Modeling of the neural mechanism underlying the terrestrial turning of the salamander

Liu, Qiang; Zhang, Yongshuo; Wang, Jingzhuo; Yang, Huizhen; Hong, Lichan

doi:10.1007/s00422-020-00821-1

Cited by 10 publications

(8 citation statements)

References 34 publications

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“…The computational modelling environment in salamander research is rich at several levels of abstractions, from coupled oscillators to detailed neuron models [4,88,89]. Recently, models for the circuitry underlying locomotor and turning movements in salamanders have also been developed [90,91]. The first model of the salamander spinal cord was based on the idea that the spinal circuits generating the fast swimming movements are inherited from phylogenetically older vertebrates, such as the lamprey, whereas the slower walking movements would result from the interactions of the swimming circuit with slower circuits controlling limb movements [92].…”

Section: Salamander Robots Numerical Models and Brain-machine Intermentioning

confidence: 99%

Walking with Salamanders: From Molecules to Biorobotics

Ryczko

Simon

Ijspeert

2020

Trends in Neurosciences

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How do four-legged animals adapt their locomotion to the environment? How do central and peripheral mechanisms interact within the spinal cord to produce adaptive locomotion and how is locomotion recovered when spinal circuits are perturbed? Salamanders are the only tetrapods that regenerate voluntary locomotion after full spinal transection. Given their evolutionary position, they provide a unique opportunity to bridge discoveries made in fish and mammalian models. Genetic dissection of salamander neural circuits is becoming feasible with new methods for precise manipulation, elimination, and visualisation of cells. These approaches can be combined with classical tools in neuroscience and with modelling and a robotic environment. We propose that salamanders provide a blueprint of the function, evolution, and regeneration of tetrapod locomotor circuits. Salamanders as a Model Organism for Studying Locomotion Two major challenges in neuroscience are to decipher how the interplay between central and peripheral mechanisms controls locomotion in four-legged animals (tetrapods) and to delineate the reorganisation of motor circuits after spinal lesion. In this review, we outline the reasons why salamanders are ideally suited to address these two problems. First, salamanders are the only tetrapods capable of regenerating their locomotor circuits after full transection at adult stage [1-3]. Second, they are the closest extant representatives of the first tetrapods that transitioned from aquatic to terrestrial life [4]. This key evolutionary position makes salamanders ideal to provide a bridge between discoveries in fish (such as zebrafish) and mammals (such as mouse). Salamanders swim underwater and walk on ground [4], allowing researchers to investigate to what extent body dynamics and sensory feedback shape these locomotor patterns. Third, high precision dissection of their neural circuits is becoming possible thanks to new tools that will allow visualisation and optogenetic and chemogenetic manipulations that can be combined with classical neuroscience tools and advanced modelling and robotic environments. It is thus timely to highlight the recent advances in salamander research at the intersection of genomics, systems neuroscience, modelling, and robotics, which altogether provide a unique opportunity to decode locomotor control in the intact and regenerated tetrapod nervous system. In this review, we systematically place these approaches and recent results into a cross-species comparative setting, with a special focus on zebrafish and mouse as comparative models for which most data on the genetic identity of locomotor circuits are available. For closer examination of the locomotor circuitries of other related animal models such as lamprey, cat, and Xenopus embryo, we refer readers to prior reviews (lamprey: [5], cat: [6], Xenopus embryo: [7]). The Salamander Nervous System: A Bridge between Fish and Mammalian Models Salamander locomotor circuits include the main features found in all vertebrates (Figure 1A,C). Their...

