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Gait variability of healthy adults exhibits Long-Range Autocorrelations (LRA), meaning that the stride interval at any time statistically depends on previous gait cycles; and this dependency spans over several hundreds of strides. Previous works have shown that this property is altered in patients with Parkinson’s disease, such that their gait pattern corresponds to a more random process. Here, we adapted a model of gait control to interpret the reduction in LRA that characterized patients in a computational framework. Gait regulation was modeled as a Linear-Quadratic-Gaussian control problem where the objective was to maintain a fixed velocity through the coordinated regulation of stride duration and length. This objective offers a degree of redundancy in the way the controller can maintain a given velocity, resulting in the emergence of LRA. In this framework, the model suggested that patients exploited less the task redundancy, likely to compensate for an increased stride-to-stride variability. Furthermore, we used this model to predict the potential benefit of an active orthosis on the gait pattern of patients. The orthosis was embedded in the model as a low-pass filter on the series of stride parameters. We show in simulations that, with a suitable level of assistance, the orthosis could help patients recovering a gait pattern with LRA comparable to that of healthy controls. Assuming that the presence of LRA in a stride series is a marker of healthy gait control, our study provides a rationale for developing gait assistance technology to reduce the fall risk associated with Parkinson’s disease.

Target reward influences motor planning strategies through modulation of movement vigor. Considering current theories of sensorimotor control suggesting that movement planning consists in selecting a goal-directed control strategy, we sought to investigate the influence of reward on feedback control. Here, we explored this question in three human reaching experiments. First, we altered the explicit reward associated with the goal target and found an overall increase in feedback gains for higher target rewards, highlighted by larger velocities, feedback responses to external loads, and background muscle activity. Then, we investigated whether the differences in target rewards across multiple goals impacted rapid motor decisions during movement. We observed idiosyncratic switching strategies dependent on both target rewards and, surprisingly, the feedback gains at perturbation onset: the more vigorous movements were less likely to switch to a new goal following perturbations. To gain further insight into a causal influence of the feedback gains on rapid motor decisions, we demonstrated that biasing the baseline activity and reflex gains by means of a background load evoked a larger proportion of target switches in the direction opposite to the background load associated with lower muscle activity. Together, our results demonstrate an impact of target reward on feedback control and highlight the competition between movement vigor and flexibility.

Savings have been described as the ability of healthy humans to relearn a previously acquired motor skill faster than the first time, which in the context of motor adaptation suggests that the learning rate in the brain could be adjusted when a perturbation is recognized. Alternatively, it has been argued that apparent savings were the consequence of a distinct process that instead of reflecting a change in the learning rate, revealed an explicit re-aiming strategy. Based on recent evidence that feedback adaptation may be central to both planning and control, we hypothesized that this component could genuinely accelerate relearning in human adaptation to force fields during reaching. Consistent with our hypothesis, we observed that upon re-exposure to a previously learned force field, the very first movement performed by healthy volunteers in the relearning context was better adapted to the external disturbance, and this occurred without any anticipation or cognitive strategy because the relearning session was started unexpectedly. We conclude that feedback adaptation is a medium by which the nervous system can genuinely accelerate learning across movements.Significance StatementSavings describe the ability of healthy humans to faster relearn a previously acquired motor skill. It is debated whether savings result from implicit changes in the learning rate or an explicit strategy. Given recent evidence that feedback control plays a key role in movement adaptation, we hypothesized that this component also contributed to savings in the context of force field adaptation. We confirm that relearning was faster and demonstrate that the very first relearning movement was better adapted to the external disturbance, i.e., the online corrections in the first re-exposure trial carried imprints of feedback adaptation from the previous sessions in the absence of any explicit strategy. We conclude that this non-explicit feedback component can genuinely accelerate motor learning.

Humans and other animals adapt motor commands to predictable disturbances within tens of trials in laboratory conditions. A central question is how does the nervous system adapt to disturbances in natural conditions when exactly the same movements cannot be practiced several times. Because motor commands and sensory feedback together carry continuous information about limb dynamics, we hypothesized that the nervous system could adapt to unexpected disturbances online., Humans and other animals adapt motor commands to predictable disturbances within tens of trials in laboratory conditions. A central question is how does the nervous system adapt to disturbances in natural conditions when exactly the same movements cannot be practiced several times. Because motor commands and sensory feedback together carry continuous information about limb dynamics, we hypothesized that the nervous system could adapt to unexpected disturbances online. We tested this hypothesis in two reaching experiments during which velocity-dependent force fields (FFs) were randomly applied. We found that within-movement feedback corrections gradually improved, despite the fact that the perturbations were unexpected. Moreover, when participants were instructed to stop at a via-point, the application of a FF prior to the via-point induced mirror-image after-effects after the via-point, consistent with within-trial adaptation to the unexpected dynamics. These findings suggest a fast time-scale of motor learning, which complements feedback control and supports adaptation of an ongoing movement.

