Biology subjects

Ijspeert, A.

Publications and source records attributed to Ijspeert, A..

11 recordsLinked to original sources

bioRxiv2026

PALAEOROBOTICS UNCOVERS DEVASTATING MAMMALIAN TAIL STRIKE DYNAMICS

Extant animals occupy only a fraction of evolutionary design space, leaving many extinct morphologies without living analogues for functional testing. We combined comparative anatomy of 32 glyptodont species with a life-sized palaeorobotic tail rig to determine strike severity in club-tailed giant from the Pleistocene megafauna Doedicurus. The robophysical model, informed by fossil geometry and inertia, matched simulated fossil-tail collision momentum (98-105%) and generated peak forces of 81.1 kN at 6.4 m{middle dot}s-{superscript 1}, with an impulse of 427 N{middle dot}s, far exceeding equine extremity fracture forces. Peak force scaled near-linearly with strike velocity, implying [~]183 kN at projected top speed of 15 m{middle dot}s-{superscript 1}. Measurements suggest Doedicurus delivered high-severity strikes, supporting antipredator defence as primary selective driver of extreme tail weaponization, and establish palaeorobotic validation of extinct animal biomechanics.

bioengineering↗

bioRxiv2024

Centralized brain networks underlie body part coordination during grooming

Animals must coordinate multiple body parts to perform important tasks such as grooming, or locomotion. How this movement synchronization is achieved by the nervous system remains largely unknown. Here, we uncover the neural basis of body part coordination during goal-directed antennal grooming in the fly, Drosophila melanogaster. We find that unilateral or bilateral grooming of one or both antenna, respectively, arises from synchronized movements of the head, antennae, and forelegs. Simulated replay of these body part kinematics in a biomechanical model shows that this coordination makes grooming more efficient by permitting unobstructed, forceful collisions between the foreleg tibiae and antennae. Movements of one body part do not require proprioceptive sensory feedback from the others: neither amputation of the forelegs or antennae, nor immobilization of the head prevented movements of the other unperturbed body parts. By constructing a comprehensive antennal grooming network from the fly brain connectome, we find that centralized interneurons and shared premotor neurons interconnect and thus likely synchronize neck, antennal, and foreleg motor networks. A simulated activation screen of neurons in this network reveals cell classes required for the coordination of antennal movements during unilateral grooming. These cells form two coupled circuit motifs that enable robust body part synchronization: a recurrent excitatory subnetwork that promotes contralateral antennal pitch and broadcast inhibition that suppresses ipsilateral antennal pitch. Similarly centralized controllers may enable the flexible co-recruitment of multiple body parts to subserve a variety of behaviors.

neuroscience↗

bioRxiv2024

Novel Neuromuscular Controllers with Simplified Muscle Model and Enhanced Reflex Modulation: A Comparative Study in Hip Exoskeletons

AO_SCPLOWBSTRACTC_SCPLOWNeuromuscular controllers (NMCs) offer a promising approach to adaptive and task-invariant control of exoskeletons for walking assistance, leveraging the bioinspired models based on the peripheral nervous system. This article expands on our previous development of a novel structure for NMCs with modifications to the virtual muscle model and reflex modulation strategy. The modifications consist firstly of simplifications to the Hill-type virtual muscle model, resulting in a more straightforward formulation and reduced number of parameters; and secondly, using a finer division of gait subphases in the reflex modulation state machine, allowing for a higher degree of control over the shape of the assistive profile. Based on the proposed general structure, we present two controller variants for hip exoskeletons, with four- and five-state reflex modulations (NMC-4 and NMC-5). We used an iterative data-driven approach with two tuning stages (i.e., muscle parameters and reflex gains) to determine the controller parameters. Biological joint torque profiles and optimal torque profiles for metabolic cost reduction were used as references for the final tuning outcome. Experimental testing under various walking conditions demonstrated the capability of both variants for adapting to the locomotion task with minimal parameter adjustments, mostly in terms of timing. Furthermore, NMC-5 exhibited better alignment with biological and optimized torque profiles in terms of timing characteristics and relative magnitudes, resulting in less negative mechanical work. These findings firstly validate the adequacy of the simplified muscle model for assistive controllers, and demonstrate the utility of a more nuanced reflex modulation in improving the assistance quality.

bioengineering↗

bioRxiv2024

Role and modulation of various spinal pathways for human upper limb control in different gravity conditions

