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  • 1.
    Bicanski, Andrej
    et al.
    School of Engineering, École Polytechnique Fédérale de Lausanne.
    Ryczko, Dimitri
    Département de Physiologie, Université de Montréa.
    Knuesel, Jérémie
    School of Engineering, École Polytechnique Fédérale de Lausanne.
    Harischandra, Nalin
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Charrier, Vanessa
    INSERM U862, Neurocentre Magendie, Université Bordeaux.
    Ekeberg, Örjan
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Cabelguen, Jean-Marie
    Neurocentre Magendie, Bordeaux University, Bordeaux Cedex, France.
    Ijspeert, Auke Jan
    School of Engineering, École Polytechnique Fédérale de Lausanne.
    Decoding the mechanisms of gait generation in salamanders by combining neurobiology, modeling and robotics2013In: Biological Cybernetics, ISSN 0340-1200, E-ISSN 1432-0770, Vol. 107, no 5, p. 545-564Article, review/survey (Refereed)
    Abstract [en]

    Vertebrate animals exhibit impressive locomotor skills. These locomotor skills are due to the complex interactions between the environment, the musculo-skeletal system and the central nervous system, in particular the spinal locomotor circuits. We are interested in decoding these interactions in the salamander, a key animal from an evolutionary point of view. It exhibits both swimming and stepping gaits and is faced with the problem of producing efficient propulsive forces using the same musculo-skeletal system in two environments with significant physical differences in density, viscosity and gravitational load. Yet its nervous system remains comparatively simple. Our approach is based on a combination of neurophysiological experiments, numerical modeling at different levels of abstraction, and robotic validation using an amphibious salamander-like robot. This article reviews the current state of our knowledge on salamander locomotion control, and presents how our approach has allowed us to obtain a first conceptual model of the salamander spinal locomotor networks. The model suggests that the salamander locomotor circuit can be seen as a lamprey-like circuit controlling axial movements of the trunk and tail, extended by specialized oscillatory centers controlling limb movements. The interplay between the two types of circuits determines the mode of locomotion under the influence of sensory feedback and descending drive, with stepping gaits at low drive, and swimming at high drive.

  • 2.
    Harischandra, Nalin
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Building a computer simulator for the study of stepping of the cat2007Report (Other academic)
    Abstract [en]

    We have developed a 3-dimensional computer simulator for investigation on the neuro-musculo-skeletal system and its interactions during normal walking of the cat. Main components of the cat model are the simulation of skeletal dynamics and the control system that includes a mathematical muscle model and a central pattern generator (CPG) network. The simulator is programmed in Python scripting language with other supported open source libraries such as Open Dynamics Engine (ODE) for body dynamics and Opengl for 3-D graphical representation. Modular structure and the object oriented programming technique allows easy access to the model parameters and the modules can be easily modified without altering the entire program. To test the model’s functionality, a simple experiment, during which the cat was set to walk on a flat surface with only the hind legs’ muscles were controlled by two separate CPGs with no sensory feed back, was carried out. It was possible to obtain a realistic stepping in the hind legs even without sensory feedback to the two controllers for each leg. We conclude that the mechanical linkages between the legs also play a major role in producing alternating gait.

  • 3.
    Harischandra, Nalin
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Computer Simulation of the Neural Control of Locomotion in the Cat2008Licentiate thesis, comprehensive summary (Other scientific)
    Abstract [en]

    Locomotion is one of the most important behaviours and requires interaction between sensors at various levels of the nervous system and the limb muscles of an animal. The basic neural rhythm for locomotion in mammals has been shown to arise from local neural networks residing in the spinal cord and these networks are known as central pattern generators (CPGs). However, during the locomotion, these centres are constantly interacting with the sensory feedback signals coming from muscles, joints and peripheral skin receptors in order to adapt the stepping to varying environmental conditions. Conceptual models of mammalian locomotion have been constructed using

    mathematical models of locomotor subsystems based on the abundance of neurophysiological evidence obtained primarily in the cat. Several aspects of locomotor control using the cat as an animal model have been investigated employing computer simulations and here we use the same approach to address number of questions or/and hypotheses related to rhythmic locomotion in quadrupeds. Some of the involve questions are, role of mechanical linkage during deafferented walking, finding inherent stabilities/instabilities of muscle-joint interactions during normal walking, estimating phase dependent controlability of muscle action over joints.

