Interjoint coordination in the stick insect leg-control system: the role of positional signaling

neuroWalknet, a controller for hexapod walking allowing for context dependent behavior

Decentralized control has been established as a key control principle in insect walking and has been successfully leveraged to account for a wide range of walking behaviors in the proposed neuroWalknet architecture. This controller allows for walking patterns at different velocities in both, forward and backward direction-quite similar to the behavior shown in stick insects-, for negotiation of curves, and for robustly dealing with various disturbances. While these simulations focus on the cooperation of different, decentrally controlled legs, here we consider a set of biological experiments not yet been tested by neuroWalknet, that focus on the function of the individual leg and are context dependent. These intraleg studies deal with four groups of interjoint reflexes. The reflexes are elicited by stimulation of the femoral chordotonal organ (fCO) or groups of campaniform sensilla (CS). Motor output signals are recorded from the alpha-joint, the beta-joint or the gamma-joint of the leg. Furthermore, the influence of these sensory inputs to artificially induced oscillations by application of pilocarpine has been studied. Although these biological data represent results obtained from different local reflexes in different contexts, they fit with and are embedded into the behavior shown by the global structure of neuroWalknet. In particular, a specific and intensively studied behavior, active reaction, has since long been assumed to represent a separate behavioral element, from which it is not clear why it occurs in some situations, but not in others. This question could now be explained as an emergent property of the holistic structure of neuroWalknet which has shown to be able to produce artificially elicited pilocarpine-driven oscillation that can be controlled by sensory input without the need of explicit innate CPG structures. As the simulation data result from a holistic system, further results were obtained that could be used as predictions to be tested in further biological experiments.

Thorax-Segment- and Leg-Segment-Specific Motor Control for Adaptive Behavior

We have just started to understand the mechanisms underlying flexibility of motor programs among segmental neural networks that control each individual leg during walking in vertebrates and invertebrates. Here, we investigated the mechanisms underlying curve walking in the stick insect Carausius morosus during optomotor-induced turning. We wanted to know, whether the previously reported body-side specific changes in a two-front leg turning animal are also observed in the other thoracic leg segments. The motor activity of the three major leg joints showed three types of responses: 1) a context-dependent increase or decrease in motor neuron (MN) activity of the antagonistic MN pools of the thorax-coxa (ThC)-joint during inside and outside turns; 2) an activation of 1 MN pool with simultaneous cessation of the other, independent of the turning direction in the coxa-trochanteral (CTr)-joint; 3) a modification in the activity of both FTi-joint MN pools which depended on the turning direction in one, but not in the other thorax segment. By pharmacological activation of the meso- or metathoracic central pattern generating networks (CPG), we show that turning-related modifications in motor output involve changes to local CPG activity. The rhythmic activity in the MN pools of the ThC and CTr-joints was modified similarly to what was observed under control conditions in saline. Our results indicate that changes in meso- and metathoracic motor activity during curve walking are leg-joint- and thorax-segment-specific, can depend on the turning direction, and are mediated through changes in local CPG activity.

Insect-Inspired Robots: Bridging Biological and Artificial Systems

This review article aims to address common research questions in hexapod robotics. How can we build intelligent autonomous hexapod robots that can exploit their biomechanics, morphology, and computational systems, to achieve autonomy, adaptability, and energy efficiency comparable to small living creatures, such as insects? Are insects good models for building such intelligent hexapod robots because they are the only animals with six legs? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying relevant and future directions in the field of hexapod robotics over the next decade. After an introduction in section (1), the sections will respectively cover the following three key areas: (2) biomechanics focused on the design of smart legs; (3) locomotion control; and (4) high-level cognition control. These interconnected and interdependent areas are all crucial to improving the level of performance of hexapod robotics in terms of energy efficiency, terrain adaptability, autonomy, and operational range. We will also discuss how the next generation of bioroboticists will be able to transfer knowledge from biology to robotics and vice versa.

