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Summary: Human gait is a complex behavior requiring dynamic control of upper and lower extremities that is accompanied by cortical activity in multiple brain areas. We investigated the contribution of beta (15–30 Hz) and gamma (30–50 Hz) band electroencephalography (EEG) activity during specific phases of the gait cycle, comparing treadmill walking with and without arm swing. Modulations of spectral power in the beta band during early double support and swing phases source-localized to the sensorimotor cortex ipsilateral, but not contralateral, to the leading leg. The lateralization disappeared in the condition with constrained arms, together with an increase of activity in bilateral supplementary motor areas. By contrast, gamma band modulations that localized to the presumed leg area of sensorimotor cortex around the heel-strike events were unaffected by arm movement. Our findings demonstrate that arm swing is accompanied by considerable cortical activation that should not be neglected in gait-related neuroimaging studies.

Abstract Background Endovascular stroke treatment (EST) has become the standard treatment for patients with stroke due to large vessel occlusion, especially in earlier time windows. Only few data from population-based registries on effectiveness of EST have been published. Methods Baden–Wuerttemberg is the third largest state in Germany in terms of area and population and has a structured stroke concept since 1998 which includes mandatory collection of quality assurance data. In 2018 and 2019, 3820 of 39,168 ischemic stroke patients (9.8%) were treated by EST (age median 78 y, NIHSS median 14). We analyzed the clinical outcome of these patients determined with the modified Rankin Scale (mRS) at discharge from the hospital or with the initiation of palliative therapy using logistic regression analysis with adjustment for the mRS at admission, additive IVT, age, and NIHSS. Results The probability of an excellent clinical outcome (mRS 0 or 1 at discharge) and for a good clinical outcome (mRS 0–2) were significantly higher in EST-patients (odds-ratio (OR) 1.27; 95% confidence interval (95% CI) 1.13–1.43, and OR of 1.15 (95% CI 1.04–1.28). Also, the regression model showed an advantage for EST-patients with less frequent ‘decision for palliative care’ (OR 0.87; 95% CI 0.78–0.98). Sensitivity analysis adjusting for intracranial vessel occlusion as further factor showed similar results. Conclusion Our data suggest that EST can be of benefit also for an area-wide unselected stroke population, in a large German federal state with sometimes long distance to the next thrombectomy center.

Abstract Background About 80% of all stroke survivors have an upper limb paresis immediately after stroke, only about a third of whom (30 to 40%) regain some dexterity within six months following conventional treatment programs. Of late, however, two recently developed interventions - constraint-induced movement therapy (CIMT) and bilateral arm training with rhythmic auditory cueing (BATRAC) - have shown promising results in the treatment of upper limb paresis in chronic stroke patients. The ULTRA-stroke (acronym for Upper Limb TRaining After stroke) program was conceived to assess the effectiveness of these interventions in subacute stroke patients and to examine how the observed changes in sensori-motor functioning relate to changes in stroke recovery mechanisms associated with peripheral stiffness, interlimb interactions, and cortical inter- and intrahemispheric networks. The present paper describes the design of this single-blinded randomized clinical trial (RCT), which has recently started and will take several years to complete. Methods/Design Sixty patients with a first ever stroke will be recruited. Patients will be stratified in terms of their remaining motor ability at the distal part of the arm (i.e., wrist and finger movements) and randomized over three intervention groups receiving modified CIMT, modified BATRAC, or an equally intensive (i.e., dose-matched) conventional treatment program for 6 weeks. Primary outcome variable is the score on the Action Research Arm test (ARAT), which will be assessed before, directly after, and 6 weeks after the intervention. During those test sessions all patients will also undergo measurements aimed at investigating the associated recovery mechanisms using haptic robots and magneto-encephalography (MEG). Discussion ULTRA-stroke is a 3-year translational research program which aims (1) to assess the relative effectiveness of the three interventions, on a group level but also as a function of patient characteristics, and (2) to delineate the functional and neurophysiological changes that are induced by those interventions. The outcome on the ARAT together with information about changes in the associated mechanisms will provide a better understanding of how specific therapies influence neurobiological changes, and which post-stroke conditions lend themselves to specific treatments. Trial Registration The ULTRA-stroke program is registered at the Netherlands Trial Register (NTR, http://www.trialregister.nl, number NTR1665).