    This thesis presents the basics of a biologically realistic model of mammalian locomotion and summarises methodological approaches in modelling quadruped locomotor subsystems such as CPGs, limb muscles and sensory pathways. In the first appended article, we extensively discuss the construction details of the three-dimensional computer simulator for the study of the hind leg neuro-musculo-skeletal-control system and its interactions during normal walking of the cat. The simulator with the walking model is programmed in Python scripting language with other supported open source libraries such as Open Dynamics Engine (ODE) for simulating body dynamics and OpenGL for three dimensional graphical representation. We have examined the

    functionality of the simulator and the walking model by simulating deafferented walking. It was possible to obtain a realistic stepping in the hind legs even without sensory feedback to the two controllers (CPGs) for each leg. We conclude that the mechanical linkages between the legs also play a major role in producing alternating gait.

    The use of simulations of walking in the cat for gaining insights into more complex interactions between the environment and the neuro-muscular-skeletal system is important especially for questions where a direct neurophysiological experiment can not be performed on a real walking animal. For instance, it is experimentally hard to isolate individual mechanisms without disrupting the natural walking pattern. In the second article, we introduce a different approach where we use the walking model to identify what control is necessary to maintain stability in the musculo-skeletal system. We show that the actions of most of the hindlimb muscles over the joints have an inherent stability during stepping, even without the involvement of proprioceptive feedback mechanisms. In addition, we observe that muscles generating movements in the ankle joint of the hind leg must be controlled by neural mechanisms, which may involve supraspinal structures, over the whole step cycle.

  • 4.
    Harischandra, Nalin
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Computer Simulation of the Neural Control of Locomotion in the Cat and the Salamander2011Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Locomotion is an integral part of a whole range of animal behaviours. The basic rhythm for locomotion in vertebrates has been shown to arise from local networks residing in the spinal cord and these networks are known as central pattern generators (CPG). However, during the locomotion, these centres are constantly interacting with the sensory feedback signals coming from muscles, joints and peripheral skin receptors in order to adapt the stepping or swimming to varying environmental conditions. Conceptual models of vertebrate locomotion have been constructed using mathematical models of locomotor subsystems based on the neurophysiological evidence obtained primarily in the cat and the salamander, an amphibian with a sprawling posture. Such models provide opportunity for studying the key elements in the transition from aquatic to terrestrial locomotion. Several aspects of locomotor control using the cat or the salamander as an animal model have been investigated employing computer simulations and here we use the same approach to address a number of questions or/and hypotheses related to rhythmic locomotion in quadrupeds. Some of the involved questions are, the role of mechanical linkage during deafferented walking, finding inherent stabilities/instabilities of muscle-joint interactions during normal walking and estimating phase dependent controlability of muscle action over joints. Also we investigate limb and body coordination for different gaits, use of side-stepping in front limbs for turning and the role of sensory feedback in gait generation and transitions in salamanders.

         This thesis presents the basics of the biologically realistic models of cat and salamander locomotion and summarizes computational methods in modeling quadruped locomotor subsystems such as CPG, limb muscles and sensory pathways. In the case of cat hind limb, we conclude that the mechanical linkages between the legs play a major role in producing the alternating gait. In another experiment we use the model to identify open-loop linear transfer functions between muscle activations and joint angles while ongoing locomotion. We hypothesize that the musculo-skeletal system for locomotion in animals, at least in cats, operates under critically damped condition.

