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Neural control of movement can only be realized though the interaction between the mechanical properties of the limb and the environment. Thus, a fundamental question is whether anatomy has evolved to simplify neural control by shaping these interactions in a beneficial way. This inductive data-driven study analyzed the patterns of muscle actions across multiple joints using the musculoskeletal model of the human upper limb. This model was used to calculate muscle lengths across the full range of motion of the arm and examined the correlations between these values between all pairs of muscles. Musculoskeletal coupling was quantified using hierarchical clustering analysis. Muscle lengths between multiple pairs of muscles across multiple postures were highly correlated. These correlations broadly formed two proximal and distal groups, where proximal muscles of the arm were correlated with each other and distal muscles of the arm and hand were correlated with each other, but not between groups. Using hierarchical clustering, between 11 and 14 reliable muscle groups were identified. This shows that musculoskeletal anatomy does indeed shape the mechanical interactions by grouping muscles into functional clusters that generally match the functional repertoire of the human arm. Together, these results support the idea that the structure of the musculoskeletal system is tuned to solve movement complexity problem by reducing the dimensionality of available solutions.

[This corrects the article DOI: 10.1371/journal.pone.0164050.].

The sensorimotor integration during unconstrained reaching movements in the presence of variable environmental forces remains poorly understood. The objective of this study was to quantify how much the primary afferent activity of muscle spindles can contribute to shaping muscle coactivation patterns during reaching movements with complex dynamics. To achieve this objective, we designed a virtual reality task that guided healthy human participants through a set of planar reaching movements with controlled kinematic and dynamic conditions that were accompanied by variable muscle co-contraction. Next, we approximated the Ia afferent activity using a phenomenological model of the muscle spindle and muscle lengths derived from a musculoskeletal model. The parameters of the spindle model were altered systematically to evaluate the effect of fusimotor drive on the shape of the temporal profile of afferent activity during movement. The experimental and simulated data were analyzed with hierarchical clustering. We found that the pattern of co-activation of agonistic and antagonistic muscles changed based on whether passive forces in each movement played assistive or resistive roles in limb dynamics. The reaching task with assistive limb dynamics was associated with the most muscle co-contraction. In contrast, the simulated Ia afferent profiles were not changing between tasks and they were largely reciprocal with homonymous muscle activity. Simulated physiological changes to the fusimotor drive were not sufficient to reproduce muscle co-contraction. These results largely rule out the static set and α-γ coactivation as the main types of fusimotor drive that transform the monosynaptic Ia afferent feedback into task-dependent co-contraction of antagonistic muscles. We speculate that another type of nonlinear transformation of Ia afferent signals that is independent of signals modulating the activity of α motoneurons is required for Ia afferent-based co-contraction. This transformation could either be applied through a complex nonlinear profile of fusimotor drive that is not yet experimentally observed or through presynaptic inhibition.

Human locomotion is a highly adaptive motor skill that adjusts to new environmental demands through learning. Split-belt treadmill paradigms have advanced our understanding of gait adaptation. Most studies have examined gait when the belts move at different speeds in the same direction. We are studying muscle activation patterns during an asymmetric gait, when the treadmill belts move at equal speed in opposite directions, i.e., bidirectional walking (BDW). Twelve healthy volunteers performed a single session on a split-belt treadmill. We simultaneously collected ground reaction forces via treadmill force plates, joint kinematics via motion capture, and surface electromyography (EMG) from bilateral soleus (SOL) and tibialis anterior (TA) muscles. Participants started with 2 min of forward walking (FW), followed with four 5-min blocks of BDW separated by 1-min standing rest intervals, and finished the session with 2 min of FW (washout). All participants successfully completed the protocol. We analyzed EMG signals for temporal activation patterns (rhythm generation) and amplitude characteristics (pattern formation). EMG recordings revealed antiphasic activation of SOL and TA muscles bilaterally throughout all trials. During BDW, the backward-moving leg's TA showed prolonged activation patterns that persisted during washout FW, suggesting retention of adaptive changes. Burst-to-cycle duration ratios showed transient changes during early adaptation but remained relatively stable across conditions, demonstrating robust rhythm generation despite adaptive modulation of activation patterns during BDW. These findings demonstrate that BDW induces asymmetric adjustments in muscle activation patterns. Rhythm generation (timing) did not significantly differ between BDW and FW. However, we did observe changes in pattern formation (i.e., EMG profiles) during FW pre- and post-BDW training. Burst-to-cycle duration ratios, as a measure of rhythm generation, showed changes during early adaptation, particularly the increase in right SOL and right TA during block 1, though these changes did not reach statistical significance and largely returned to baseline during washout. The underlying pattern formation structure, was maintained across all conditions, with selective amplitude modulations rather than fundamental reorganization of activation patterns. The substantial temporal adjustments in the backward-moving leg's SOL and phase shifts in TA provide the neuromuscular mechanism driving the bilateral step-length reduction, altered inter-limb phasing, and asymmetric double stance timing. These results extend our understanding of locomotor control by suggesting how the central nervous system (CNS) dynamically recalibrates muscle timing and amplitude to maintain satisfactory locomotion under new environmental demands.

