circuits are distributed in the spinal cord, the midbrain and higher brain regions in vertebrates. The spinal cord plays a key role in locomotor control because it contains central pattern generators (CPGs) - systems of coupled neuronal oscillators that provide coordinated rhythmic control of muscle activation that can be viewed as feedforward controllers - and multiple reflex loops that provide feedback mechanisms. These circuits are activated and modulated by descending pathways from the brain. The relative contributions of CPGs, feedback loops and descending modulation, and how these vary between species and locomotor conditions, remain poorly understood. Robots and neuromechanical simulations can complement experimental approaches by testing specific hypotheses and performing what-if scenarios. This Review will give an overview of key knowledge gained from comparative vertebrate experiments, and insights obtained from neuromechanical simulations and robotic approaches. We suggest that the roles of CPGs, feedback loops and descending modulation vary among animals depending on body size, intrinsic mechanical stability, time required to reach locomotor maturity and speed effects. We also hypothesize that distal joints rely more on feedback control compared with proximal joints. Finally, we highlight important opportunities to address fundamental biological questions through continued collaboration between experimentalists and engineers.

Postural adjustments to self-triggered perturbations under conditions of changes in body orientation

We studied anticipatory and compensatory postural adjustments (APAs and CPAs) associated with self-triggered postural perturbations in conditions with changes in the initial body orientation. In particular, we were testing hypotheses on adjustments in the reciprocal and coactivation commands, role of proximal vs. distal muscles, and correlations between changes in indices of APAs and CPAs. Healthy young participants stood on a board with full support or reduced support area and held a standard load in the extended arms. They released the load in a self-paced manned with a standard small-amplitude arm movement. Electromyograms of 12 muscles were recorded and used to compute reciprocal and coactivation indices between three muscle pairs on both sides of the body. The subject's body was oriented toward one of three targets: straight ahead, 60° to the left, and 60° to the right. Body orientation has stronger effects on proximal muscle pairs compared to distal muscles. It led to more consistent changes in the reciprocal command compared to the coactivation command. Indices of APAs and CPAs showed positive correlations across conditions. We conclude that the earlier suggested hierarchical relations between the reciprocal and coactivation command could be task-specific. Predominance of negative or positive correlations between APA and CPA indices could also be task-specific.

Muscle Coordination Matters: Insights into Motor Planning using Corticospinal Responses during Functional Reaching

The central nervous system (CNS) moves the human body by forming a plan in the primary motor cortex and then executing this plan by activating the relevant muscles. It is possible to study motor planning by using noninvasive brain stimulation techniques to stimulate the motor cortex prior to a movement and examine the evoked responses. Studying the motor planning process can reveal useful information about the CNS, but previous studies have generally been limited to single degree of freedom movements ( e.g., wrist flexion). It is currently unclear if findings in these studies generalize to multi-joint movements, which may be influenced by kinematic redundancy and muscle synergies. Here, our objective was to characterize motor planning in the cortex prior to a functional reach involving the upper extremity. We asked participants to reach for a cup placed in front of them when presented with a visual "Go Cue". Following the go cue, but prior to movement onset, we used transcranial magnetic stimulation (TMS) to stimulate the motor cortex and measured the changes in the magnitudes of evoked responses in several upper extremity muscles (MEPs). We varied each participant's initial arm posture to examine the effect of muscle coordination on MEPs. Additionally, we varied the timing of the stimulation between the go cue and movement onset to examine the time course of changes in the MEPs. We found that the MEPs in all proximal (shoulder and elbow) muscles increased as the stimulation was delivered closer to movement onset, regardless of arm posture, but MEPs in the distal (wrist and finger) muscles were not facilitated or even inhibited. We also found that facilitation varied with arm posture in a manner that reflected the coordination of the subsequent reach. We believe that these findings provide useful insight into the way the CNS plans motor skills.

