Complex Locomotor Research Articles

Sleep benefits perceptual but not movement-based learning of locomotor sequences

Practicing complex locomotor skills, such as those involving a step sequence engages distinct perceptual and motor mechanisms that support the recall of learning under new conditions (i.e., skill transfer). While sleep has been shown to enhance learning of sequences of fine movements (i.e., sleep-dependent consolidation), here we examined whether this benefit extends to learning of a locomotor pattern. Specifically, we tested the perceptual and motor learning of a locomotor sequence following sleep compared to wake. We hypothesized that post-practice sleep would increase locomotor sequence learning in the perceptual, but not in the motor domain. In this study, healthy young adult participants (n = 48; 18–33 years) practiced a step length sequence on a treadmill cued by visual stimuli displayed on a screen during training. Participants were then tested in a perceptual condition (backward walking with the same visual stimuli), or a motor condition (forward walking but with an inverted screen). Skill was assessed immediately, and again after a 12-h delay following overnight sleep or daytime wake (n = 12 for each interval/condition). Off-line learning improved following sleep compared to wake, but only for the perceptual condition. Our results suggest that perceptual and motor sequence learning are processed separately after locomotor training, and further points to a benefit of sleep that is rooted in the perceptual as opposed to the motor aspects of motor learning.

Cautious Gait during Navigational Tasks in People with Hemiparesis: An Observational Study.

Locomotor and balance disorders are major limitations for subjects with hemiparesis. The Timed Up and Go (TUG) test is a complex navigational task involving oriented walking and obstacle circumvention. We hypothesized that subjects with hemiparesis adopt a cautious gait during complex locomotor tasks. The primary aim was to compare spatio-temporal gait parameters, indicators of cautious gait, between the locomotor subtasks of the TUG (Go, Turn, Return) and a Straight-line walk in people with hemiparesis. Our secondary aim was to analyze the relationships between TUG performance and balance measures, compare spatio-temporal gait parameters between fallers and non-fallers, and identify the biomechanical determinants of TUG performance. Biomechanical parameters during the TUG and Straight-line walk were analyzed using a motion capture system. A repeated measures ANOVA and two stepwise ascending multiple regressions (with performance variables and biomechanical variables) were conducted. Gait speed, step length, and % single support phase (SSP) of the 29 participants were reduced during Turn compared to Go and Return and the Straight-line walk, and step width and % double support phase were increased. TUG performance was related to several balance measures. Turn performance (R2 = 63%) and Turn trajectory deviation followed by % SSP on the paretic side and the vertical center of mass velocity during Go (R2 = 71%) determined TUG performance time. People with hemiparesis adopt a cautious gait during complex navigation at the expense of performance.

Reprogrammable, Recyclable Origami Robots Controlled by Magnetic Fields

Origami, the art of paper folding, has emerged as a versatile technique for crafting intricate 3D structures from 2D sheets. Combined with the magnetic actuation, origami paper becomes the building blocks for cost‐effective, wirelessly controllable magnetic robots. Herein, a biodegradable magnetic paper with excellent formability and recyclability is developed, facilitating its convenient utilization and disposal. The programable magnetic paper, fabricated with specific magnetization and crease patterns, enables the transformation of 2D sheets into predetermined 3D structures. Leveraging the lightweight and pliable nature of paper‐based materials, exceptional control of origami robots with fast response is demonstrated, enabling a wide range of locomotion. Furthermore, the paper‐based approach enables the incorporation of electronic functionality into magnetic actuators. By introducing conductive nanoparticles into magnetic paper, an electrically conductive substance is created. Constructing electronic circuits and integrating electronic components onto the paper‐based printed circuit board platform enables the repairing of broken circuits inside complicated equipment and optical sensing of surrounding environments in conjunction with locomotive robots. The origami robots have a huge potential to be facilitated in diverse fields with various functions, demonstrating complex locomotion, and integrating chemical, optical, thermal, and mechanical sensors for monitoring environmental conditions in hard‐to‐reach locations. The array of possibilities holds significant promise for the widespread application of these origami magnetic robots across a diverse spectrum of research fields in soft robotics.