Humans can acquire and maintain motor skills throughout their lives through motor learning. Motor learning and skill acquisition are essential for rehabilitation following neurological disease or injury. Adaptation, the initial stage of motor learning, involves short-term changes in motor performance in response to a new demand in the person's environment. Repeated adaptation can improve skill performance and result in long-term skill retention. Locomotor adaptation is extensively studied using split-belt treadmill paradigms. In this study we explored whether bidirectional walking (BDW) on a split-belt treadmill can induce short-term gait adaptations. Twelve healthy volunteers participated in our single session, starting with 2 minutes of normal walking (NW), followed by four 5-minute blocks of BDW with a 1-minute passive rest in between blocks, and ending with another 2-minute of NW. We recorded body kinematics and ground reaction forces throughout the experiment. Participants quickly adapted to BDW with both legs showing decreased step lengths. However, only the backward-walking leg exhibited aftereffects upon returning to NW, indicating short-term adaptation. Notable kinematic changes were observed, particularly in hip extension and pelvis tilt, though these varied among participants. Our findings suggest that BDW induces unilateral adaptations despite bilateral changes in gait, offering new insights into locomotor control and spinal CPG organization.

Hoffmann reflex (HR) operant conditioning has emerged as an important intervention in neurorehabilitation. During conditioning, the HR is elicited at low rates (∼0.2 Hz) to avoid the initial reduction in HR size that can occur over repeated stimulation, i.e., rate-dependent depression (RDD), thereby maintaining reflex size. This study investigated the impact of higher stimulation rates on HR size, where a stable, low-level, background electromyographic (EMG) signal is maintained over 225 conditioning trials in each of 30 sessions. A higher rate could shorten session length and/or number. Fifteen healthy participants maintained low background soleus EMG (5-18 µV, ∼1-3% of the maximum stimulation evoked direct muscle (M-wave) EMG response (M ) while standing. Soleus HR and M-wave recruitment curves were obtained at rates of 0.2, 1, and 2 Hz, from which M and H were calculated. Seventy-five HR trials (HRT) were collected for each stimulation rate at a target M-wave size (∼10-20% of M ). There was no evidence of RDD at higher stimulation rates. In addition, the mean HR over trials was reliable across participants and rates. The Intraclass Correlation Coefficient (ICC) was 0.965 (95%CI:0.915, 0.987). This study shows that H-reflex conditioning might be performed at rates up to 2 Hz with no RDD and with consistent HR values. A faster rate could increase the number of conditioning trials per session, reduce session duration, and/or reduce the number of sessions. It could thereby accelerate the conditioning process and make the process less demanding for participants. NIH Grant P41 EB018783 (Wolpaw), NYS Spinal Cord Injury Research Board C37714GG (Gupta) and C38338GG (Wolpaw), VA SPiRE NCT05880251 (Brangaccio), Stratton Veterans Affairs Medical Center.

The stabilizing role of sensory feedback in relation to realistic 3-dimensional movement dynamics remains poorly understood. The objective of this study was to quantify how primary afferent activity contributes to shaping muscle activity patterns during reaching movements. To achieve this objective, we designed a virtual reality task that guided healthy human subjects through a set of planar reaching movements with controlled kinematic and dynamic conditions that minimized inter-subject variability. Next, we integrated human upper-limb models of musculoskeletal dynamics and proprioception to analyze motion and major muscle activation patterns during these tasks. We recorded electromyographic and motion-capture data and used the integrated model to simulate joint kinematics, joint torques due to muscle contractions, muscle length changes, and simulated primary afferent feedback. The parameters of the primary afferent model were altered systematically to evaluate the effect of fusimotor drive. The experimental and simulated data were analyzed with hierarchical clustering. We found that the muscle activity patterns contained flexible task-dependent groups that consisted of co-activating agonistic and antagonistic muscles that changed with the dynamics of the task. The activity of muscles spanning only the shoulder generally grouped into a proximal cluster, while the muscles spanning the wrist grouped into a distal cluster. The bifunctional muscle spanning the shoulder and elbow were flexibly grouped with either proximal or distal cluster based on the dynamical requirements of the task. The composition and activation of these groups reflected the relative contribution of active and passive forces to each motion. In contrast, the simulated primary afferent feedback was most related to joint kinematics rather than dynamics, even though the primary afferent models had nonlinear dynamical components and variable fusimotor drive. Simulated physiological changes to the fusimotor drive were not sufficient to reproduce the dynamical features in muscle activity pattern. Altogether, these results suggest that sensory feedback signals are in a different domain from that of muscle activation signals. This indicates that to solve the neuromechanical problem, the central nervous system controls limb dynamics through task-dependent co-activation of muscles and non-linear modulation of monosynaptic primary afferent feedback. Footnotes * Parameter exploration for the primary afferent model was performed to simulate the effect of the fusimotor drive. The results are summarized in the manuscript and in the new Figure 7.