Feedback delays are a major challenge for any controlled process, and yet we are able to easily control limb movements with speed and grace. A popular hypothesis suggests that the brain largely mitigates the impact of feedback delays (∼50 ms) by regulating the limb intrinsic visco-elastic properties (or impedance) with muscle co-contraction, which generates forces proportional to changes in joint angle and velocity with zero delay. Although attractive, this hypothesis is often based on estimates of limb impedance that include neural feedback, and therefore describe the entire motor system. In addition, this approach does not systematically take into account that muscles exhibit high intrinsic impedance only for small perturbations (short-range impedance). As a consequence, it remains unclear how the nervous system handles large perturbations, as well as disturbances encountered during movement when short-range impedance cannot contribute. We address this issue by comparing feedback responses to load pulses applied to the elbow of human subjects with theoretical simulations. After validating the model parameters, we show that the ability of humans to generate fast and accurate corrective movements is compatible with a control strategy based on state estimation. We also highlight the merits of delay-uncompensated robust control, which can mitigate the impact of internal model errors, but at the cost of slowing feedback corrections. We speculate that the puzzling observation of presynaptic inhibition of peripheral afferents in the spinal cord at movement onset helps to counter the destabilizing transition from high muscle impedance during posture to low muscle impedance during movement., Author Summary Recent studies have investigated how the brain generates purposeful feedback responses to perturbations during motor control. One hypothesis suggests that the brain exploits the spring-like properties of muscles to counter perturbations. However, muscles exhibit high mechanical impedance only against small perturbations during posture, which questions the general contribution of intrinsic muscle impedance for feedback control. Alternatively, the brain may directly map sensory data into motor commands without compensating for sensorimotor delays, which is known to limit control performance. A third hypothesis suggests that neural activity following an external disturbance estimates the current state of the limb to generate a motor response. We used a perturbation paradigm where healthy participants were instructed to respond to perturbations within an extremely short time window. Comparing participants' performances with a model considering intrinsic joint impedance and conduction delays revealed that the case of state estimation was the best candidate control model to explain very fast corrective response of humans. This study emphasizes that model-based control can generate human-like rapid and stable feedback responses given low muscle stiffness and sensorimotor delays.

Recent theories of voluntary control predict that multiple motor strategies can be precomputed and expressed throughout movement. We examined online decisional processing in humans by asking them to make reaching movements with obstacles located just to the sides of a direct path between start and end targets. On random trials, the limb was perturbed with one of four mechanical loads that varied in direction and amplitude. Notably, we observed two different strategies when we applied a perturbation (left medium-sized) that deviated the participants' hand directly toward an obstacle. In some trials, subjects directed their hand between the obstacles and in other trials to the left of the obstacles. Importantly, changes in the muscle stretch response between these two strategies were observed in

Stride duration variability is considered a marker of gait balance and can be investigated in at least two different ways. Fluctuation magnitude can be addressed by classical mathematical methods, whereas fluctuation dynamics between strides can be characterized using the autocorrelation function. Although each approach has revealed changes of these parameters in different age-groups, most studies have focused on spontaneous walking speeds, which vary across groups and is described as a possible confounder in the assessment of stride duration variability. In the present study, the influence of speed on stride duration fluctuations was first analyzed in six young adults walking at six different speeds on a treadmill. Second, the results of 18 subjects from three different age-groups (≈5, 25, and 75 years old) were compared to assess the effect of age on the same variables at three different speeds. Fluctuation dynamics was evaluated, thanks to combined mathematical methods recently validated in the context of physiological time series, to increase the level of confidence in the results. Fluctuation magnitude was assessed by coefficients of variation (CV) on the same and large number of 512 gait strides, to enhance the validity of comparisons between both parameters. Long-range autocorrelations were highlighted in all time series, and characteristics were not influenced by gait speed and age of the participants. This suggests that the dynamics of variability is efficient for comparing subjects presenting with different spontaneous speed, and supports the hypothesis that long-range variability of human gait reflects a centrally controlled behavior. In contrast, CV was inversely related to walking speed and the age of the subjects. Slower speeds increased CV values, and fluctuation magnitude was also significantly larger for children compared with young and old adults. This confirms that fluctuation magnitude and dynamics could be complementary tools for more complete gait characterization.