Motor unit-based synergies in a non-compartmentalized muscle

The concept of synergies has been used to address the grouping of motor elements contributing to a task with the covariation of these elements reflecting task stability. This concept has recently been extended to groups of motor units with parallel scaling of the firing frequencies with possible contributions of intermittent recruitment (MU-modes) in compartmentalized flexor and extensor muscles of the forearm stabilizing force magnitude in finger pressing tasks. Here, we directly test for the presence and behavior of MU-modes in the tibialis anterior, a non-compartmentalized muscle. Ten participants performed an isometric cyclical dorsiflexion force production task at 1 Hz between 20 and 40% of maximal voluntary contraction and electromyographic (EMG) data were collected from two high-density wireless sensors placed on the skin over the right tibialis anterior. EMG data were decomposed into individual motor unit frequencies and resolved into sets of MU-modes. Inter-cycle analysis of MU-mode magnitudes within the framework of the uncontrolled manifold (UCM) hypothesis was used to quantify force-stabilizing synergies. Two or three MU-modes were identified in all participants and trials accounting, on average, for 69% of variance and were robust to cross-validation measurements. Strong dorsiflexion force-stabilizing synergies in the space of MU-modes were present in all participants and for both electrode locations as reflected in variance within the UCM (median 954, IQR 511-1924) exceeding variance orthogonal to the UCM (median 5.82, IQR 2.9-17.4) by two orders of magnitude. In contrast, MU-mode-stabilizing synergies in the space of motor unit frequencies were not present. This study offers strong evidence for the existence of synergic control mechanisms at the level of motor units independent of muscle compartmentalization, likely organized within spinal cord circuitry.

Multi-muscle Synergies of Postural Control in Self- and External-Triggered Force Release During Simulated Archery Shooting

We investigated postural stability during simulated archery shooting. The experiment consisted of two force release conditions: self-triggered (time-set in a feedforward fashion) and external cue-triggered (time-set by reacting to external cue) conditions while standing on the force platform. The electromyography of leg muscles and the center of pressure (COP) were recorded. The notions of muscle-modes (M-modes) and multi-muscle synergies were employed to quantify the postural stability, which described covariation patterns of the M-modes to stabilize the COP. The result showed relatively strong postural stability in a self-triggered condition associated with consistent shooting performance. The current findings suggested that initiating force release in a feedforward fashion would be a beneficial strategy to ensure the consistency in shooting performance.

"Fine synergies" describe motor adaptation in people with drop foot in a way that supplements traditional "coarse synergies"

Synergy analysis via dimensionality reduction is a standard approach in biomechanics to capture the dominant features of limb kinematics or muscle activation signals, which can be called "coarse synergies." Here we demonstrate that the less dominant features of these signals, which are often explicitly disregarded or considered noise, can nevertheless exhibit "fine synergies" that reveal subtle, yet functionally important, adaptations. To find the coarse synergies, we applied non-negative matrix factorization (NMF) to unilateral EMG data from eight muscles of the involved leg in ten people with drop-foot (DF), and of the right leg of 16 unimpaired (control) participants. We then extracted the fine synergies for each group by removing the coarse synergies (i.e., first two factors explaining ≥ 85% of variance) from the data and applying Principal Component Analysis (PCA) to those residuals. Surprisingly, the time histories and structure of the coarse EMG synergies showed few differences between DF and controls-even though the kinematics of drop-foot gait is evidently different from unimpaired gait. In contrast, the structure of the fine EMG synergies (as per their PCA loadings) showed significant differences between groups. In particular, loadings for Tibialis Anterior, Peroneus Longus, Gastrocnemius Lateralis, Biceps and Rectus Femoris, Vastus Medialis and Lateralis muscles differed between groups ( p < 0.05 ). We conclude that the multiple differences found in the structure of the fine synergies extracted from EMG in people with drop-foot vs. unimpaired controls-not visible in the coarse synergies-likely reflect differences in their motor strategies. Coarse synergies, in contrast, seem to mostly reflect the gross features of EMG in bipedal gait that must be met by all participants-and thus show few differences between groups. However, drawing insights into the clinical origin of these differences requires well-controlled clinical trials. We propose that fine synergies should not be disregarded in biomechanical analysis, as they may be more informative of the disruption and adaptation of muscle coordination strategies in participants due to drop-foot, age and/or other gait impairments.

