skip to main content


Title: Contribution of Afferent Feedback to Adaptive Hindlimb Walking in Cats: A Neuromusculoskeletal Modeling Study
Mammalian locomotion is generated by central pattern generators (CPGs) in the spinal cord, which produce alternating flexor and extensor activities controlling the locomotor movements of each limb. Afferent feedback signals from the limbs are integrated by the CPGs to provide adaptive control of locomotion. Responses of CPG-generated neural activity to afferent feedback stimulation have been previously studied during fictive locomotion in immobilized cats. Yet, locomotion in awake, behaving animals involves dynamic interactions between central neuronal circuits, afferent feedback, musculoskeletal system, and environment. To study these complex interactions, we developed a model simulating interactions between a half-center CPG and the musculoskeletal system of a cat hindlimb. Then, we analyzed the role of afferent feedback in the locomotor adaptation from a dynamic viewpoint using the methods of dynamical systems theory and nullcline analysis. Our model reproduced limb movements during regular cat walking as well as adaptive changes of these movements when the foot steps into a hole. The model generates important insights into the mechanism for adaptive locomotion resulting from dynamic interactions between the CPG-based neural circuits, the musculoskeletal system, and the environment.  more » « less
Award ID(s):
2113069
NSF-PAR ID:
10344219
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ;
Date Published:
Journal Name:
Frontiers in Bioengineering and Biotechnology
Volume:
10
ISSN:
2296-4185
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    The absence of preserved soft tissues in the fossil record is frequently a hindrance for palaeontologists wishing to investigate morphological shifts in key skeletal systems, such as the limbs. Understanding the soft tissue composition of modern species can aid in understanding changes in musculoskeletal features through evolution, including those pertaining to locomotion. Establishing anatomical differences in soft tissues utilising an extant phylogenetic bracket can, in turn, assist in interpreting morphological changes in hard tissues and modelling musculoskeletal movements during evolutionary transitions (e.g. digit reduction in perissodactyls). Perissodactyls (horses, rhinoceroses, tapirs and their relatives) are known to have originated with a four‐toed (tetradactyl) forelimb condition. Equids proceeded to reduce all but their central digit, resulting in monodactyly, whereas tapirs retained the ancestral tetradactyl state. The modern Malayan tapir (Tapirus indicus) has been shown to exhibit fully functional tetradactyly in its forelimb, more so than any other tapir, and represents an ideal case‐study for muscular arrangement and architectural comparison with the highly derived monodactylEquus. Here, we present the first quantification of muscular architecture of a tetradactyl perissodactyl (T. indicus), and compare it to measurements from modern monodactyl caballine horse (Equus ferus caballus). Each muscle of the tapir forelimb was dissected out from a cadaver and measured for architectural properties: muscle‐tendon unit (MTU) length, MTU mass, muscle mass, pennation angle, and resting fibre length. Comparative parameters [physiological cross‐sectional area (PCSA), muscle volume, and % muscle mass] were then calculated from the raw measurements. In the shoulder region, theinfraspinatusofT. indicusexhibits dual origination sites on either side of the deflected scapular spine. Within ungulates, this condition has only been previously reported in suids. Differences in relative contribution to limb muscle mass betweenT. indicusandEquushighlight forelimb muscles that affect mobility in the lateral and medial digits (e.g.extensor digitorum lateralis). These muscles were likely reduced in equids during their evolutionary transition from tetradactyl forest‐dwellers to monodactyl, open‐habitat specialists. Patterns of PCSA across the forelimb were similar betweenT. indicusandEquus, with the notable exceptions of thebiceps brachiiandflexor carpi ulnaris, which were much larger inEquus. The differences observed in PCSA between the tapir and horse forelimb muscles highlight muscles that are essential for maintaining stability in the monodactyl limb while moving at high speeds. This quantitative dataset of muscle architecture in a functionally tetradactyl perissodactyl is a pivotal first step towards reconstructing the locomotor capabilities of extinct, four‐toed ancestors of modern perissodactyls, and providing further insights into the equid locomotor transition.