The representation of upper limb muscles in the motor cortex is not clear-cut. The motor cortex contains areas that, when stimulated, may activate different muscles simultaneously, hence they seem to overlap. We expected the cortical representations of synergistic muscle pairs to overlap more than those of non-synergistic muscles. To test this, we used navigated transcranial magnetic stimulation to probe eight hand and forearm muscles of twenty healthy participants. We transformed the cortical representations of muscles to a template MRI to allow for group analysis. We found that the amount of overlap in cortical representations differed significantly between within-hand and within-forearm muscle combinations. Most synergistic muscle pairs, both within the hand, within the forearm and between them, had a larger overlap than non-synergistic muscle pairs. Our study demonstrates the largely overlapping nature of cortical representations of upper limb muscles. It is noteworthy that the overlap is elevated in muscles that usually act in a synergistic manner.

Understanding the mechanisms humans use to stabilize walking is vital for predicting falls in elderly. Modeling studies identified two potential mechanisms to stabilize gait in the anterior-posterior direction: foot placement control and ankle push-off control: foot placement depends on position and velocity of the center-of-mass (CoM) and push-off covaries with deviations between actual and predicted CoM trajectories. While both control mechanisms have been reported in humans, it is unknown whether especially the latter one is employed in unperturbed steady-state walking. Based on the finding of Wang and Srinivasan that foot placement deviates in the same direction as the CoM states in the preceding swing phase, and assuming that this covariance serves the role of stabilizing gait, the covariance between the CoM states and foot placement can be seen as a measure of foot placement accuracy. We subsequently interpreted the residual variance in foot placement from a linear regression model as “errors” that must be compensated, and investigated whether these foot placement errors were correlated to push-off kinetic time series of the subsequent double stance phase. We found ankle push-off torque to be correlated to the foot placement errors in 30 participants when walking at normal and slow speeds, with peak correlations over the double stance phase up to 0.39. Our study suggests that humans use a push-off strategy for correcting foot placement errors in steady-state walking.

IntroductionChildren start to run after they master walking. How running develops, however, is largely unknown.MethodsWe assessed the maturity of running pattern in two very young, typically developing children in a longitudinal design spanning about three years. Leg and trunk 3D kinematics and electromyography collected in six recording sessions, with more than a hundred strides each, entered our analysis. We recorded walking during the first session (the session of the first independent steps of the two toddlers at the age of 11.9 and 10.6 months) and fast walking or running for the subsequent sessions. More than 100 kinematic and neuromuscular parameters were determined for each session and stride. The equivalent data of five young adults served to define mature running. After dimensionality reduction using principal component analysis, hierarchical cluster analysis based on the average pairwise correlation distance to the adult running cluster served as a measure for maturity of the running pattern.ResultsBoth children developed running. Yet, in one of them the running pattern did not reach maturity whereas in the other it did. As expected, mature running appeared in later sessions (>13 months after the onset of independent walking). Interestingly, mature running alternated with episodes of immature running within sessions. Our clustering approach separated them.DiscussionAn additional analysis of the accompanying muscle synergies revealed that the participant who did not reach mature running had more differences in muscle contraction when compared to adults than the other. One may speculate that this difference in muscle activity may have caused the difference in running pattern.

In human walking, power for propulsion is generated primarily via ankle and hip muscles. The addition of a ‘passive’ hip spring to simple bipedal models appears more efficient than using only push-off impulse, at least, when hip spring associated energetic costs are not considered. Hip flexion and retraction torques, however, are not ‘free’, as they are produced by muscles demanding metabolic energy. Studies evaluating the inclusion of hip actuation costs, especially during the swing phase, and the hip actuation’s energetic benefits are few and far between. It is also unknown whether these possible benefits/effects may depend on speed. We simulated a planar flat-feet model walking stably over a range of speeds. We asked whether the addition of independent hip flexion and retraction remains energetically beneficial when considering work-based metabolic cost of transport (MCOT) with different efficiencies of doing positive and negative work. We found asymmetric hip actuation can reduce the estimated MCOT relative to ankle actuation by up to 6%, but only at medium speeds. The corresponding optimal strategy is zero hip flexion and some hip retraction actuation. The reason for this reduced MCOT is that the decrease in collision loss is larger than the associated increase in hip negative work. This leads to a reduction in total positive mechanical work, which results in an overall lower MCOT. Our study shows how ankle actuation, hip flexion, and retraction actuation can be coordinated to reduce MCOT.

