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Abstract Inspired by animals that co-adapt their brain and body to interact with the environment, we present a tendon-driven and over-actuated (i.e.njoint,n+1 actuators) bipedal robot that (i) exploits its backdrivable mechanical properties to manage body-environment interactions without explicit control,and(ii) uses a simple 3-layer neural network to learn to walk after only 2 min of ‘natural’ motor babbling (i.e. an exploration strategy that is compatible with leg and task dynamics; akin to childsplay). This brain–body collaboration first learns to produce feet cyclical movements ‘in air’ and, without further tuning, can produce locomotion when the biped is lowered to be in slight contact with the ground. In contrast, training with 2 min of ‘naïve’ motor babbling (i.e. an exploration strategy that ignores leg task dynamics), does not produce consistent cyclical movements ‘in air’, and produces erratic movements and no locomotion when in slight contact with the ground. When further lowering the biped and making the desired leg trajectories reach 1 cm below ground (causing the desired-vs-obtained trajectories error to be unavoidable), cyclical movements based on either natural or naïve babbling presented almost equally persistent trends, and locomotion emerged with naïve babbling. Therefore, we show how continual learning of walking in unforeseen circumstances can be driven by continual physical adaptation rooted in the backdrivable properties of the plant and enhanced by exploration strategies that exploit plant dynamics. Our studies also demonstrate that the bio-inspired co-design and co-adaptations of limbs and control strategies can produce locomotion without explicit control of trajectory errors. 

The primary motor cortex does not uniquely or directly produce alpha motoneurone (α-MN) drive to muscles during voluntary movement. Rather, α-MN drive emerges from the synthesis and competition among excitatory and inhibitory inputs from multiple descending tracts, spinal interneurons, sensory inputs, and proprioceptive afferents. One such fundamental input is velocity-dependent stretch reflexes in lengthening muscles, which should be inhibited to enable voluntary movement. It remains an open question, however, the extent to which unmodulated stretch reflexes disrupt voluntary movement, and whether and how they are inhibited in limbs with numerous multiarticular muscles. We used a computational model of a Rhesus Macaque arm to simulate movements with feedforward α-MN commands only, and with added velocity-dependent stretch reflex feedback. We found that velocity-dependent stretch reflex caused movement-specific, typically large and variable disruptions to arm movements. These disruptions were greatly reduced when modulating velocity-dependent stretch reflex feedback (i) as per the commonly proposed (but yet to be clarified) idealized alpha-gamma (α-γ) coactivation or (ii) an alternative α-MN collateral projection to homonymous γ-MNs. We conclude that such α-MN collaterals are a physiologically tenable propriospinal circuit in the mammalian fusimotor system. These collaterals could still collaborate with α-γ coactivation, and the few skeletofusimotor fibers (β-MNs) in mammals, to create a flexible fusimotor ecosystem to enable voluntary movement. By locally and automatically regulating the highly nonlinear neuro-musculo-skeletal mechanics of the limb, these collaterals could be a critical low-level enabler of learning, adaptation, and performance via higher-level brainstem, cerebellar, and cortical mechanisms. 

Quantifying the dynamical features of discrete tasks is essential to understanding athletic performance for many sports that are not repetitive or cyclical. We compared three dynamical features of the (i) bow hand, (ii) drawing hand, and (iii) center of mass during a single bow-draw movement between professional and neophyte archers: dispersion (convex hull volume of their phase portraits), persistence (tendency to continue a trend as per Hurst exponents), and regularity (sample entropy). Although differences in the two groups are expected due to their differences in skill, our results demonstrate we can quantify these differences. The center of mass of professional athletes exhibits tighter movements compared to neophyte archers (6.3 < 11.2 convex hull volume), which are nevertheless less persistent (0.82 < 0.86 Hurst exponent) and less regular (0.035 > 0.025 sample entropy). In particular, the movements of the bow hand and center of mass differed more between groups in Hurst exponent analysis, and the drawing hand and center of mass were more different in sample entropy analysis. This suggests tighter neuromuscular control over the more fluid dynamics of the movement that exhibits more active corrections that are more individualized. Our work, therefore, provides proof of principle of how well-established dynamical analysis techniques can be used to quantify the nature and features of neuromuscular expertise for discrete movements in elite athletes. 