     
    more » « less
  2. When animals walk overground, mechanical stimuli activate various receptors located in muscles, joints, and skin. Afferents from these mechanoreceptors project to neuronal networks controlling locomotion in the spinal cord and brain. The dynamic interactions between the control systems at different levels of the neuraxis ensure that locomotion adjusts to its environment and meets task demands. In this article, we describe and discuss the essential contribution of somatosensory feedback to locomotion. We start with a discussion of how biomechanical properties of the body affect somatosensory feedback. We follow with the different types of mechanoreceptors and somatosensory afferents and their activity during locomotion. We then describe central projections to locomotor networks and the modulation of somatosensory feedback during locomotion and its mechanisms. We then discuss experimental approaches and animal models used to investigate the control of locomotion by somatosensory feedback before providing an overview of the different functional roles of somatosensory feedback for locomotion. Lastly, we briefly describe the role of somatosensory feedback in the recovery of locomotion after neurological injury. We highlight the fact that somatosensory feedback is an essential component of a highly integrated system for locomotor control. 
    more » « less
  3. null (Ed.)
    Locomotion is an essential behaviour for the survival of all animals. The neural circuitry underlying locomotion is therefore highly robust to a wide variety of perturbations, including injury and abrupt changes in the environment. In the short term, fault tolerance in neural networks allows locomotion to persist immediately after mild to moderate injury. In the longer term, in many invertebrates and vertebrates, neural reorganization including anatomical regeneration can restore locomotion after severe perturbations that initially caused paralysis. Despite decades of research, very little is known about the mechanisms underlying locomotor resilience at the level of the underlying neural circuits and coordination of central pattern generators (CPGs). Undulatory locomotion is an ideal behaviour for exploring principles of circuit organization, neural control and resilience of locomotion, offering a number of unique advantages including experimental accessibility and modelling tractability. In comparing three well-characterized undulatory swimmers, lampreys, larval zebrafish and Caenorhabditis elegans, we find similarities in the manifestation of locomotor resilience. To advance our understanding, we propose a comparative approach, integrating experimental and modelling studies, that will allow the field to begin identifying shared and distinct solutions for overcoming perturbations to persist in orchestrating this essential behaviour. 
    more » « less
  4. This work presents an in-depth numerical investigation into a hypothesized two-layer central pattern generator (CPG) that controls mammalian walking and how different parameter choices might affect the stepping of a simulated neuromechanical model. Particular attention is paid to the functional role of features that have not received a great deal of attention in previous work: the weak cross-excitatory connectivity within the rhythm generator and the synapse strength between the two layers. Sensitivity evaluations of deafferented CPG models and the combined neuromechanical model are performed. Locomotion frequency is increased in two different ways for both models to investigate whether the model’s stability can be predicted by trends in the CPG’s phase response curves (PRCs). Our results show that the weak cross-excitatory connection can make the CPG more sensitive to perturbations and that increasing the synaptic strength between the two layers results in a trade-off between forced phase locking and the amount of phase delay that can exist between the two layers. Additionally, although the models exhibit these differences in behavior when disconnected from the biomechanical model, these differences seem to disappear with the full neuromechanical model and result in similar behavior despite a variety of parameter combinations. This indicates that the neural variables do not have to be fixed precisely for stable walking; the biomechanical entrainment and sensory feedback may cancel out the strengths of excitatory connectivity in the neural circuit and play a critical role in shaping locomotor behavior. Our results support the importance of including biomechanical models in the development of computational neuroscience models that control mammalian locomotion. 
    more » « less
  5. Neuronal circuits in the spinal cord are essential for the control of locomotion. They integrate supraspinal commands and afferent feedback signals to produce coordinated rhythmic muscle activations necessary for stable locomotion. For several decades, computational modeling has complemented experimental studies by providing a mechanistic rationale for experimental observations and by deriving experimentally testable predictions. This symbiotic relationship between experimental and computational approaches has resulted in numerous fundamental insights. With recent advances in molecular and genetic methods, it has become possible to manipulate specific constituent elements of the spinal circuitry and relate them to locomotor behavior. This has led to computational modeling studies investigating mechanisms at the level of genetically defined neuronal populations and their interactions. We review literature on the spinal locomotor circuitry from a computational perspective. By reviewing examples leading up to and in the age of molecular genetics, we demonstrate the importance of computational modeling and its interactions with experiments. Moving forward, neuromechanical models with neuronal circuitry modeled at the level of genetically defined neuronal populations will be required to further unravel the mechanisms by which neuronal interactions lead to locomotor behavior. 
    more » « less