Abstract During steady-state walking, mediolateral gait stability can be maintained by controlling the center of pressure (CoP). The CoP modulates the moment of the ground reaction force, which brakes and reverses movement of the center of mass (CoM) towards the lateral border of the base of support. In addition to foot placement, ankle moments serve to control the CoP. We hypothesized that, during steady-state walking, single stance ankle moments establish a CoP shift to correct for errors in foot placement. We expected ankle muscle activity to be associated with this complementary CoP shift. During treadmill walking, full-body kinematics, ground reaction forces and electromyography were recorded in thirty healthy participants. We found a negative relationship between preceding foot placement error and CoP displacement during single stance; steps that were too medial were compensated for by a lateral CoP shift and vice versa, steps that were too lateral were compensated for by a medial CoP shift. Peroneus longus, soleus and tibialis anterior activity correlated with these CoP shifts. As such, we identified an (active) ankle strategy during steady-state walking. As expected, absolute explained CoP variance by foot placement error decreased when walking with shoes constraining ankle moments. Yet, contrary to our expectations that ankle moment control would compensate for constrained foot placement, the absolute explained CoP variance by foot placement error did not increase when foot placement was constrained. We argue that this lack of compensation reflects the interdependent nature of ankle moment and foot placement control. We suggest that single stance ankle moments do not only compensate for preceding foot placement errors, but also assist control of the subsequent foot placement. Foot placement and ankle moment control are ‘caught’ in a circular relationship, in which constraints imposed on one will also influence the other.

Accelerometers are low-cost measurement devices that can readily be used outside the lab. However, determining isolated gait events from accelerometer signals, especially foot-off events during running, is an open problem. We outline a two-step approach where machine learning serves to predict vertical ground reaction forces from accelerometer signals, followed by force-based event detection. We collected shank accelerometer signals and ground reaction forces from 21 adults during comfortable walking and running on an instrumented treadmill. We trained one common reservoir computer using segmented data using both walking and running data. Despite being trained on just a small number of strides, this reservoir computer predicted vertical ground reaction forces in continuous gait with high quality. The subsequent foot contact and foot off event detection proved highly accurate when compared to the gold standard based on co-registered ground reaction forces. Our proof-of-concept illustrates the capacity of combining accelerometry with machine learning for detecting isolated gait events irrespective of mode of locomotion.

Summary: The neural locomotor system strongly relies on spinal circuitries. Yet, the control of bipedal gait is accompanied by activity in motor cortex. In human gait control, the functional interaction between these cortical contributions and their spinal counterparts are largely elusive. We focused on four spinal activation patterns during walking and explored their cortical signatures in toddlers and adults. In both groups, cortico-spinal coherence analysis revealed activity in primary motor cortex to be closely related to two of the four spinal patterns. Their corresponding muscle synergies are known to develop around the onset of independent walking. By hypothesis, the cortex hence contributes to the emergence of these synergies. In contrast, the other two spinal patterns investigated here resembled those present during newborn stepping. As expected, they did not show any cortical involvement. Together, our findings suggest a crucial role of motor cortex for independent walking in humans.

The representation of muscles in the cortex can be mapped using navigated transcranial magnetic stimulation. The commonly employed measure to quantify the mapping are the center of gravity or the centroid of the region of excitability as well as its size. Determining these measures typically relies only on stimulation points that yield motor-evoked potentials (MEPs); stimulations that do not elicit an MEP, i.e., non-MEP points, are ignored entirely. In this study, we show how incorporating non-MEP points may affect the estimates of the size and centroid of the excitable area in eight hand and forearm muscles after mono-phasic single-pulse TMS. We performed test-retest assessments in twenty participants and estimated the reliability of centroids and sizes of the corresponding areas using inter-class correlation coefficients. For most muscles, the reliability turned out good. As expected, removing the non-MEP points significantly decreased area sizes and area weights, suggesting that conventional approaches that do not account for non-MEP points are likely to overestimate the regions of excitability.

Implications of structural connections within and between brain regions for their functional counterpart are timely points of discussion. White matter microstructural organization and functional activity can be assessed in unison. At first glance, however, the corresponding findings appear variable, both in the healthy brain and in numerous neuro-pathologies. To identify consistent associations between structural and functional connectivity and possible impacts for the clinic, we reviewed the literature of combined recordings of electro-encephalography (EEG) and diffusion-based magnetic resonance imaging (MRI). It appears that the strength of event-related EEG activity increases with increased integrity of structural connectivity, while latency drops. This agrees with a simple mechanistic perspective: the nature of microstructural white matter influences the transfer of activity. The EEG, however, is often assessed for its spectral content. Spectral power shows associations with structural connectivity that can be negative or positive often dependent on the frequencies under study. Functional connectivity shows even more variations, which are difficult to rank. This might be caused by the diversity of paradigms being investigated, from sleep and resting state to cognitive and motor tasks, from healthy participants to patients. More challenging, though, is the potential dependency of findings on the kind of analysis applied. While this does not diminish the principal capacity of EEG and diffusion-based MRI co-registration, it highlights the urgency to standardize especially EEG analysis.