         The 3D model of the salamander is successfully used to mimic locomotion on level ground and in water. We compare the walking gait with the trotting gait in simulations. We also found that for turning, the use of side-stepping alone or in combination with trunk bending is more effective than the use of trunk bending alone. The same model together with a more realistic CPG composed of spiking neurons was used to investigate the role of sensory feedback in gait generation and transition. We found that the proprioceptive sensory inputs are essential in obtaining the walking gait, whereas the trotting gait is more under central (CPG) influence compared to that of the peripheral or sensory feedback.

         This thesis work sheds light on understanding the neural control mechanisms behind vertebrate locomotion. Additionally, both neuro-mechanical models can be used for further investigations in finding new control algorithms which give robust, adaptive, efficient and realistic stepping in each leg, which would be advantageous since it can be implemented on a controller of a quadruped-robotic device.

  • 5.
    Harischandra, Nalin
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Cabelguen, Jean-Marie
    Neurocentre Magendie, Bordeaux University, Bordeaux Cedex, France.
    Ekeberg, Örjan
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    A 3D musculo-mechanical model of the salamander for the study of different gaits and modes of locomotion2010In: Frontiers in neurorobotics, ISSN 1662-5218, Vol. 4, p. 112-Article in journal (Refereed)
    Abstract [en]

    Computer simulation has been used to investigate several aspects of locomotion in salamanders. Here we introduce a three-dimensional forward dynamics mechanical model of a salamander, with physically realistic weight and size parameters. Movements of the four limbs and of the trunk and tail are generated by sets of linearly modeled skeletal muscles. In this study, activation of these muscles were driven by prescribed neural output patterns. The model was successfully used to mimic locomotion on level ground and in water. We compare the walking gait where a wave of activity in the axial muscles travels between the girdles, with the trotting gait in simulations using the musculo-mechanical model. In a separate experiment, the model is used to compare different strategies for turning while stepping; either by bending the trunk or by using side-stepping in the front legs. We found that for turning, the use of side-stepping alone or in combination with trunk bending, was more effective than the use of trunk bending alone. We conclude that the musculo-mechanical model described here together with a proper neural controller is useful for neuro-physiological experiments in silico.

  • 6.
    Harischandra, Nalin
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Ekeberg, Örjan
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    System identification of muscle-joint interactions of the cat hind limb during locomotion2008In: Biological Cybernetics, ISSN 0340-1200, E-ISSN 1432-0770, Vol. 99, no 2, p. 125-138Article in journal (Refereed)
    Abstract [en]

    Neurophysiological experiments in walking cats have shown that a number of neural control mechanisms are involved in regulating the movements of the hind legs during locomotion. It is experimentally hard to isolate individual mechanisms without disrupting the natural walking pattern and we therefore introduce a different approach where we use a model to identify what control is necessary to maintain stability in the musculo-skeletal system. We developed a computer simulation model of the cat hind legs in which the movements of each leg are produced by eight limb muscles whose activations follow a centrally generated pattern with no proprioceptive feedback. All linear transfer functions, from each muscle activation to each joint angle, were identified using the response of the joint angle to an impulse in the muscle activation at 65 postures of the leg covering the entire step cycle. We analyzed the sensitivity and stability of each muscle action on the joint angles by studying the gain and pole plots of these transfer functions. We found that the actions of most of the hindlimb muscles display inherent stability during stepping, even without the involvement of any proprioceptive feedback mechanisms, and that those musculo-skeletal systems are acting in a critically damped manner, enabling them to react quickly without unnecessary oscillations. We also found that during the late swing, the activity of the posterior biceps/semitendinosus (PB/ST) muscles causes the joints to be unstable. In addition, vastus lateralis (VL), tibialis anterior (TA) and sartorius (SAT) muscle-joint systems were found to be unstable during the late stance phase, and we conclude that those muscles require neuronal feedback to maintain stable stepping, especially during late swing and late stance phases. Moreover, we could see a clear distinction in the pole distribution (along the step cycle) for the systems related to the ankle joint from that of the other two joints, hip or knee. A similar pattern, i.e., a pattern in which the poles were scattered over the s-plane with no clear clustering according to the phase of the leg position, could be seen in the systems related to soleus (SOL) and TA muscles which would indicate that these muscles depend on neural control mechanisms, which may involve supraspinal structures, over the whole step cycle.