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Section: Salamander Robots Numerical Models and Brain-machine Intermentioning

confidence: 99%

Walking with Salamanders: From Molecules to Biorobotics

Ryczko

Simon

Ijspeert

2020

Trends in Neurosciences

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“…Previous studies have modeled the CPG components using abstract oscillators (Ijspeert et al, 2005(Ijspeert et al, , 2007Knüsel et al, 2013;Yin et al, 2016), single bursting neurons (Liu et al, 2018(Liu et al, , 2020, integrate-and-fire neurons (Ijspeert, 2001;Bem et al, 2003;Harischandra et al, 2011;Knüsel et al, 2013) and detailed networks of three compartment Hodgkin-Huxley neurons (Bicanski et al, 2013).…”

Section: Related Modeling Workmentioning

confidence: 99%

“…The mechanical body of the salamander has been modeled with varying accuracy. Many models include four joints between the girdles and a single degree of freedom (DOF) per limb (Ijspeert, 2001;Ijspeert et al, 2005Ijspeert et al, , 2007Suzuki et al, 2019a) or three DOFs per limb (Harischandra et al, 2010(Harischandra et al, , 2011Liu et al, 2018Liu et al, , 2020). The simplest model has one of each (Yin et al, 2016), while other models have one joint between the girdles and two DOFs per limb (Zhong et al, 2018;Suzuki et al, 2019b).…”

Section: Related Modeling Workmentioning

confidence: 99%

“…The most accurate model has five joints between the girdles and four DOFs in each limb (Karakasiliotis et al, 2016;. Mechanical properties (damping and elasticity) of the body tissues were included in the muscle models used by Ijspeert (2001; Bem et al (2003), Harischandra et al (2010Harischandra et al ( , 2011, and Liu et al (2018Liu et al ( , 2020, and in the controller of Suzuki et al (2019b).…”

Section: Related Modeling Workmentioning

confidence: 99%

“…The effect of sensory feedback on the activity of the salamander CPG has only been investigated in simulation (Bem et al, 2003;Ijspeert et al, 2005;Harischandra et al, 2011;Liu et al, 2020). The role of sensory feedback in body-limb coordination has also been investigated using controllers without CPG, both in simulations and with a robot (Suzuki et al, 2019a).…”

Section: Related Modeling Workmentioning

confidence: 99%

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Reproducing Five Motor Behaviors in a Salamander Robot With Virtual Muscles and a Distributed CPG Controller Regulated by Drive Signals and Proprioceptive Feedback

et al. 2020

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Diverse locomotor behaviors emerge from the interactions between the spinal central pattern generator (CPG), descending brain signals and sensory feedback. Salamander motor behaviors include swimming, struggling, forward underwater stepping, and forward and backward terrestrial stepping. Electromyographic and kinematic recordings of the trunk show that each of these five behaviors is characterized by specific patterns of muscle activation and body curvature. Electrophysiological recordings in isolated spinal cords show even more diverse patterns of activity. Using numerical modeling and robotics, we explored the mechanisms through which descending brain signals and proprioceptive feedback could take advantage of the flexibility of the spinal CPG to generate different motor patterns. Adapting a previous CPG model based on abstract oscillators, we propose a model that reproduces the features of spinal cord recordings: the diversity of motor patterns, the correlation between phase lags and cycle frequencies, and the spontaneous switches between slow and fast rhythms. The five salamander behaviors were reproduced by connecting the CPG model to a mechanical simulation of the salamander with virtual muscles and local proprioceptive feedback. The main results were validated on a robot. A distributed controller was used to obtain the fast control loops necessary for implementing the virtual muscles. The distributed control is demonstrated in an experiment where the robot splits into multiple functional parts. The five salamander behaviors were emulated by regulating the CPG with two descending drives. Reproducing the kinematics of backward stepping and struggling however required stronger muscle contractions. The passive oscillations observed in the salamander's tail during forward underwater stepping could be reproduced using a third descending drive of zero to the tail oscillators. This reduced the drag on the body in our hydrodynamic simulation. We explored the effect of local proprioceptive feedback during swimming and forward terrestrial stepping. We found that feedback could replace or reduce the need for different drives in both cases. It also reduced the variability of intersegmental phase lags toward values appropriate for locomotion. Our work suggests that different motor behaviors do not require different CPG circuits: a single circuit can produce various behaviors when modulated by descending drive and sensory feedback.

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