Investigating the role of low level reinforcement reflex loops in insect locomotion

Insects are highly capable walkers, but many questions remain regarding how the insect nervous system controls locomotion. One particular question is how information is communicated between the 'lower level' ventral nerve cord (VNC) and the 'higher level' head ganglia to facilitate control. In this work, we seek to explore this question by investigating how systems traditionally described as 'positive feedback' may initiate and maintain stepping in the VNC with limited information exchanged between lower and higher level centers. We focus on the 'reflex reversal' of the stick insect femur-tibia joint between a resistance reflex (RR) and an active reaction in response to joint flexion, as well as the activation of populations of descending dorsal median unpaired (desDUM) neurons from limb strain as our primary reflex loops. We present the development of a neuromechanical model of the stick insect (Carausius morosus) femur-tibia (FTi) and coxa-trochanter joint control networks 'in-the-loop' with a physical robotic limb. The control network generates motor commands for the robotic limb, whose motion and forces generate sensory feedback for the network. We based our network architecture on the anatomy of the non-spiking interneuron joint control network that controls the FTi joint, extrapolated network connectivity based on known muscle responses, and previously developed mechanisms to produce 'sideways stepping'. Previous studies hypothesized that RR is enacted by selective inhibition of sensory afferents from the femoral chordotonal organ, but no study has tested this hypothesis with a model of an intact limb. We found that inhibiting the network's flexion position and velocity afferents generated a reflex reversal in the robot limb's FTi joint. We also explored the intact network's ability to sustain steady locomotion on our test limb. Our results suggested that the reflex reversal and limb strain reinforcement mechanisms are both necessary but individually insufficient to produce and maintain rhythmic stepping in the limb, which can be initiated or halted by brief, transient descending signals. Removing portions of this feedback loop or creating a large enough disruption can halt stepping independent of the higher-level centers. We conclude by discussing why the nervous system might control motor output in this manner, as well as how to apply these findings to generalized nervous system understanding and improved robotic control.

Distributed control of motor circuits for backward walking in Drosophila

How do descending inputs from the brain control leg motor circuits to change how an animal walks? Conceptually, descending neurons are thought to function either as command-type neurons, in which a single type of descending neuron exerts a high-level control to elicit a coordinated change in motor output, or through a population coding mechanism, whereby a group of neurons, each with local effects, act in combination to elicit a global motor response. The Drosophila Moonwalker Descending Neurons (MDNs), which alter leg motor circuit dynamics so that the fly walks backwards, exemplify the command-type mechanism. Here, we identify several dozen MDN target neurons within the leg motor circuits, and show that two of them mediate distinct and highly-specific changes in leg muscle activity during backward walking: LBL40 neurons provide the hindleg power stroke during stance phase; LUL130 neurons lift the legs at the end of stance to initiate swing. Through these two effector neurons, MDN directly controls both the stance and swing phases of the backward stepping cycle. These findings suggest that command-type descending neurons can also operate through the distributed control of local motor circuits.

Lower complexity of motor primitives ensures robust control of high-speed human locomotion

Walking and running are mechanically and energetically different locomotion modes. For selecting one or another, speed is a parameter of paramount importance. Yet, both are likely controlled by similar low-dimensional neuronal networks that reflect in patterned muscle activations called muscle synergies. Here, we challenged human locomotion by having our participants walk and run at a very broad spectrum of submaximal and maximal speeds. The synergistic activations of lower limb locomotor muscles were obtained through decomposition of electromyographic data via non-negative matrix factorization. We analyzed the duration and complexity (via fractal analysis) over time of motor primitives, the temporal components of muscle synergies. We found that the motor control of high-speed locomotion was so challenging that the neuromotor system was forced to produce wider and less complex muscle activation patterns. The motor modules, or time-independent coefficients, were redistributed as locomotion speed changed. These outcomes show that humans cope with the challenges of high-speed locomotion by adapting the neuromotor dynamics through a set of strategies that allow for efficient creation and control of locomotion.

Central pattern generating networks in insect locomotion

Central pattern generators (CPGs) are neural circuits that based on their connectivity can generate rhythmic and patterned output in the absence of rhythmic external inputs. This property makes CPGs crucial elements in the generation of many kinds of rhythmic motor behaviors in insects, such as flying, walking, swimming, or crawling. Arguably representing the most diverse group of animals, insects utilize at least one of these types of locomotion during one stage of their ontogenesis. Insects have been extensively used to study the neural basis of rhythmic motor behaviors, and particularly the structure and operation of CPGs involved in locomotion. Here, we review insect locomotion with regard to flying, walking, and crawling, and we discuss the contribution of central pattern generation to these three forms of locomotion. In each case, we compare and contrast the topology and structure of the CPGs, and we point out how these factors are involved in the generation of the respective motor pattern. We focus on the importance of sensory information for establishing a functional motor output and we indicate behavior-specific adaptations. Furthermore, we report on the mechanisms underlying coordination between different body parts. Last but not least, by reviewing the state-of-the-art knowledge concerning the role of CPGs in insect locomotion, we endeavor to create a common ground, upon which future research in the field of motor control in insects can build.