UV Light-Mediated Hydrolytic Reaction to Develop Magnetic Hydrogel Actuators with Spatially Distributed Ferriferous Oxide Microparticles.

Magnetic hydrogel actuators are developed by incorporating magnetic fillers into the hydrogel matrix. Regulating the distribution of these fillers is key to the exhibited functionalities but is still challenging. Here a facile way to spatially synthesize ferrosoferric oxide(Fe3O4) microparticles in situ in a thermal-responsive hydrogel is reported. This method involves the photo-reduction of Fe3+ ions coordinated with carboxylate groups in polymer chains, and the hydrolytic reaction of the reduced Fe2+ ions with residual Fe3+ ions. By controlling the irradiation time and position, the concentration of Fe3O4 microparticles can be spatially controlled, and the resulting Fe3O4 pattern enables the hydrogel to exhibit complex locomotion driven by magnet, temperature, and NIR light. This method is convenient and extendable to other hydrogel systems to realize more complicated magneto-responsive functionalities.

Motor patterns of patients with spinal muscular atrophy suggestive of sensory and corticospinal contributions to the development of locomotor muscle synergies.

Complex locomotor patterns are generated by combination of muscle synergies. How genetic processes, early sensorimotor experiences, and the developmental dynamics of neuronal circuits contribute to the expression of muscle synergies remains elusive. We shed light on the factors that influence development of muscle synergies by studying subjects with spinal muscular atrophy (SMA, types II/IIIa), a disorder associated with degeneration and deafferentation of motoneurons and possibly motor cortical and cerebellar abnormalities, from which the afflicted would have atypical sensorimotor histories around typical walking onset. Muscle synergies of children with SMA were identified from electromyographic signals recorded during active-assisted leg motions or walking, and compared with those of age-matched controls. We found that the earlier the SMA onset age, the more different the SMA synergies were from the normative. These alterations could not just be explained by the different degrees of uneven motoneuronal losses across muscles. The SMA-specific synergies had activations in muscles from multiple limb compartments, a finding reminiscent of the neonatal synergies of typically developing infants. Overall, while the synergies shared between SMA and control subjects may reflect components of a core modular infrastructure determined early in life, the SMA-specific synergies may be developmentally immature synergies that arise from inadequate activity-dependent interneuronal sculpting due to abnormal sensorimotor experience and other factors. Other mechanisms including SMA-induced intraspinal changes and altered cortical-spinal interactions may also contribute to synergy changes. Our interpretation highlights the roles of the sensory and descending systems to the typical and abnormal development of locomotor modules.NEW & NOTEWORTHY This is likely the first report of locomotor muscle synergies of children with spinal muscular atrophy (SMA), a subject group with atypical developmental sensorimotor experience. We found that the earlier the SMA onset age, the more the subjects' synergies deviated from those of age-matched controls. This result suggests contributions of the sensory/corticospinal activities to the typical expression of locomotor modules, and how their disruptions during a critical period of development may lead to abnormal motor modules.

Використання методики тілесно-орієнтованої терапії "м'ячики" у психологічному відновленні військовослужбовців

Background. In solving the psychological challenges of today, related to the consequences of hostilities, body-oriented methods are a number step in the direction of psychological recovery of Ukrainian military personnel. These psychotechniques not only help relieve emotional stress through physical activity, but also help restore harmony between body and soul. This deep and balanced approach supports mental resilience and adapts the military personnel to difficult situations. The article is aimed at presenting the author's method of body-oriented therapy "Balls" (V.G. Shevchenko) to the wider scientific community and its use in the psychological recovery of military personnel – participants in the russianUkrainian war. It is also important to substantiate the expediency of using this technique as one of the tools for comprehensive psychological recovery of combatants who have survived combat stress. Methods. The research used such theoretical methods as analysis, systematization and generalization of psychological data on the research problem. An analysis of scientific sources on psychological assistance to military personnel using body-oriented approaches was carried out, as well as a synthesis of this information for a better understanding of modern theoretical aspects of psychological recovery using the "Balls" technique. Results. Primarily effective – the five-level training technique "Balls" as a complex of thirteen basic exercises with constantly increasing tasks was decoded within the framework of pilot projects of medical and psychological rehabilitation of the Ministry of Defense of Ukraine (2018) on the basis of the Military Medical Clinical Center of the Southern Region in the Odesa region and the base of winter sports "Tysovets" in the Lviv region, which covered about 700 of military personnel – participants in hostilities. Conclusions. A military personnel, after participating in training using the body-oriented "Balls" method, will experience positive changes in the perception and overcoming of stress, will gain new knowledge and skills in psychological self-regulation and will improve the quality of sleep, restore psychological balance, strengthen his internal resources and improve the general well-being It has been established that, in addition to the body-oriented effect, the "Balls" technique develops both simple and complex locomotion, promotes the development of psychomotor grace and contains both preventive and therapeutic effects in overcoming the effects of stress.