Humans can perform movements in various physical environments and positions (corresponding to different experienced gravity), requiring the interaction of the musculoskeletal system, the neural system and the external environment. The neural system is itself comprised of several interactive components, from the brain mainly conducting motor planning, to the spinal cord (SC) implementing its own motor control centres through sensory reflexes. Nevertheless, it remains unclear whether similar movements in various environmental dynamics necessitate replanning modulation at the brain level, correcting modulation at the spinal level, or both. Here, we addressed this question by focusing on upper limb motor control in various gravity conditions (magnitudes and directions) and using neuromusculoskeletal simulation tools. We integrated supraspinal sinusoidal commands with a modular SC model controlling a musculoskeletal model to reproduce recorded elbow flexion-extension trajectories (kinematics and EMGs) in different contexts. We first studied the role of various spinal pathways (such as stretch reflexes) in movement smoothness and robustness against perturbation. Then, we optimised the supraspinal sinusoidal commands without and with a fixed SC model including stretch reflexes to reproduce a target trajectory in various gravity conditions. Inversely, we fixed the supraspinal commands and optimised the spinal synaptic strengths in the different environments. In the first optimisation context, the presence of SC resulted in easier optimisation of the supraspinal commands (faster convergence, better performance). The main supraspinal commands modulation was found in the flexor sinusoids amplitude, resp. frequency, to adapt to different gravity magnitudes, resp. directions. In the second optimisation context, the modulation of the spinal synaptic strengths also remarkably reproduced the target trajectory for the mild gravity changes. We highlighted that both strategies of modulation of the supraspinal commands or spinal stretch pathways can be used to control movements in different gravity environments. Our results thus support that the SC can assist gravity compensation.

neuroscience↗

bioRxiv2024

Asymmetric Fin Shape changes Swimming Dynamics of Ancient Marine Reptiles' Soft Robophysical Models

Animals have evolved highly effective locomotion capabilities in terrestrial, aerial, and aquatic environments. Over lifes history, mass extinctions have wiped out unique animal species with specialized adaptations, leaving paleontologists to reconstruct their locomotion through fossil analysis. Despite advancements, little is known about how extinct megafauna, such as the Ichthyosauria one of the most successful lineages of marine reptiles, utilized their varied morphologies for swimming. Traditional robotics struggle to mimic extinct locomotion effectively, but the emerging soft robotics field offers a promising alternative to overcome this challenge. This paper aims to bridge this gap by studying Mixosaurus locomotion with soft robotics, combining material modeling and biomechanics in physical experimental validation. Combining a soft body with soft pneumatic actuators, the soft robotic platform described in this study investigates the correlation between asymmetrical fins and buoyancy by recreating the pitch torque generated by extinct swimming animals. We performed a comparative analysis of thrust and torque generated by Carthorhyncus, Utatsusaurus, Mixosaurus, Guizhouichthyosaurus, and Ophthalmosaurus tail fins in a flow tank. Experimental results suggest that the pitch torque on the torso generated by hypocercal fin shapes such as found in model systems of Guizhouichthyosaurus, Mixosaurus and Utatsusaurus produce distinct ventral body pitch effects able to mitigate the animals non-neutral buoyancy. This body pitch control effect is particularly pronounced in Guizhouichthyosaurus, which results suggest would have been able to generate high ventral pitch torque on the torso to compensate for its positive buoyancy. By contrast, homocercal fin shapes may not have been conducive for such buoyancy compensation, leaving torso pitch control to pectoral fins, for example. Across the range of the actuation frequencies of the caudal fins tested, resulted in oscillatory modes arising, which in turn can affect the for-aft thrust generated.

biophysics↗

bioRxiv2023

The spinal cord facilitates cerebellar upper limb motor learning and control; inputs from neuromusculoskeletal simulation