Descending octopaminergic neurons modulate sensory-evoked activity of thoracic motor neurons in stick insects

Neuromodulatory neurons located in the brain can influence activity in locomotor networks residing in the spinal cord or ventral nerve cords of invertebrates. How inputs to and outputs of neuromodulatory descending neurons affect walking activity is largely unknown. With the use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and immunohistochemistry, we show that a population of dorsal unpaired median (DUM) neurons descending from the gnathal ganglion to thoracic ganglia of the stick insect Carausius morosus contains the neuromodulatory amine octopamine. These neurons receive excitatory input coupled to the legs’ stance phases during treadmill walking. Inputs did not result from connections with thoracic central pattern-generating networks, but, instead, most are derived from leg load sensors. In excitatory and inhibitory retractor coxae motor neurons, spike activity in the descending DUM (desDUM) neurons increased depolarizing reflexlike responses to stimulation of leg load sensors. In these motor neurons, descending octopaminergic neurons apparently functioned as components of a positive feedback network mainly driven by load-detecting sense organs. Reflexlike responses in excitatory extensor tibiae motor neurons evoked by stimulations of a femur-tibia movement sensor either are increased or decreased or were not affected by the activity of the descending neurons, indicating different functions of desDUM neurons. The increase in motor neuron activity is often accompanied by a reflex reversal, which is characteristic for actively moving animals. Our findings indicate that some descending octopaminergic neurons can facilitate motor activity during walking and support a sensory-motor state necessary for active leg movements.

NEW & NOTEWORTHY We investigated the role of descending octopaminergic neurons in the gnathal ganglion of stick insects. The neurons become active during walking, mainly triggered by input from load sensors in the legs rather than pattern-generating networks. This report provides novel evidence that octopamine released by descending neurons on stimulation of leg sense organs contributes to the modulation of leg sensory-evoked activity in a leg motor control system.

Temporal Relationship of Ocular and Tail Segmental Movements Underlying Locomotor-Induced Gaze Stabilization During Undulatory Swimming in Larval Xenopus

In larval xenopus, locomotor-induced oculomotor behavior produces gaze-stabilizing eye movements to counteract the disruptive effects of tail undulation during swimming. While neuronal circuitries responsible for feed-forward intrinsic spino-extraocular signaling have recently been described, the resulting oculomotor behavior remains poorly understood. Conveying locomotor CPG efference copy, the spino-extraocular motor command coordinates the multi-segmental rostrocaudal spinal rhythmic activity with the extraocular motor activity. By recording sequences of xenopus tadpole free swimming, we quantified the temporal calibration of conjugate eye movements originating from spino-extraocular motor coupled activity during pre-metamorphic tail-based undulatory swimming. Our results show that eye movements are produced only during robust propulsive forward swimming activity and increase with the amplitude of tail movements. The use of larval isolated in vitro and semi-intact fixed head preparations revealed that spinal locomotor networks driving the rostral portion of the tail set the precise timing of the spino-extraocular motor coupling by adjusting the phase relationship between spinal segment and extraocular rhythmic activity with the swimming frequency. The resulting spinal-evoked oculomotor behavior produced conjugated eye movements that were in phase opposition with the mid-caudal part of the tail. This time adjustment is independent of locomotor activity in the more caudal spinal parts of the tail. Altogether our findings demonstrate that locomotor feed-forward spino-extraocular signaling produce conjugate eye movements that compensate specifically the undulation of the mid-caudal tail during active swimming. Finally, this study constitutes the first extensive behavioral quantification of spino-extraocular motor coupling, which sets the basis for understanding the mechanisms of locomotor-induced oculomotor behavior in larval frog.