Goal-Conditioned Hierarchical Reinforcement Learning With High-Level Model Approximation.

Hierarchical reinforcement learning (HRL) exhibits remarkable potential in addressing large-scale and long-horizon complex tasks. However, a fundamental challenge, which arises from the inherently entangled nature of hierarchical policies, has not been understood well, consequently compromising the training stability and exploration efficiency of HRL. In this article, we propose a novel HRL algorithm, high-level model approximation (HLMA), presenting both theoretical foundations and practical implementations. In HLMA, a Planner constructs an innovative high-level dynamic model to predict the k -step transition of the Controller in a subtask. This allows for the estimation of the evolving performance of the Controller. At low level, we leverage the initial state of each subtask, transforming absolute states into relative deviations by a designed operator as Controller input. This approach facilitates the reuse of subtask domain knowledge, enhancing data efficiency. With this designed structure, we establish the local convergence of each component within HLMA and subsequently derive regret bounds to ensure global convergence. Abundant experiments conducted on complex locomotion and navigation tasks demonstrate that HLMA surpasses other state-of-the-art single-level RL and HRL algorithms in terms of sample efficiency and asymptotic performance. In addition, thorough ablation studies validate the effectiveness of each component of HLMA.

Minimally designed thermo-magnetic dual responsive soft robots for complex applications.

The fabrication of thermo-magnetic dual-responsive soft robots often requires intricate designs to implement complex locomotion patterns and utilize the implemented responsive behaviors. This work demonstrates a minimally designed soft robot based on poly-N-isopropylacrylamide (pNIPAM) and ferromagnetic particles, showcasing excellent control over both thermo- and magnetic responses. Free radical polymerization enables the magnetic particles to be entrapped homogeneously within the polymeric network. The integration of magnetic shape programming and temperature response allows the robot to perform various tasks including shaping, locomotion, pick-and-place, and release maneuvers of objects using independent triggers. The robot can be immobilized in a gripping state through magnetic actuation, and a subsequent increase in temperature transitions the robot from a swollen to a collapsed state. The temperature switch enables the robot to maintain a secured configuration while executing other movements via magnetic actuation. This approach offers a straightforward yet effective solution for achieving full control over both stimuli in dual-responsive soft robotics.

DeepCPG Policies for Robot Locomotion

Central Pattern Generators (CPGs) form the neural basis of the observed rhythmic behaviors for locomotion in legged animals. The CPG dynamics organized into networks allow the emergence of complex locomotor behaviors. In this work, we take this inspiration for developing walking behaviors in multi-legged robots. We present novel DeepCPG policies that embed CPGs as a layer in a larger neural network and facilitate end-to-end learning of locomotion behaviors in deep reinforcement learning (DRL) setup. We demonstrate the effectiveness of this approach on physics engine-based insectoid robots. We show that, compared to traditional approaches, DeepCPG policies allow sample-efficient end-to-end learning of effective locomotion strategies even in the case of high-dimensional sensor spaces (vision). We scale the DeepCPG policies using a modular robot configuration and multi-agent DRL. Our results suggest that gradual complexification with embedded priors of these policies in a modular fashion could achieve non-trivial sensor and motor integration on a robot platform. These results also indicate the efficacy of bootstrapping more complex intelligent systems from simpler ones based on biological principles. Finally, we present the experimental results for a proof-of-concept insectoid robot system for which DeepCPG learned policies initially using the simulation engine and these were afterwards transferred to real-world robots without any additional fine-tuning.