The effect of modified optic flow gain on quiet stance

Visual feedback provides critical information to support postural stability. Previous work has shown that magnifying visual feedback, such as by presenting individuals with biofeedback during balance tasks, can improve postural control. When studies manipulate the availability of optic flow directly, the conditions are often restricted to include an absence of visual feedback or sway referenced paradigms. Therefore, the aim of this study was to understand how manipulating the gain of optic flow contributes to quiet standing balance control among healthy adults. Optic flow was amplified or reduced relative to head motion using a virtual reality head-mounted display while participants stood quietly on either a firm or foam surface. Overall, when there was an increased reliance placed on the visual system by standing on foam, a tighter control of upright stance was observed as the gain of optic flow increased. Further, this study provided evidence that visual contributions to balance control may extend to higher frequencies of postural sway than previously theorized (greater than 0.1 Hz).

Preventing falls: the use of machine learning for the prediction of future falls in individuals without history of fall

Nowadays, it becomes of paramount societal importance to support many frail-prone groups in our society (elderly, patients with neurodegenerative diseases, etc.) to remain socially and physically active, maintain their quality of life, and avoid their loss of autonomy. Once older people enter the prefrail stage, they are already likely to experience falls whose consequences may accelerate the deterioration of their quality of life (injuries, fear of falling, reduction of physical activity). In that context, detecting frailty and high risk of fall at an early stage is the first line of defense against the detrimental consequences of fall. The second line of defense would be to develop original protocols to detect future fallers before any fall occur. This paper briefly summarizes the current advancements and perspectives that may arise from the combination of affordable and easy-to-use non-wearable systems (force platforms, 3D tracking motion systems), wearable systems (accelerometers, gyroscopes, inertial measurement units-IMUs) with appropriate machine learning analytics, as well as the efforts to address these challenges.

Muscle coordination and recruitment during squat assistance using a robotic ankle-foot exoskeleton

Squatting is an intensive activity routinely performed in the workplace to lift and lower loads. The effort to perform a squat can decrease using an exoskeleton that considers individual worker's differences and assists them with a customized solution, namely, personalized assistance. Designing such an exoskeleton could be improved by understanding how the user's muscle activity changes when assistance is provided. This study investigated the change in the muscle recruitment and activation pattern when personalized assistance was provided. The personalized assistance was provided by an ankle-foot exoskeleton during squatting and we compared its effect with that of the no-device and unpowered exoskeleton conditions using previously collected data. We identified four main muscle recruitment strategies across ten participants. One of the strategies mainly used quadriceps muscles, and the activation level corresponding to the strategy was reduced under exoskeleton assistance compared to the no-device and unpowered conditions. These quadriceps dominant synergy and rectus femoris activations showed reasonable correlations (r = 0.65, 0.59) to the metabolic cost of squatting. These results indicate that the assistance helped reduce quadriceps activation, and thus, the metabolic cost of squatting. These outcomes suggest that the muscle recruitment and activation patterns could be used to design an exoskeleton and training methods.

Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals

Muscle synergy analysis is useful for investigating trunk coordination patterns based on the assumption that the central nervous system reduces the dimensionality of muscle activation to simplify movement. This study aimed to quantify the variability in trunk muscle synergy during various trunk motor tasks in healthy participants to provide reference data for evaluating trunk control strategies in patients and athletes. Sixteen healthy individuals performed 11 trunk movement and stability tasks with electromyography (EMG) recording of their spinal and abdominal muscles (6 bilaterally). Non-negative matrix factorization applied to the concatenated EMG of all tasks identified the five trunk muscle synergies (W) with their corresponding temporal patterns (C). The medians of within-cluster similarity defined by scalar products in W and rmax coefficient using the cross-correlation function in C were 0.73-0.86 and 0.64-0.75, respectively, while the inter-session similarities were 0.81-0.96 and 0.74-0.84, respectively. However, the lowest and highest values of both similarity indices were broad, reflecting the musculoskeletal system's redundancy within and between participants. Furthermore, the significant differences in the degree of variability between the trunk synergies may represent the different neural features of synergy organization and strategies to overcome the various mechanical demands of a motor task.