A load-based mechanism for inter-leg coordination in insects

Animals rely on an adaptive coordination of legs during walking. However, which specific mechanisms underlie coordination during natural locomotion remains largely unknown. One hypothesis is that legs can be coordinated mechanically based on a transfer of body load from one leg to another. To test this hypothesis, we simultaneously recorded leg kinematics, ground reaction forces and muscle activity in freely walking stick insects (Carausius morosus). Based on torque calculations, we show that load sensors (campaniform sensilla) at the proximal leg joints are well suited to encode the unloading of the leg in individual steps. The unloading coincides with a switch from stance to swing muscle activity, consistent with a load reflex promoting the stance-to-swing transition. Moreover, a mechanical simulation reveals that the unloading can be ascribed to the loading of a specific neighbouring leg, making it exploitable for inter-leg coordination. We propose that mechanically mediated load-based coordination is used across insects analogously to mammals.

A Synthetic Nervous System Controls a Simulated Cockroach

The purpose of this work is to better understand how animals control locomotion. This knowledge can then be applied to neuromechanical design to produce more capable and adaptable robot locomotion. To test hypotheses about animal motor control, we model animals and their nervous systems with dynamical simulations, which we call synthetic nervous systems (SNS). However, one major challenge is picking parameter values that produce the intended dynamics. This paper presents a design process that solves this problem without the need for global optimization. We test this method by selecting parameter values for SimRoach2, a dynamical model of a cockroach. Each leg joint is actuated by an antagonistic pair of Hill muscles. A distributed SNS was designed based on pathways known to exist in insects, as well as hypothetical pathways that produced insect-like motion. Each joint’s controller was designed to function as a proportional-integral (PI) feedback loop and tuned with numerical optimization. Once tuned, SimRoach2 walks through a simulated environment, with several cockroach-like features. A model with such reliable low-level performance is necessary to investigate more sophisticated locomotion patterns in the future.

Mantisbot is a robotic model of visually guided motion in the praying mantis

Insects use highly distributed nervous systems to process exteroception from head sensors, compare that information with state-based goals, and direct posture or locomotion toward those goals. To study how descending commands from brain centers produce coordinated, goal-directed motion in distributed nervous systems, we have constructed a conductance-based neural system for our robot MantisBot, a 29 degree-of-freedom, 13.3:1 scale praying mantis robot. Using the literature on mantis prey tracking and insect locomotion, we designed a hierarchical, distributed neural controller that establishes the goal, coordinates different joints, and executes prey-tracking motion. In our controller, brain networks perceive the location of prey and predict its future location, store this location in memory, and formulate descending commands for ballistic saccades like those seen in the animal. The descending commands are simple, indicating only 1) whether the robot should walk or stand still, and 2) the intended direction of motion. Each joint's controller uses the descending commands differently to alter sensory-motor interactions, changing the sensory pathways that coordinate the joints' central pattern generators into one cohesive motion. Experiments with one leg of MantisBot show that visual input produces simple descending commands that alter walking kinematics, change the walking direction in a predictable manner, enact reflex reversals when necessary, and can control both static posture and locomotion with the same network.

Template for the neural control of directed stepping generalized to all legs of MantisBot

We previously developed a neural controller for one leg of our six-legged robot, MantisBot, that could direct locomotion toward a goal by modulating leg-local reflexes with simple descending commands from a head sensor. In this work, we successfully apply an automated method to tune the control network for all three pairs of legs of our hexapod robot MantisBot in only 90 s with a desktop computer. Each foot's motion changes appropriately as the body's intended direction of travel changes. In addition, several results from studies of walking insects are captured by this model. This paper both demonstrates the broad applicability of this control method for robots, and suggests neural mechanisms underlying observations from walking insects.

Neuromechanical model of praying mantis explores the role of descending commands in pre-strike pivots