The Morphological Transformation of the Thorax during the Eclosion of Drosophila melanogaster (Diptera: Drosophilidae).

The model organism Drosophila melanogaster, as a species of Holometabola, undergoes a series of transformations during metamorphosis. To deeply understand its development, it is crucial to study its anatomy during the key developmental stages. We describe the anatomical systems of the thorax, including the endoskeleton, musculature, nervous ganglion, and digestive system, from the late pupal stage to the adult stage, based on micro-CT and 3D visualizations. The development of the endoskeleton causes original and insertional changes in muscles. Several muscles change their shape during development in a non-uniform manner with respect to both absolute and relative size; some become longer and broader, while others shorten and become narrower. Muscular shape may vary during development. The number of muscular bundles also increases or decreases. Growing muscles are probably anchored by the tissues in the stroma. Some muscles and tendons are absent in the adult stage, possibly due to the hardened sclerites. Nearly all flight muscles are present by the third day of the pupal stage, which may be due to the presence of more myofibers with enough mitochondria to support flight power. There are sexual differences in the same developmental period. In contrast to the endodermal digestive system, the functions of most thoracic muscles change in the development from the larva to the adult in order to support more complex locomotion under the control of a more structured ventral nerve cord based on the serial homology proposed herein.

Omnidirectional propulsion in a metachronal swimmer.

Aquatic organisms often employ maneuverable and agile swimming behavior to escape from predators, find prey, or navigate through complex environments. Many of these organisms use metachronally coordinated appendages to execute complex maneuvers. However, though metachrony is used across body sizes ranging from microns to tens of centimeters, it is understudied compared to the swimming of fish, cetaceans, and other groups. In particular, metachronal coordination and control of multiple appendages for three-dimensional maneuvering is not fully understood. To explore the maneuvering capabilities of metachronal swimming, we combine 3D high-speed videography of freely swimming ctenophores (Bolinopsis vitrea) with reduced-order mathematical modeling. Experimental results show that ctenophores can quickly reorient, and perform tight turns while maintaining forward swimming speeds close to 70% of their observed maximum-performance comparable to or exceeding that of many vertebrates with more complex locomotor systems. We use a reduced-order model to investigate turning performance across a range of beat frequencies and appendage control strategies, and reveal that ctenophores are capable of near-omnidirectional turning. Based on both recorded and modeled swimming trajectories, we conclude that the ctenophore body plan enables a high degree of maneuverability and agility, and may be a useful starting point for future bioinspired aquatic vehicles.

A meshfree model of hard-magnetic soft materials

Hard-magnetic soft materials comprising a soft matrix embedded with hard-magnetic particles can exhibit large deformations under external magnetic fields, which have attracted much interest due to their non-contact activation, flexible programmability, and rapid response in various applications such as biomedical devices, soft robotics and flexible electronics. Precise predictions of large deformations of hard-magnetic soft materials would be a key for relevant applications. Given that the rational designs in the programmable shape morphing of ferromagnetic structures requires high precision, here we develop a meshfree model based on the radial point interpolation method to quantitatively predict large deformations of hard-magnetic soft materials. We apply the stabilized conforming nodal integration instead of direct nodal integration to eliminate the influence of zero-energy mode, and the central difference scheme is implemented for the resolution procedure. We explore the bending of a hard-magnetic beam and snap buckling of a bistable hard-magnetic beam under external magnetic stimuli. Uniform and non-uniform discretizations are compared to show the insensitivity of the radial point interpolation method to nodal mesh. To demonstrate the versatile programmability of our model in the design of magnetic robotics, we further simulate complex locomotion (crawling, walking and rolling) of hard-magnetic soft robots under external magnetic excitation. The results could be used to guide rational designs of ferromagnetic structures and soft continuum robots.