  • 7.
    Harischandra, Nalin
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Knuesel, Jeremei
    EPFL.
    Kozlov, Alexander
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Bicanski, Andrej
    EPFL.
    Cabelguen, Jean-Marie
    Neurocentre Magendie, Bordeaux University, Bordeaux Cedex, France.
    Ijspeert, Auke
    EPFL.
    Ekeberg, Örjan
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Sensory feedback plays a significant role in generating walking gait and in gait transition in salamanders: a simulation study2011In: Frontiers in Neurorobotics, ISSN 1662-5218, Vol. 5, p. 3:1-3:13Article in journal (Refereed)
    Abstract [en]

    Here, we investigate the role of sensory feedback in gait generation and transition by using a three-dimensional, neuro-musculo-mechanical model of a salamander with realistic physical parameters. Activation of limb and axial muscles were driven by neural output patterns obtained from a central pattern generator (CPG) which is composed of simulated spiking neurons with adaptation. The CPG consists of a body-CPG and four limb-CPGs that are interconnected via synapses both ipsilaterally and contralaterally. We use the model both with and without sensory modulation and four different combinations of ipsilateral and contralateral coupling between the limb-CPGs. We found that the proprioceptive sensory inputs are essential in obtaining a coordinated lateral sequence walking gait (walking). The sensory feedback includes the signals coming from the stretch receptor like intraspinal neurons located in the girdle regions and the limb stretch receptors residing in the hip and scapula regions of the salamander. On the other hand, walking trot gait (trotting) is more under central (CPG) influence compared to that of the peripheral or sensory feedback. We found that the gait transition from walking to trotting can be induced by increased activity of the descending drive coming from the mesencephalic locomotor region and is helped by the sensory inputs at the hip and scapula regions detecting the late stance phase. More neurophysiological experiments are required to identify the precise type of mechanoreceptors in the salamander and the neural mechanisms mediating the sensory modulation.

  • 8.
    Kamali Sarvestani, Iman
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Kozlov, Alexander
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Harischandra, Nalin
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Grillner, Sten
    Karolinska Institutet.
    Ekeberg, Örjan
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    A computational model of visually guided locomotion in lamprey2013In: Biological Cybernetics, ISSN 0340-1200, E-ISSN 1432-0770, Vol. 107, no 5, p. 497-512Article in journal (Refereed)
    Abstract [en]

    This study addresses mechanisms for the generation and selection of visual behaviors in anamniotes. To demonstrate the function of these mechanisms, we have constructed an experimental platform where a simulated animal swims around in a virtual environment containing visually detectable objects. The simulated animal moves as a result of simulated mechanical forces between the water and its body. The undulations of the body are generated by contraction of simulated muscles attached to realistic body components. Muscles are driven by simulated motoneurons within networks of central pattern generators. Reticulospinal neurons, which drive the spinal pattern generators, are in turn driven directly and indirectly by visuomotor centers in the brainstem. The neural networks representing visuomotor centers receive sensory input from a simplified retina. The model also includes major components of the basal ganglia, as these are hypothesized to be key components in behavior selection. We have hypothesized that sensorimotor transformation in tectum and pretectum transforms the place-coded retinal information into rate-coded turning commands in the reticulospinal neurons via a recruitment network mimicking the layered structure of tectal areas. Via engagement of the basal ganglia, the system proves to be capable of selecting among several possible responses, even if exposed to conflicting stimuli. The anatomically based structure of the control system makes it possible to disconnect different neural components, yielding concrete predictions of how animals with corresponding lesions would behave. The model confirms that the neural networks identified in the lamprey are capable of responding appropriately to simple, multiple, and conflicting stimuli.

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