Optimum trajectory learning in musculoskeletal systems with model predictive control and deep reinforcement learning

From the computational point of view, musculoskeletal control is the problem of controlling high degrees of freedom and dynamic multi-body system that is driven by redundant muscle units. A critical challenge in the control perspective of skeletal joints with antagonistic muscle pairs is finding methods robust to address this ill-posed nonlinear problem. To address this computational problem, we implemented a twofold optimization and learning framework to be specialized in addressing the redundancies in the muscle control . In the first part, we used model predictive control to obtain energy efficient skeletal trajectories to mimick human movements. The second part is to use deep reinforcement learning to obtain a sequence of stimulus to be given to muscles in order to obtain the skeletal trajectories with muscle control. We observed that the desired stimulus to muscles is only efficiently constructed by integrating the state and control input in a closed-loop setting as it resembles the proprioceptive integration in the spinal cord circuits. In this work, we showed how a variety of different reference trajectories can be obtained with optimal control and how these reference trajectories are mapped to the musculoskeletal control with deep reinforcement learning. Starting from the characteristics of human arm movement to obstacle avoidance experiment, our simulation results confirm the capabilities of our optimization and learning framework for a variety of dynamic movement trajectories. In summary, the proposed framework is offering a pipeline to complement the lack of experiments to record human motion-capture data as well as study the activation range of muscles to replicate the specific trajectory of interest. Using the trajectories from optimal control as a reference signal for reinforcement learning implementation has allowed us to acquire optimum and human-like behaviour of the musculoskeletal system which provides a framework to study human movement in-silico experiments. The present framework can also allow studying upper-arm rehabilitation with assistive robots given that one can use healthy subject movement recordings as reference to work on the control architecture of assistive robotics in order to compensate behavioural deficiencies. Hence, the framework opens to possibility of replicating or complementing labour-intensive, time-consuming and costly experiments with human subjects in the field of movement studies and digital twin of rehabilitation.

Parietofrontal oscillations show hand-specific interactions with top-down movement plans

To generate a hand-specific reach plan, the brain must integrate hand-specific signals with the desired movement strategy. Although various neurophysiology/imaging studies have investigated hand-target interactions in simple reach-to-target tasks, the whole brain timing and distribution of this process remain unclear, especially for more complex, instruction-dependent motor strategies. Previously, we showed that a pro/anti pointing instruction influences magnetoencephalographic (MEG) signals in frontal cortex that then propagate recurrently through parietal cortex (Blohm G, Alikhanian H, Gaetz W, Goltz HC, DeSouza JF, Cheyne DO, Crawford JD. NeuroImage 197: 306-319, 2019). Here, we contrasted left versus right hand pointing in the same task to investigate 1) which cortical regions of interest show hand specificity and 2) which of those areas interact with the instructed motor plan. Eight bilateral areas, the parietooccipital junction (POJ), superior parietooccipital cortex (SPOC), supramarginal gyrus (SMG), medial/anterior interparietal sulcus (mIPS/aIPS), primary somatosensory/motor cortex (S1/M1), and dorsal premotor cortex (PMd), showed hand-specific changes in beta band power, with four of these (M1, S1, SMG, aIPS) showing robust activation before movement onset. M1, SMG, SPOC, and aIPS showed significant interactions between contralateral hand specificity and the instructed motor plan but not with bottom-up target signals. Separate hand/motor signals emerged relatively early and lasted through execution, whereas hand-motor interactions only occurred close to movement onset. Taken together with our previous results, these findings show that instruction-dependent motor plans emerge in frontal cortex and interact recurrently with hand-specific parietofrontal signals before movement onset to produce hand-specific motor behaviors.NEW & NOTEWORTHY The brain must generate different motor signals depending on which hand is used. The distribution and timing of hand use/instructed motor plan integration are not understood at the whole brain level. Using MEG we show that different action planning subnetworks code for hand usage and integrating hand use into a hand-specific motor plan. The timing indicates that frontal cortex first creates a general motor plan and then integrates hand specificity to produce a hand-specific motor plan.

Number of trials and data structure affect the number and components of muscle synergies in upper-limb reaching movements

Objective.Due to the variability of human movements, muscle activations vary among trials and subjects. However, few studies investigated how data organization methods for addressing variability impact the extracted muscle synergies.Approach.Fifteen healthy subjects performed a large set of upper limb multi-directional point-to-point reaching movements. Then, the study extracted muscle synergies under different data settings and investigated how data structure prior to synergy extraction, namely concatenation, averaging, and single trial, the number of considered trials, and the number of reaching directions affected the number and components of muscle synergies.Main results.The results showed that the number and components of synergies were significantly affected by the data structure. The concatenation method identified the highest number of synergies, and the averaging method usually found a smaller number of synergies. When the concatenated trials or reaching directions was lower than a minimum value, the number of synergies increased with the increase of the number of trials or reaching directions; however, when the number of trials or reaching directions reached a threshold, the number of synergies was usually constant or with less variation even when novel directions and trials were added. Similarity analysis also showed a slight increase when the number of trials or reaching directions was lower than a threshold. This study recommends that at least five trials and four reaching directions and the concatenation method are considered in muscle synergies analysis during upper limb tasks.Significance.This study makes the researchers focus on the variability analysis induced by the diseases rather than the techniques applied for synergies analysis and promotes applications of muscle synergies in clinical scenarios.