Automatic lameness scoring of dairy cows based on the analysis of head- and back-hoof linkage features using machine learning methods

Cow lameness is a complex locomotion behaviour, and effective characteristics are the key to identifying early lameness. Machine learning methods were used to quantify the movement of the hooves and head of cows, and they showed the possibility of using the head- and back-hoof linkage features extracted from motion analysis to classify early lameness. Firstly, the key points of the body in the side-view walking videos were tracked by DeepLabCut (DLC). Based on the curves of hoof movement and head swing, the head-hoof linkage pattern was analysed. Second, the curve of cow's back was extracted and the back-hoof linkage feature was built when the hoof touched the ground. At the same time, the movement curves were analysed to extract five other gait characteristics, including asymmetry of stride length, tracking up, asymmetry in the proportion of supporting phase, landing speed, and moving speed. Multiple models were trained on a dataset containing 212 videos, and 10-fold cross-validation was used to verify the performance of the algorithm. The classification performance was improved by optimising the model and algorithm. Overall accuracy and recall were 89.2% and 90.7%, respectively. The scores of the importance of features calculated by the Chi-square test showed that the head- and back-hoof linkage features play an important role in the classification of early lame cows. The hooves and their linkage features with the head and back of cows proposed in this paper can thus effectively detect early lameness in cows.

Philosophie der Bionik: Das Komponieren von bio-robotischen Formen

AbstractIn this paper, I explore how bio-hybrid forms can be created and combined starting from organic forms. The thesis put forward is epistemological: the combinatorial practice of bionics, biomimetics, biorobotics, and all design strategies inspired by nature is not based on a kind of biomimetic inspiration, i. e., on a kind of imitation of nature, but on a practice of translation.To develop this thesis, I focus on the practices of contemporary biorobotics, first examining the practice of translating natural forms into technical artefacts as developed by Raoul Heinrich Francé at the beginning of the 20th century, secondly, analysing the production of robots capable of replicating complex locomotion systems and, finally, investigating the interaction between robots and living organisms (fish). In the last part of the paper, I reflect on the philosophical payoff and broader conditions of possibility for this translational practice. I discuss when and to what extent a translation of biological forms into biotechnical ones is acceptable and point out the notion of form that underlies this practice. Moreover, I draw attention to the need to philosophically investigate what happens between different domains of knowledge – and especially between science and technology. This article is thus an invitation to philosophers to develop a philosophy in the interstices of knowledge production.

Cortical activation and functional connectivity during locomotion tasks in Parkinson's disease with freezing of gait.

Freezing of gait (FoG) is a severely disabling symptom in Parkinson's disease (PD). The cortical mechanisms underlying FoG during locomotion tasks have rarely been investigated. We aimed to compare the cerebral haemodynamic response during FoG-prone locomotion tasks in patients with PD and FoG (PD-FoG), patients with PD but without FoG (PD-nFoG), and healthy controls (HCs). Twelve PD-FoG patients, 10 PD-nFoG patients, and 12 HCs were included in the study. Locomotion tasks included normal stepping, normal turning and fast turning ranked as three difficulty levels based on kinematic requirements and probability of provoking FoG. During each task, we used functional near-infrared spectroscopy to capture concentration changes of oxygenated haemoglobin (ΔHBO2) and deoxygenated haemoglobin (ΔHHB) that reflected cortical activation, and recorded task performance time. The cortical regions of interest (ROIs) were prefrontal cortex (PFC), supplementary motor area (SMA), premotor cortex (PMC), and sensorimotor cortex (SMC). Intra-cortical functional connectivity during each task was estimated based on correlation of ΔHBO2 between ROIs. Two-way multivariate ANOVA with task performance time as a covariate was conducted to investigate task and group effects on cerebral haemodynamic responses of ROIs. Z statistics of z-scored connectivity between ROIs were used to determine task and group effects on functional connectivity. PD-FoG patients spent a nearly significant longer time completing locomotion tasks than PD-nFoG patients. Compared with PD-nFoG patients, they showed weaker activation (less ΔHBO2) in the PFC and PMC. Compared with HCs, they had comparable ΔHBO2 in all ROIs but more negative ΔHHB in the SMC, whereas PD-nFoG showed SMA and PMC hyperactivity but more negative ΔHHB in the SMC. With increased task difficulty, ΔHBO2 increased in each ROI except in the PFC. Regarding functional connectivity during normal stepping, PD-FoG patients showed positive and strong PFC-PMC connectivity, in contrast to the negative PFC-PMC connectivity observed in HCs. They also had greater PFC-SMC connectivity than the other groups. However, they exhibited decreased SMA-SMC connectivity when task difficulty increased and had lower SMA-PMC connectivity than HCs during fast turning. Insufficient compensatory cortical activation and depletion of functional connectivity during complex locomotion in PD-FoG patients could be potential mechanisms underlying FoG. Chinese clinical trial registry (URL: http://www.chictr.org.cn, registration number: ChiCTR2100042813).