Beta-band (15–30 Hz) synchronization between the EMG signals of active limb muscles can serve as a non-invasive assay of corticospinal tract integrity. Tasks engaging a single limb often primarily utilize one corticospinal pathway, although bilateral neural circuits can participate in goal-directed actions involving multi-muscle coordination and utilization of feedback. Suboptimal utilization of such circuits after CNS injury can result in unintended mirror movements and activation of pathological synergies. Accordingly, it is important to understand how the actions of one limb (e.g., a less-affected limb after strokes) influence the opposite corticospinal pathway for the rehabilitation target. Certain unimanual actions decrease the excitability of the “unengaged” corticospinal tract, presumably to prevent mirror movement, but there is no direct way to predict the extent to which this will occur. In this study, we tested the hypothesis that task-dependent changes in beta-band drives to muscles of one hand will inversely correlate with changes in the opposite corticospinal tract excitability. Ten participants completed spring pinching tasks known to induce differential 15–30 Hz drive to muscles. During compressions, transcranial magnetic stimulation single pulses to the ipsilateral M1 were delivered to generate motor-evoked potentials in the unengaged hand. The task-induced changes in ipsilateral corticospinal excitability were inversely correlated with associated changes in EMG-EMG coherence of the task hand. These results demonstrate a novel connection between intermuscular coherence and the excitability of the “unengaged” corticospinal tract and provide a springboard for further mechanistic studies of unimanual tasks of varying difficulty and their effects on neural pathways relevant to rehabilitation. 

Multiple proprioceptive signals, like those from muscle spindles, are thought to enable robust estimates of body configuration. Yet, it remains unknown whether spindle signals suffice to discriminate limb movements. Here, a simulated 4-musculotendon, 2-joint planar limb model produced repeated cycles of five end-point trajectories in forward and reverse directions, which generated spindle Ia and II afferent signals (proprioceptors for velocity and length, respectively) from each musculotendon. We find that cross-correlation of the 8D time series of raw firing rates (four Ia, four II) cannot discriminate among most movement pairs (∼ 29% accuracy). However, projecting these signals onto their 1^stand 2^ndprincipal components greatly improves discriminability of movement pairs (82% accuracy). We conclude that high-dimensional ensembles of muscle proprioceptors can discriminate among limb movements—but only after dimensionality reduction. This may explain the pre-processing of some afferent signals before arriving at the somatosensory cortex, such as processing of cutaneous signals at the cat’s cuneate nucleus. 

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 $\ge$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 forTibialis Anterior,Peroneus Longus,Gastrocnemius Lateralis,BicepsandRectus Femoris,Vastus MedialisandLateralismuscles 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. 

Tendon transfer surgery is often used to restore hand grasp function following high median-ulnar nerve palsy. This surgery typically reroutes and sutures the tendon of the extensor carpi radialis longus (ECRL) muscle to all four flexor digitorum profundus (FDP) tendons of the hand, coupling them together. This makes it difficult to grasp irregularly shaped objects. We propose inserting a novel implantable passive device between the FDP tendons to surgically construct a differential mechanism, enabling the fingers to individually adapt to the irregular contours during grasping. These passive implants with no moving parts are fabricated from biocompatible materials. We tested the implants’ ability to create differential flexion between the index and middle fingers when actuated by a single muscle in two human cadaver hands using a computerized closed-loop control paradigm. In these cadaveric models, the implants enabled significantly more differential flexion between the index and middle fingers for a wide range of donor tendon tensions. The implants also redistributed fingertip forces between fingers. When grasping uneven objects, the difference in contact forces between fingers reduced by nearly 23% compared to the current suture-based surgery. These results suggest that self-adaptive grasp is possible in tendon transfers that drive multiple distal flexor tendons.