Complexity of locomotion activities in an outside-of-the-lab wearable motion capture dataset

Gait complexity is widely used to understand risk factors for injury, rehabilitation, the performance of assistive devices, and other matters of clinical interest. We analyze the complexity of out-of-the-lab locomotion activities via measures that have previously been used in gait analysis literature, as well as measures from other domains of data analysis. We categorize these broadly as quantifying either the intrinsic dimensionality, the variability, or the regularity, periodicity, or self-similarity of the data from a nonlinear dynamical systems perspective. We perform this analysis on a novel full-body motion capture dataset collected in out-of-the-lab conditions for a variety of indoor environments. This is a unique dataset with a large amount (over 24 h total) of data from participants behaving without low-level instructions in out-of-the-lab indoor environments. We show that reasonable complexity measures can yield surprising, and even profoundly contradictory, results. We suggest that future complexity analysis can use these guidelines to be more specific and intentional about what aspect of complexity a quantitative measure expresses. This will become more important as wearable motion capture technology increasingly allows for comparison of ecologically relevant behavior with lab-based measurements.

Similarity of hand muscle synergies elicited by transcranial magnetic stimulation and those found during voluntary movement

Converging evidence in human and animal models suggests that exogenous stimulation of the motor cortex (M1) elicits responses in the hand with similar modular structure to that found during voluntary grasping movements. The aim of this study was to establish the extent to which modularity in muscle responses to transcranial magnetic stimulation (TMS) to M1 resembles modularity in muscle activation during voluntary hand movements involving finger fractionation. Electromyography (EMG) was recorded from eight hand-forearm muscles in eight healthy individuals. Modularity was defined using non-negative matrix factorization to identify low-rank approximations (spatial muscle synergies) of the complex activation patterns of EMG data recorded during high-density TMS mapping of M1 and voluntary formation of gestures in the American Sign Language alphabet. Analysis of synergies revealed greater than chance similarity between those derived from TMS and those derived from voluntary movement. Both data sets included synergies dominated by single intrinsic hand muscles presumably to meet the demand for highly fractionated finger movement. These results suggest that corticospinal connectivity to individual intrinsic hand muscles may be combined with modular multimuscle activation via synergies in the formation of hand postures.NEW & NOTEWORTHY This is the first work to examine the similarity of modularity in hand muscle responses to transcranial magnetic stimulation (TMS) of the motor cortex and that derived from voluntary hand movement. We show that TMS-elicited muscle synergies of the hand, measured at rest, reflect those found in voluntary behavior involving finger fractionation. This work provides a basis for future work using TMS to investigate muscle activation modularity in the human motor system.

Synergies Stabilizing Vertical Posture in Spaces of Control Variables

In this study, we address the question: Can the central nervous system stabilize vertical posture in the abundant space of neural commands? We assume that the control of vertical posture is associated with setting spatial referent coordinates (RC) for the involved muscle groups, which translates into two basic commands, reciprocal and co-activation. We explored whether the two commands co-varied across trials to stabilize the initial postural state. Young, healthy participants stood quietly against an external horizontal load and were exposed to smooth unloading episodes. Linear regression between horizontal force and center of mass coordinate during the unloading phase was computed to define the intercept (RC) and slope (apparent stiffness, k). Hyperbolic regression between the intercept and slope across unloading episodes and randomization analysis both demonstrated high indexes of co-variation stabilizing horizontal force in the initial state. Higher co-variation indexes were associated with lower average k values across the participants suggesting destabilizing effects of muscle coactivation. Analysis of deviations in the {RC; k} space keeping the posture unchanged (motor equivalent) between two states separated by a voluntary quick body sway showed significantly larger motor equivalent deviations compared to non-motor equivalent ones. This is the first study demonstrating posture-stabilizing synergies in the space of neural control variables using various computational methods. It promises direct applications to studies of postural disorders and rehabilitation.