Musculoskeletal modeling has significant potential as a translational and clinical research tool for examining neuromuscular injuries and disorders. However its adoption has been limited due, in part, to the difficulty of measuring the subject-specific physiological measures that define model parameters. These measurements may require substantial time and expensive methods, such as MRI, to determine the parameters of a model and thus ensure its accuracy. We used a Monte Carlo simulation to examine the impact of parameter variability on the ill-defined, inverse approximation of muscle activity. We first amalgamated previously published measurements of the physiological characteristics of the upper/lower arm and the biceps/triceps muscles. We then used the observed distributions of these measurements to set physiologically plausible boundaries on uniform distributions and then generated perturbed parameter sets. We computed the root mean squared error (RMSE) between muscle activity patterns generated by the perturbed model parameters to those generated by the original parameters. Regression models were fit to the RMSE of the approximated muscle activity patterns to determine the sensitivity of the simulation results to to variation in each parameter. We found that variation in parameters associated with muscle physiology had the most effect on RMSE, suggesting that these parameters may require subject-specific scaling, whereas parameters associated with skeletal bodies had less effect, and might be safely approximated by their population means.Competing Interest StatementThe authors have declared no competing interest.Footnotes* The manuscript has been updated to include the studies referenced in tables 1-4 in the bibliography. Supplemental Data has also been uploaded.

How the neural motor system recruits muscles to support the arm against gravity is a matter of active debate. It is unknown how the neural motor system compensates for the changing gravity-related joint moments either when holding a steady-state posture or during movement between postural steady states, e.g., during reaching. Here we used single-pulse transcranial magnetic stimulation to compare the roles that the human primary motor cortex plays in the muscle recruitment to compensate for gravity. We hypothesized that the motor cortex contributes to muscle recruitment to both maintain posture and to compensate for changes in gravitational passive joint moments during movement. To test this hypothesis, we used visual targets in virtual reality to instruct five postures and three movements with or against gravity. We then measured the amplitude and gain of motor evoked potentials in multiple muscles of the arm at several phases of the reaching motion and during posture maintenance. Stimulation below the resting motor threshold, calibrated to the biceps muscle, caused motor evoked potentials in all muscles during all postural and reaching tasks. The amplitude of motor evoked potentials was proportional to the motoneuronal excitability measured as muscle activity. The coefficient of proportionality was positively correlated with the postural component of muscle moment during posture and movement. Altogether our results support the hypothesis. The observed contribution of the motor cortex to the recruitment of multiple antagonistic muscles suggests a whole-limb strategy for overcoming passive gravity-related moments with both active muscle moments and muscle co-activation that modulates limb impedance. Competing Interest Statement The authors have declared no competing interest.

Polychlorinated biphenyls (PCBs) are persistent organic pollutants associated with metabolic disruption and nonalcoholic fatty liver disease (NAFLD). Based on their ability to activate the aryl hydrocarbon receptor (AhR), PCBs are subdivided into two classes: dioxin-like (DL) and non-dioxin-like (NDL) PCBs. Previously, we demonstrated that NDL PCBs compromised the liver to promote more severe diet-induced NAFLD. Here, the hepatic effects and potential mechanisms (by untargeted liver proteomics) of DL PCBs and NDL PCBs or co-exposure to both in diet-induced NAFLD are investigated. Male C57Bl/6 mice were fed a 42% fat diet and exposed to vehicle control; Aroclor1260 (20 mg/kg, NDL PCB mixture); PCB126 (20 μg/kg, DL PCB congener); or a mixture of Aroclor1260 (20 mg/kg) + PCB126 (20 μg/kg) for 12 weeks. Each exposure was associated with a distinct hepatic proteome. Phenotypic and proteomic analyses revealed increased hepatic inflammation and phosphoprotein signaling disruption by Aroclor1260. PCB126 decreased hepatic inflammation and fibrosis at the molecular level; while altering cytoskeletal remodeling, metal homeostasis, and intermediary/xenobiotic metabolism. PCB126 attenuated Aroclor1260-induced hepatic inflammation but increased hepatic free fatty acids in the co-exposure group. Aroclor1260 + PCB126 exposure was strongly associated with multiple epigenetic processes, and these could potentially explain the observed nonadditive effects of the exposures on the hepatic proteome. Taken together, the results demonstrated that PCB exposures differentially regulated the hepatic proteome and the histologic severity of diet-induced NAFLD. Future research is warranted to determine the AhR-dependence of the observed effects including metal homeostasis and the epigenetic regulation of gene expression.