Complex interactions between brain regions and the spinal cord (SC) govern body motion, which is ultimately driven by muscle activation. Motor planning or learning are mainly conducted at higher brain regions, whilst the SC acts as a brain-muscle gateway and as a motor control centre providing fast reflexes and muscle activity regulation. Thus, higher brain areas need to cope with the SC as an inherent and evolutionary older part of the body dynamics. Here, we address the question of how SC dynamics affects motor learning within the cerebellum; in particular, does the SC facilitate cerebellar motor learning or constitute a biological constraint? We provide an exploratory framework by integrating biologically plausible cerebellar and SC computational models in a musculoskeletal upper limb control loop. The cerebellar model, equipped with the main form of cerebellar plasticity, provides motor adaptation; whilst the SC model implements stretch reflex and reciprocal inhibition between antagonist muscles. The resulting spino-cerebellar model is tested performing a set of upper limb motor tasks, including external perturbation studies. A cerebellar model, lacking the implemented SC model and directly controlling the simulated muscles, was also tested in the same benchmark. The performances of the spino-cerebellar and cerebellar models were then compared, thus allowing directly addressing the SC influence on cerebellar motor adaptation and learning, and on handling external motor perturbations. Performance was assessed in both joint and muscle space, and compared with kinematic and EMG recordings from healthy participants. The differences in cerebellar synaptic adaptation between both models were also studied. We conclude that the SC facilitates cerebellar motor learning; when the SC circuits are in the loop, faster convergence in motor learning is achieved with simpler cerebellar synaptic weight distributions. The SC is also found to improve robustness against external perturbations, by better reproducing and modulating muscle cocontraction patterns. SummaryAccurate motor control emerges from complex interactions between different brain areas, the spinal cord (SC), and the musculoskeletal system. These different actors contribute with distributed, integrative and complementary roles yet to be fully elucidated. To further study and hypothesise about such interactions, neuromechanical modelling and computational simulation constitute powerful tools. Here, we focus on the SC influence on motor learning in the cerebellum, an issue that has drawn little attention so far; does the SC facilitate or hinder cerebellar motor learning? To address this question, we integrate biologically plausible computational models of the cerebellum and SC, equipped with motor learning capability and fast reflex responses respectively. The resulting spino-cerebellar model is used to control a simulated musculoskeletal upper limb performing a set of motor tasks involving two degrees of freedom. Moreover, we use kinematic and EMG recordings from healthy participants to validate the model performance. The SC fast control primitives operating in muscle space are shown to facilitate cerebellar motor learning, both in terms of kinematics and synaptic adaptation. This, to the best of our knowledge, is the first time to be shown. The SC also modulates muscle cocontraction, improving the robustness against external motor perturbations.

neuroscience↗

bioRxiv2023

Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model

Studying the neural components regulating movement in human locomotion is obstructed by the inability to perform invasive experimental recording. Neuromechanical simulations can provide insights by modeling the locomotor circuits. Past neuromechanical models proposed control of locomotion either driven by central pattern generators (CPGs) with simple sensory commands or by a purely reflex-based network regulated by state-machine mechanisms. However, the physiological interpretation of these state-machines remains unclear. Here, we present a physiologically plausible model to investigate spinal control and modulation of human locomotion. We propose a bio-inspired controller composed of two coupled central pattern generators (CPGs) that produce the rhythm and pattern and a reflex-based network simulating low-level reflex pathways and Renshaw cells. This reflex network is based on leaky-integration neurons, and the whole system does not rely on changing reflex gains according to the gait cycle state. The only component of the controller that maintains a state-machine mechanism is the balance controller of the trunk. The musculoskeletal model is composed of a skeletal structure and 9 muscles per leg generating movement in sagittal plane. After optimizing the open parameters, human locomotion replicating kinematics and muscle activation naturally emerged. Furthermore, when CPGs were not activated, no stable and physiologically plausible gaits could be achieved through optimization, suggesting the necessity of this component to generate rhythmic behavior without a state machine mechanism regulating reflex activation. The controller could reproduce a wide range of speeds from 0.3 to 1.9 m/s. The results also showed that the net influence of feedback on motoneurons during perturbed locomotion is predominantly inhibitory and that the CPG network provides the timing of motoneurons activation by exciting or inhibiting muscles in specific gait phases. The proposed bio-inspired controller could contribute to our understanding of locomotor circuits of the intact spinal cord and could be used to study neuromotor disorders.

neuroscience↗

bioRxiv2021

NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster

Animal behavior emerges from a seamless interaction between neural network dynamics, musculoskeletal properties, and the physical environment. Accessing and understanding the interplay between these intertwined elements requires the development of integrative and morphologically realistic neuromechanical simulations. Until now, there has been no such simulation framework for the widely studied model organism, Drosophila melanogaster. Here we present NeuroMech-Fly, a data-driven model of the adult female fly within a physics-based simulation environment. NeuroMechFly combines a series of independent computational modules including a biomechanical exoskeleton with articulating body parts-legs, halteres, wings, abdominal segments, head, proboscis, and antennae-muscle models, and neural network controllers. To enable illustrative use cases, we first define minimal leg degrees-of-freedom by analyzing real 3D kinematic measurements during real Drosophila walking and grooming. Then, we show how, by replaying these behaviors using NeuroMechFlys biomechanical exoskeleton in its physics-based simulation environment, one can predict otherwise unmeasured torques and contact reaction forces. Finally, we leverage NeuroMechFlys full neuromechanical capacity to discover neural networks and muscle parameters that enable locomotor gaits optimized for speed and stability. Thus, NeuroMechFly represents a powerful testbed for building an understanding of how behaviors emerge from interactions between complex neuromechanical systems and their physical surroundings.