Estimation of Time-Frequency Muscle Synergy in Wrist Movements

Muscle synergy analysis is a kind of modularized decomposition of muscles during exercise controlled by the central nervous system (CNS). It can not only extract the synergistic muscles in exercise, but also obtain the activation states of muscles to reflect the coordination and control relationship between muscles. However, previous studies have mainly focused on the time-domain synergy without considering the frequency-specific characteristics within synergy structures. Therefore, this study proposes a novel method, named time-frequency non-negative matrix factorization (TF-NMF), to explore the time-varying regularity of muscle synergy characteristics of multi-channel surface electromyogram (sEMG) signals at different frequency bands. In this method, the wavelet packet transform (WPT) is used to transform the time-scale signals into time-frequency dimension. Then, the NMF method is calculated in each time-frequency window to extract the synergy modules. Finally, this method is used to analyze the sEMG signals recorded from 8 muscles during the conversion between wrist flexion (WF stage) and wrist extension (WE stage) movements in 12 healthy people. The experimental results show that the number of synergy modules in wrist flexion transmission to wrist extension (Motion Conversion, MC stage) is more than that in the WF stage and WE stage. Furthermore, the number of flexor and extensor muscle synergies in the frequency band of 0–125 Hz during the MC stage is more than that in the frequency band of 125–250 Hz. Further analysis shows that the flexion muscle synergies mostly exist in the frequency band of 140.625–156.25 Hz during the WF stage, and the extension muscle synergies appear in the frequency band of 125–156.25 Hz during the WE stage. These results can help to better understand the time-frequency features of muscle synergy, and expand study perspective related to motor control in nervous system.

Is modular control related to functional outcomes in individuals with knee osteoarthritis and following total knee arthroplasty?

BACKGROUND

Individuals who undergo total knee arthroplasty (TKA) for treatment of knee osteoarthritis often experience suboptimal outcomes. Investigation of neuromuscular control strategies in these individuals may reveal factors that contribute to these functional deficits. The purpose of this pilot study was to determine the relationship between patient function and modular control during gait before and after TKA.

METHODS

Electromyography data from 36 participants (38 knees) were collected from 8 lower extremity muscles on the TKA-involved limb during ≥5 over-ground walking trials before (n = 30), 6-months after (n = 26), and 24-months after (n = 13) surgery. Muscle modules were estimated using non-negative matrix factorization. The number of modules was determined from 500 resampled trials.

RESULTS

A higher number of modules was related to better performance-based and patient-reported function before and 6-months after surgery. Participants with organization similar to healthy, age-matched controls trended toward better function 24-months after surgery, though these results were not statistically significant. We also observed plasticity in the participants' modular control strategies, with 100% of participants who were present before and 24-months after surgery (10/10) demonstrating changes in the number of modules and/or organization of at least 1 module.

CONCLUSIONS

This pilot work suggests that functional improvements following TKA may initially present as increases in the number of modules recruited during gait. Subsequent improvements in function may present as improved module organization.

NOTEWORTHY

This work is the first to characterize motor modules in TKA both before and after surgery and to demonstrate changes in the number and organization of modules over the time course of recovery, which may be related to changes in patient function. The plasticity of modular control following TKA is a key finding which has not been previously documented and may be useful in predicting or improving surgical outcomes through novel rehabilitation protocols.

Muscle synergies of multi-directional postural control in astronauts on Earth after a long-term stay in space

Movements of the human biological system have adapted to the physical environment under the 1-g gravitational force on Earth. However, the effects of microgravity in space on the underlying functional neuromuscular control behaviors remain poorly understood. Here, we aimed to elucidate the effects of prolonged exposure to a microgravity environment on the functional coordination of multiple muscle activities. The activities of 16 lower limb muscles of 5 astronauts who stayed in space for at least 3 months were recorded while they maintained multidirectional postural control during bipedal standing. The coordinated activation patterns of groups of muscles, i.e., muscle synergies, were estimated from the muscle activation datasets using a factorization algorithm. The experiments were repeated a total of 5 times for each astronaut, once before and 4 times after spaceflight. The compositions of muscle synergies were altered, with a constant number of synergies, after long-term exposure to microgravity, and the extent of the changes was correlated with the severity of the deficits in postural stability. Furthermore, the muscle synergies extracted 3 months after the return were similar in their activation profile but not in their muscle composition compared with those extracted in the preflight condition. These results suggest that the modularity in the neuromuscular system became reorganized to adapt to the microgravity environment and then possibly reoptimized to the new sensorimotor environment after the astronauts were re-exposed to a gravitational force. It is expected that muscle synergies can be used as physiological markers of the status of astronauts with gravity-dependent change.