The first years of life might be critical for encouraging independent walking in children with cerebral palsy (CP). We sought to identify mechanisms that may underlie the impaired development of walking in three young children with early brain lesions, at high risk of CP, via comprehensive instrumented longitudinal assessments of locomotor patterns and muscle activation during walking. We followed three children (P1–P3) with early brain lesions, at high risk of CP, during five consecutive gait analysis sessions covering a period of 1 to 2 years, starting before the onset of independent walking, and including the session during the first independent steps. In the course of the study, P1 did not develop CP, P2 was diagnosed with unilateral and P3 with bilateral CP. We monitored the early development of locomotor patterns over time via spatiotemporal gait parameters, intersegmental coordination (estimated via principal component analysis), electromyography activity, and muscle synergies (determined from 11 bilateral muscles via nonnegative matrix factorization). P1 and P2 started to walk independently at the corrected age of 14 and 22 months, respectively. In both of them, spatiotemporal gait parameters, intersegmental coordination, muscle activation patterns, and muscle synergy structure changed from supported to independent walking, although to a lesser extent when unilateral CP was diagnosed (P2), especially for the most affected leg. The child with bilateral CP (P3) did not develop independent walking, and all the parameters did not change over time. Our exploratory longitudinal study revealed differences in maturation of locomotor patterns between children with divergent developmental trajectories. We succeeded in identifying mechanisms that may underlie impaired walking development in very young children at high risk of CP. When verified in larger sample sizes, our approach may be considered a means to improve prognosis and to pinpoint possible targets for early intervention.

Muscle synergies reflect the presence of a common neural input to multiple muscles. Steering small sets of synergies is commonly believed to simplify the control of complex motor tasks like walking and running. When these locomotor patterns emerge, it is likely that synergies emerge as well. We hence hypothesized that in children learning to run the number of accompanying synergies increases and that some of the synergies’ activities display a temporal shift related to a reduced stance phase as observed in adults. We investigated the development of locomotion in 23 children aged 2–9 years of age and compared them with seven young adults. Muscle activity of 15 bilateral leg, trunk, and arm muscles, ground reaction forces, and kinematics were recorded during comfortable treadmill walking and running, followed by a muscle synergy analysis. We found that toddlers (2–3.5 years) and preschoolers (3.5–6.5 years) utilize a “walk-run strategy” when learning to run: they managed the fastest speeds on the treadmill by combining double support (DS) and flight phases (FPs). In particular the activity duration of the medial gastrocnemius muscle was weakly correlated with age. The number of synergies across groups and conditions needed to cover sufficient data variation ranged between four and eight. The number of synergies tended to be smaller in toddlers than it did in preschoolers and school-age children but the adults had the lowest number for both conditions. Against our expectations, the age groups did not differ significantly in the timing or duration of synergies. We believe that the increase in the number of muscle synergies in older children relates to motor learning and exploration. The ability to run with a FP is clearly associated with an increase in the number of muscle synergies.

Identification of individuals at risk of falling is important when designing fall prevention methods. Current measures that estimate gait stability and robustness appear limited in predicting falls in older adults. Inspired by recent findings on changes in phase-dependent local stability within a gait cycle, we devised several phase-dependent stability measures and tested for their usefulness to predict gait robustness in compass walker models. These measures are closely related to the often-employed maximum finite-time Lyapunov exponent and maximum Floquet multiplier that both assess a system's response to infinitesimal perturbations. As such, they entail linearizing the system, but this is realized in a rotating hypersurface orthogonal to the period-one solution followed by estimating the trajectory-normal divergence rate of the swing phases and the foot strikes. We correlated the measures with gait robustness, i.e. the largest perturbation a walker can handle, in two compass walker models with either point or circular feet to estimate their prediction accuracy. To also test for the dependence of the measures under state space transform, we represented the point feet walker in both Euler–Lagrange and Hamiltonian canonical form. Our simulations revealed that for most of the measures their correlation with gait robustness differs between models and between different state space forms. In particular, the latter may jeopardize many stability measures' predictive capacity for gait robustness. The only exception that consistently displayed strong correlations is the divergence of foot strike. Our results admit challenges of using phase-dependent stability measures as objective means to estimate the risk of falling.