Recent progress in soft electronics and robotics based on magnetic nanomaterials

Recent advancements in soft electronics and robotics have expanded the possibilities beyond the capabilities of traditional rigid devices, indicating promise for a range of applications in electronic skins, wireless biomedical devices, and others. Magnetic materials exploited in these soft systems can further broaden the modalities in sensing and actuation. These magnetic materials, when constructed in the forms of nanoparticles, nanomembranes, or other types of nanostructures, exhibit some unique characteristics, such as the magnetoresistance effect and size-dependent coercivity. Soft electronics and robotics employing such magnetic nanomaterials offer a variety of functions, including the detection of the intensity and direction of magnetic fields, measurement of various types of mechanical deformations, manipulation and transport at small scales, and multimodal complex locomotion in a controllable fashion. Despite recent advancements in soft electronics and robotics, challenges remain in developing advanced materials and manufacturing schemes to improve performance metrics and facilitate integration with other devices. This review article aims to summarize the progress made in soft electronics and robotics based on magnetic nanomaterials, with an emphasis on introducing material and device performance. The discussions focus on soft electronics and robotics based on magnetic nanomembranes/nanostructures and magnetic composites. As a concluding remark, this article summarizes the current status of the field and discusses opportunities that underpin future progress.

Chx10+V2a interneurons in spinal motor regulation and spinal cord injury.

Chx10-expressing V2a (Chx10+V2a) spinal interneurons play a large role in the excitatory drive of motoneurons. Chemogenetic ablation studies have demonstrated the essential nature of Chx10+V2a interneurons in the regulation of locomotor initiation, maintenance, alternation, speed, and rhythmicity. The role of Chx10+V2a interneurons in locomotion and autonomic nervous system regulation is thought to be robust, but their precise role in spinal motor regulation and spinal cord injury have not been fully explored. The present paper reviews the origin, characteristics, and functional roles of Chx10+V2a interneurons with an emphasis on their involvement in the pathogenesis of spinal cord injury. The diverse functional properties of these cells have only been substantiated by and are due in large part to their integration in a variety of diverse spinal circuits. Chx10+V2a interneurons play an integral role in conferring locomotion, which integrates various corticospinal, mechanosensory, and interneuron pathways. Moreover, accumulating evidence suggests that Chx10+V2a interneurons also play an important role in rhythmic patterning maintenance, left-right alternation of central pattern generation, and locomotor pattern generation in higher order mammals, likely conferring complex locomotion. Consequently, the latest research has focused on postinjury transplantation and noninvasive stimulation of Chx10+V2a interneurons as a therapeutic strategy, particularly in spinal cord injury. Finally, we review the latest preclinical study advances in laboratory derivation and stimulation/transplantation of these cells as a strategy for the treatment of spinal cord injury. The evidence supports that the Chx10+V2a interneurons act as a new therapeutic target for spinal cord injury. Future optimization strategies should focus on the viability, maturity, and functional integration of Chx10+V2a interneurons transplanted in spinal cord injury foci.

An Aerial-Wall Robotic Insect That Can Land, Climb, and Take Off from Vertical Surfaces.