Postural control strategies are revealed by the complexity of fractional components of COP

The complexity of the center of pressure (COP) provides important information regarding the underlying mechanisms of postural control. The relationships between COP complexity and balance performance are not fully established and might depend on the task constraints and the filtering decomposition of the COP signal. This study assessed COP complexity under different task constraints and it was assessed if emergent dynamics of COP fluctuations differ according to fractional components of COP related to peripheral or central adjustments. One hundred and sixty-two participants performed two sitting balance tasks. Accuracy was required by following a target that moved in the mediolateral (ML) or in the anteroposterior (AP) axis. Complexity dynamics of COP were addressed through Detrended Fluctuation Analysis (DFA) in the axis constrained by accuracy requirements and in the one non-constrained. Decomposition of COP components was applied by low-pass, band-pass and high-pass filters. DFA of low-pass and band-pass components of COP in the constrained axis were small-to-moderately related (r = .190 to .237) to balance performance. DFA of the high-pass component of the COP exhibited the opposite relationship (r = -.283 to -.453) in both axes (constrained and non-constrained). This study evidences that COP complexity is linked to better performance. This positive relationship complexity/performance is observed in the low- and mid-frequency components of the COP. These components might be related to central mechanisms of postural control. The lack of relationships between the different frequencies analyzed in the study suggests that they are capturing different components of postural control.

Neural Network Models for Spinal Implementation of Muscle Synergies

Muscle synergies have been proposed as functional modules to simplify the complexity of body motor control; however, their neural implementation is still unclear. Converging evidence suggests that output projections of the spinal premotor interneurons (PreM-INs) underlie the formation of muscle synergies, but they exhibit a substantial variation across neurons and exclude standard models assuming a small number of unitary “modules” in the spinal cord. Here we compared neural network models for muscle synergies to seek a biologically plausible model that reconciles previous clinical and electrophysiological findings. We examined three neural network models: one with random connections (non-synergy model), one with a small number of spinal synergies (simple synergy model), and one with a large number of spinal neurons representing muscle synergies with a certain variation (population synergy model). We found that the simple and population synergy models emulate the robustness of muscle synergies against cortical stroke observed in human stroke patients. Furthermore, the size of the spinal variation of the population synergy matched well with the variation in spinal PreM-INs recorded in monkeys. These results suggest that a spinal population with moderate variation is a biologically plausible model for the neural implementation of muscle synergies.

Synergies are minimally affected during emulation of cerebral palsy gait patterns

Muscle synergy analysis is commonly used to characterize motor control during dynamic tasks like walking. For clinical populations, such as children with cerebral palsy (CP), synergies are altered compared to nondisabled (ND) peers and have been associated with both function and treatment outcomes. However, the factors that contribute to altered synergies remain unclear. In particular, the extent to which synergies reflect altered biomechanics (e.g., changes in gait) or underlying neurologic injury is debated. To evaluate the effect that altered biomechanics have on synergies, we compared synergy complexity and structure while ND individuals (n = 14) emulated four common CP gait patterns (equinus, equinus-crouch, mild-crouch, and moderate crouch). Secondarily, we compared the similarity of ND synergies during emulation to synergies from a retrospective cohort of individuals with CP walking in similar gait patterns (n = 28 per pattern). During emulation, ND individuals recruited similar synergies as baseline walking. However, pattern-specific deviations in synergy activations and complexity emerged. In particular, equinus gait altered plantarflexor activation timing and reduced synergy complexity. Importantly, ND synergies during emulation were distinct from those observed in CP for all gait patterns. These results suggest that altered gait patterns are not primarily driving the changes in synergies observed in CP, highlighting the value of using synergies as a tool to capture patient-specific differences in motor control. However, they also highlight the sensitivity of both synergy activations and complexity to altered biomechanics, which should be considered when using these measures in clinical care.