Praying mantises hunt by standing on their meso- and metathoracic legs and using them to rotate and translate (together, 'pivot') their bodies toward prey. We have developed a neuromechanical software model of the praying mantis Tenodera sinensis to use as a platform for testing postural controllers that the animal may use while hunting. Previous results showed that a feedforward model was insufficient for capturing the diversity of posture observed in the animal (Szczecinski et al 2014 Biomimetic and Biohybrid Syst. 3 296-307). Therefore we have expanded upon this model to make a flexible controller with feedback that more closely mimics the animal. The controller actuates 24 joints in the legs of a dynamical model to orient the head and translate the thorax toward prey. It is controlled by a simulation of nonspiking neurons assembled as a highly simplified version of networks that may exist in the mantid central complex and thoracic ganglia. Because of the distributed nature of these networks, we hypothesize that descending commands that orient the mantis toward prey may be simple direction-of-intent signals, which are turned into motor commands by the structure of low-level networks in the thoracic ganglia. We verify this through a series of experiments with the model. It captures the speed and range of mantid pivots as reported in other work (Yamawaki et al 2011 J. Insect Physiol. 57 1010-6). It is capable of pivoting toward prey from a variety of initial postures, as seen in the animal. Finally, we compare the model's joint kinematics during pivots to preliminary 3D kinematics collected from Tenodera.

A leg-local neural mechanism mediates the decision to search in stick insects

In many animals, individual legs can either function independently, as in behaviors such as scratching or searching, or be used in coordinated patterns with other legs, as in walking or climbing. While the control of walking has been extensively investigated, the mechanisms mediating the behavioral choice to activate individual legs independently are poorly understood. We examined this issue in stick insects, in which each leg can independently produce a rhythmic searching motor pattern if it doesn't find a foothold [1-4]. We show here that one non-spiking interneuron, I4, controls searching behavior in individual legs. One I4 is present in each hemi-segment of the three thoracic ganglia [5, 6]. Search-inducing sensory input depolarizes I4. I4 activity was necessary and sufficient to initiate and maintain searching movements. When substrate contact was provided, I4 depolarization no longer induced searching. I4 therefore both integrates search-inducing sensory input and is gated out by other sensory input (substrate contact). Searching thus occurs only when it is behaviorally appropriate. I4 depolarization never elicited stepping. These data show that individual, locally activated neurons can mediate the behavioral choice to use individual legs independently. This mechanism may be particularly important in insects' front legs, which can function independently like vertebrate arms and hands [7]. Similar local command mechanisms that selectively activate the pattern generators controlling repeated functional units such as legs or body segments may be present in other systems.

Task-dependent modification of leg motor neuron synaptic input underlying changes in walking direction and walking speed

Animals modify their behavior constantly to perform adequately in their environment. In terrestrial locomotion many forms of adaptation exist. Two tasks are changes of walking direction and walking speed. We investigated these two changes in motor output in the stick insect Cuniculina impigra to see how they are brought about at the level of leg motor neurons. We used a semi-intact preparation in which we can record intracellularly from leg motor neurons during walking. In this single-leg preparation the middle leg of the animal steps in a vertical plane on a treadwheel. Stimulation of either abdomen or head reliably elicits fictive forward or backward motor activity, respectively, in the fixed and otherwise deafferented thorax-coxa joint. With a change of walking direction only thorax-coxa-joint motor neurons protractor and retractor changed their activity. The protractor switched from swing activity during forward to stance activity during backward walking, and the retractor from stance to swing. This phase switch was due to corresponding change of phasic synaptic inputs from inhibitory to excitatory and vice versa at specific phases of the step cycle. In addition to phasic synaptic input a tonic depolarization of the motor neurons was present. Analysis of changes in stepping velocity during stance showed only a significant correlation to flexor motor neuron activity, but not to that of retractor and depressor motor neurons during forward walking. These results show that different tasks in the stick insect walking system are generated by altering synaptic inputs to specific leg joint motor neurons only.

A network model comprising 4 segmental, interconnected ganglia, and its application to simulate multi-legged locomotion in crustaceans

Inter-segmental coordination is crucial for the locomotion of animals. Arthropods show high variability of leg numbers, from 6 in insects up to 750 legs in millipedes. Despite this fact, the anatomical and functional organization of their nervous systems show basic similarities. The main similarities are the segmental organization, and the way the function of the segmental units is coordinated. We set out to construct a model that could describe locomotion (walking) in animals with more than 6 legs, as well as in 6-legged animals (insects). To this end, we extended a network model by Daun-Gruhn and Tóth (Journal of Computational Neuroscience, doi: 10.1007/s10827-010-0300-1 , 2011). This model describes inter-segmental coordination of the ipsilateral legs in the stick insect during walking. Including an additional segment (local network) into the original model, we could simulate coordination patterns that occur in animals walking on eight legs (e.g., crayfish). We could improve the model by modifying its original cyclic connection topology. In all model variants, the phase relations between the afferent segmental excitatory sensory signals and the oscillatory activity of the segmental networks played a crucial role. Our results stress the importance of this sensory input on the generation of different stable coordination patterns. The simulations confirmed that using the modified connection topology, the flexibility of the model behaviour increased, meaning that changing a single phase parameter, i.e., gating properties of just one afferent sensory signal was sufficient to reproduce all coordination patterns seen in the experiments.