A wealth of studies highlight the importance of rapid corrective responses during voluntary motor tasks. These studies used relatively large perturbations to evoke robust muscle activity. Thus it remains unknown whether these corrective responses (latency 20–100 ms) are evoked at perturbation levels approaching the inherent variability of voluntary control. To fill this gap, we examined responses for large to small perturbations applied while participants either performed postural or reaching tasks. To address multijoint corrective responses, we induced various amounts of single-joint elbow motion with scaled amounts of combined elbow and shoulder torques. Indeed, such perturbations are known to elicit a response at the unstretched shoulder muscle, which reflects an internal model of arm intersegmental dynamics. Significant muscle responses were observed during both postural control and reaching, even when perturbation-related joint angle, velocity, and acceleration overlapped in distribution with deviations encountered in unperturbed trials. The response onsets were consistent across the explored range of perturbation loads, with short-latency onset for the muscles spanning the elbow joints (20–40 ms), and long-latency for shoulder muscles (onset > 45 ms). In addition, the evoked activity was strongly modulated by perturbation magnitude. These results suggest that multijoint responses are not specifically engaged to counter motor errors that exceed a certain threshold. Instead, we suggest that these corrective processes operate continuously during voluntary motor control.

ObjectivesFalls remain a major concern in Parkinson disease (PD). However, no precocious marker of fall risk has been highlighted. Recently, complex temporal organization of stride duration variability has been demonstrated, displaying long-range autocorrelations (LRA). The breakdown of such temporal dynamics is thought to be associated to dynamic instability in locomotion. However, no studies have included the analysis of stride duration variability in the functional assessment of patients presenting a neurological disease, such as PD.Materials and methodsTemporal organization (LRA) and magnitude (CV and SD) of stride duration variability, collected from 20 parkinsonian patients walking on overground at a comfortable speed, were studied. The presence of LRA was based on scaling properties of the series variability (Hurst exponent) and the shape of the power spectral density (α exponent). Functional status, objective and subjective measures of balance were collected using MDS-UPDRS (and PIGD), modified H&Y scale, BESTest and ABC Scale, respectively. In order to precise the relationship between stride duration variability and the dynamic stability, a principal component analysis was applied.ResultsLRA were highlighted in all patients and excellent correlations were observed between LRA (factor loading: Hurst=0,907; α=0,931), H&Y scale (−0,914), BESTest score (0,867) and PIGD (−0,741), while no significant correlations were observed with age and gait speed. CV and SD stride duration were inversely correlated with ABC Scale.DiscussionSupporting firmly the relationship with dynamic stability, strong correlations between LRA, disease severity and balance status were demonstrated for the first time in PD. Taken together with clinical tests, magnitude and organization of variability allow a more comprehensive description of specific deficits increasing fall risk than either method could provide alone. While magnitude of variability could be a marker of the degree of automaticity of gait, LRA could be considered as the reflection of dynamic stability. The quantification of stride duration variability can thus constitute an easy and effective tool to objectively and quantitatively provide a clinical measure of fall risk in PD.

Objectives Unstructured gait variability is a hallmark of timing gait disorders of Parkinson's disease (PD). Recently, complex temporal structure of stride duration variability has been demonstrated in healthy gait pattern, displaying long-range autocorrelations (LRA). Conversely, the breakdown of such temporal organization was associated to dynamic instability in PD. To improve timing gait in PD, synchronization of walking with rhythmic auditory stimulation (RAS) like music or metronome is largely used in clinical settings. However, while structure of RAS can modulate LRA in healthy gait pattern, it remains unknown in PD. Materials and method Patients performed overground walking trials at a comfortable speed while listening different structures of RAS (counterbalanced order across patients). Each structure was adapted to the gait cadence of each patient as previously measured in a 10-meter walking test. The RAS varied in term of fluctuation of the metronome period in the sound sequence, yielding four conditions: strictly metronomic, randomly fluctuating around the metronome period, fluctuating according to an LRA structure (Hurst exponent = 0.80) and no auditory stimulus. Cadence, speed, stride length, temporal organization (LRA) and magnitude of stride duration variability were measured on 512 consecutive gait cycles. The presence of LRA was based on scaling properties of the series variability (Hurst exponent) and the shape of the power spectral density (α exponent). Those measures were compared across the four conditions using a one-way repeated ANOVA. Results/Discussion Our results show that temporal organization of PD gait may be modulated using different auditory structures. Spearman's coefficients indicate adequate correlations between LRA of gait and auditory cue. This matching indicates strong adaptation and synchronization of the gait to the RAS in those patients. However, LRA were systematically lower during auditory conditions compared to spontaneous walking session. Furthermore, magnitude of stride duration variability, walking cadence, walking speed, stride length were not statistically different across different conditions. Consequently, strictly metronomic auditory stimuli do not seem to be an optimal way to improve timing gait in PD, as it induces the disappearance of LRA. Future work will investigate whether structured auditory stimuli induce gait improvement in PD.