Insects that can perform flapping-wing flight, climb on a wall, and switch smoothly between the 2 locomotion regimes provide us with excellent biomimetic models. However, very few biomimetic robots can perform complex locomotion tasks that combine the 2 abilities of climbing and flying. Here, we describe an aerial-wall amphibious robot that is self-contained for flying and climbing, and that can seamlessly move between the air and wall. It adopts a flapping/rotor hybrid power layout, which realizes not only efficient and controllable flight in the air but also attachment to, and climbing on, the vertical wall through a synergistic combination of the aerodynamic negative pressure adsorption of the rotor power and a climbing mechanism with bionic adhesion performance. On the basis of the attachment mechanism of insect foot pads, the prepared biomimetic adhesive materials of the robot can be applied to various types of wall surfaces to achieve stable climbing. The longitudinal axis layout design of the rotor dynamics and control strategy realize a unique cross-domain movement during the flying-climbing transition, which has important implications in understanding the takeoff and landing of insects. Moreover, it enables the robot to cross the air-wall boundary in 0.4 s (landing), and cross the wall-air boundary in 0.7 s (taking off). The aerial-wall amphibious robot expands the working space of traditional flying and climbing robots, which can pave the way for future robots that can perform autonomous visual monitoring, human search and rescue, and tracking tasks in complex air-wall environments.

Emergence of Distinct Neural Subspaces in Motor Cortical Dynamics during Volitional Adjustments of Ongoing Locomotion.

The ability to modulate ongoing walking gait with precise, voluntary adjustments is what allows animals to navigate complex terrains. However, how the nervous system generates the signals to precisely control the limbs while simultaneously maintaining locomotion is poorly understood. One potential strategy is to distribute the neural activity related to these two functions into distinct cortical activity coactivation subspaces so that both may be conducted simultaneously without disruptive interference. To investigate this hypothesis, we recorded the activity of primary motor cortex in male nonhuman primates during obstacle avoidance on a treadmill. We found that the same neural population was active during both basic unobstructed locomotion and volitional obstacle avoidance movements. We identified the neural modes spanning the subspace of the low-dimensional dynamics in primary motor cortex and found a subspace that consistently maintains the same cyclic activity throughout obstacle stepping, despite large changes in the movement itself. All of the variance corresponding to this large change in movement during the obstacle avoidance was confined to its own distinct subspace. Furthermore, neural decoders built for ongoing locomotion did not generalize to decoding obstacle avoidance during locomotion. Our findings suggest that separate underlying subspaces emerge during complex locomotion that coordinates ongoing locomotor-related neural dynamics with volitional gait adjustments. These findings may have important implications for the development of brain-machine interfaces.SIGNIFICANCE STATEMENT Locomotion and precise, goal-directed movements are two distinct movement modalities with known differing requirements of motor cortical input. Previous studies have characterized the cortical activity during obstacle avoidance while walking in rodents and felines, but, to date, no such studies have been completed in primates. Additionally, in any animal model, it is unknown how these two movements are represented in primary motor cortex (M1) low-dimensional dynamics when both activities are performed at the same time, such as during obstacle avoidance. We developed a novel obstacle avoidance paradigm in freely moving nonhuman primates and discovered that the rhythmic locomotion-related dynamics and the voluntary, gait-adjustment movement separate into distinct subspaces in M1 cortical activity. Our analysis of decoding generalization may also have important implications for the development of brain-machine interfaces.

Physical human locomotion prediction using manifold regularization.

Human locomotion is an imperative topic to be conversed among researchers. Predicting the human motion using multiple techniques and algorithms has always been a motivating subject matter. For this, different methods have shown the ability of recognizing simple motion patterns. However, predicting the dynamics for complex locomotion patterns is still immature. Therefore, this article proposes unique methods including the calibration-based filter algorithm and kinematic-static patterns identification for predicting those complex activities from fused signals. Different types of signals are extracted from benchmarked datasets and pre-processed using a novel calibration-based filter for inertial signals along with a Bessel filter for physiological signals. Next, sliding overlapped windows are utilized to get motion patterns defined over time. Then, polynomial probability distribution is suggested to decide the motion patterns natures. For features extraction based kinematic-static patterns, time and probability domain features are extracted over physical action dataset (PAD) and growing old together validation (GOTOV) dataset. Further, the features are optimized using quadratic discriminant analysis and orthogonal fuzzy neighborhood discriminant analysis techniques. Manifold regularization algorithms have also been applied to assess the performance of proposed prediction system. For the physical action dataset, we achieved an accuracy rate of 82.50% for patterned signals. While, the GOTOV dataset, we achieved an accuracy rate of 81.90%. As a result, the proposed system outdid when compared to the other state-of-the-art models in literature.