neuroscience↗

bioRxiv2020

Sensory modulation of gait characteristics in human locomotion: a neuromusculoskeletal modeling study

The central nervous system of humans and animals is able to modulate the activity in the spinal cord to achieve several locomotion behaviors. Previous neuromechanical models investigated the modulation of human gait changing selected parameters belonging to the CPGs (Central Pattern Generators) feedforward oscillatory structures or to the feedback reflex circuits. CPG-based models could replicate slow and fast walking by changing only the oscillations properties. On the other hand, reflex-based models could achieve different behaviors mainly through optimizations of a large dimensional parameter space, but could not identify effectively individual key reflex parameters responsible for the modulation of gait characteristics. This study, investigates which reflex parameters modulate the gait characteristics through neuromechanical simulations. A recently developed reflex-based model is used to perform optimizations with different target behaviors on speed, step length and step duration in order to analyse the correlation between reflex parameters and their influence on these gait characteristics. We identified 9 key parameters that influence the target speed ranging from slow to fast walking (0.48 and 1.71 m/s) as well as a large range of step lengths (0.43 and 0.88 m) and step duration (0.51, 0.98 s). The findings show that specific reflexes during stance have a major effect on step length regulation mainly given by the contribution of positive force feedback on the ankle plantarflexors group. On the other hand, stretch reflexes active during swing of iliopsoas and gluteus maximus regulate all the gait characteristics under analysis. Additionally, the results show that the stretch reflex of the hamstrings group during landing phase is responsible for modulating the step length and step duration. Additional validation studies in simulations demonstrated that the identified reflexes are sufficient to modulate gait in human locomotion. Thus, this study provides an overview of the possible reflexes to control the gait characteristics. Author summary

neuroscience↗

bioRxiv2020

Experimental and computational study on motor control and recovery after stroke: towards a constructive loop betweenexperimental and virtual embodiedneuroscience

Being able to replicate real experiments with computational simulations is a unique opportunity to refine and validate models with experimental data and redesign the experiments based on simulations. However, since it is technically demanding to model all components of an experiment, traditional approaches to modeling reduce the experimental setups as much as possible. In this study, our goal is to replicate all the relevant features of an experiment on motor control and motor rehabilitation after stroke. To this aim, we propose an approach that allows continuous integration of new experimental data into a computational modeling framework. First, results show that we could reproduce experimental object displacement with high accuracy via the simulated embodiment in the virtual world by feeding a spinal cord model with experimental registration of the cortical activity. Second, by using computational models of multiple granularities, our preliminary results show the possibility of simulating several features of the brain after stroke, from the local alteration in neuronal activity to long-range connectivity remodeling. Finally, strategies are proposed to merge the two pipelines. We further suggest that additional models could be integrated into the framework thanks to the versatility of the proposed approach, thus allowing many researchers to achieve continuously improved experimental design.

neuroscience↗

bioRxiv2019

Spatiotemporal Maps of Proprioceptive Inputs to the Cervical Spinal Cord During Three-Dimensional Reaching and Grasping

Proprioceptive feedback is a critical component of voluntary movement planning and execution. Neuroprosthetic technologies aiming at restoring movement must interact with it to restore accurate motor control. Optimization and design of such technologies depends on the availability of quantitative insights into the neural dynamics of proprioceptive afferents during functional movements. However, recording proprioceptive neural activity during unconstrained movements in clinically relevant animal models presents formidable challenges. In this work, we developed a computational framework to estimate the spatiotemporal patterns of proprioceptive inputs to the cervical spinal cord during three-dimensional arm movements in monkeys. We extended a biomechanical model of the monkey arm with ex-vivo measurements, and combined it with models of mammalian group-Ia, Ib and II afferent fibers. We then used experimental recordings of arm kinematics and muscle activity of two monkeys performing a reaching and grasping task to estimate muscle stretches and forces with computational biomechanics. Finally, we projected the simulated proprioceptive firing rates onto the cervical spinal roots, thus obtaining spatiotemporal maps of spinal proprioceptive inputs during voluntary movements. Estimated maps show complex and markedly distinct patterns of neural activity for each of the fiber populations spanning the spinal cord rostro-caudally. Our results indicate that reproducing the proprioceptive information flow to the cervical spinal cord requires complex spatio-temporal modulation of each spinal root. Our model can support the design of neuroprosthetic technologies as well as in-silico investigations of the primate sensorimotor system.

bioengineering↗