The role of leg touchdown for the control of locomotor activity in the walking stick insect

Much is known on how select sensory feedback contributes to the activation of different motoneuron pools in the locomotor control system of stick insects. However, even though activation of the stance phase muscles depressor trochanteris, retractor unguis, flexor tibiae and retractor coxae is correlated with the touchdown of the leg, the potential sensory basis of this correlation or its connection to burst intensity remains unknown. In our experiments, we are using a trap door setup to investigate how ground contact contributes to stance phase muscle activation and burst intensity in different stick insect species, and which afferent input is involved in the respective changes. While the magnitude of activation is changed in all of the above stance phase muscles, only the timing of the flexor tibiae muscle is changed if the animal unexpectedly steps into a hole. Individual and combined ablation of different force sensors on the leg demonstrated influence from femoral campaniform sensilla on flexor muscle timing, causing a significant increase in the latencies during control and air steps. Our results show that specific load feedback signals determine the timing of flexor tibiae activation at the swing-to-stance transition in stepping stick insects, but that additional feedback may also be involved in flexor muscle activation during stick insect locomotion. With respect to timing, all other investigated stance phase muscles appear to be under sensory control other than that elicited through touchdown.

The effect of sensory feedback on crayfish posture and locomotion: I. Experimental analysis of closing the loop

The effect of proprioceptive feedback on the control of posture and locomotion was studied in the crayfish Procambarus clarkii (Girard). Sensory and motor nerves of an isolated crayfish thoracic nerve cord were connected to a computational neuromechanical model of the crayfish thorax and leg. Recorded levator (Lev) and depressor (Dep) nerve activity drove the model Lev and Dep muscles to move the leg up and down. These movements released and stretched a model stretch receptor, the coxobasal chordotonal organ (CBCO). Model CBCO length changes drove identical changes in the real CBCO; CBCO afferent responses completed the feedback loop. In a quiescent preparation, imposed model leg lifts evoked resistance reflexes in the Dep motor neurons that drove the leg back down. A muscarinic agonist, oxotremorine, induced an active state in which spontaneous Lev/Dep burst pairs occurred and an imposed leg lift excited a Lev assistance reflex followed by a Lev/Dep burst pair. When the feedback loop was intact, Lev/Dep burst pairs moved the leg up and down rhythmically at nearly three times the frequency of burst pairs when the feedback loop was open. The increased rate of rhythmic bursting appeared to result from the positive feedback produced by the assistance reflex.

Degradation of mouse locomotor pattern in the absence of proprioceptive sensory feedback

Mammalian locomotor programs are thought to be directed by the actions of spinal interneuron circuits collectively referred to as "central pattern generators." The contribution of proprioceptive sensory feedback to the coordination of locomotor activity remains less clear. We have analyzed changes in mouse locomotor pattern under conditions in which proprioceptive feedback is attenuated genetically and biomechanically. We find that locomotor pattern degrades upon elimination of proprioceptive feedback from muscle spindles and Golgi tendon organs. The degradation of locomotor pattern is manifest as the loss of interjoint coordination and alternation of flexor and extensor muscles. Group Ia/II sensory feedback from muscle spindles has a predominant influence in patterning the activity of flexor muscles, whereas the redundant activities of group Ia/II and group Ib afferents appear to determine the pattern of extensor muscle firing. These findings establish a role for proprioceptive feedback in the control of fundamental aspects of mammalian locomotor behavior.

A neuromechanical simulation of insect walking and transition to turning of the cockroach Blaberus discoidalis

A neuromechanical simulation of the cockroach Blaberus discoidalis was developed to explore changes in locomotion when the animal transitions from walking straight to turning. The simulation was based upon the biological data taken from three sources. Neural circuitry was adapted from the extensive literature primarily obtained from the studies of neural connections within thoracic ganglia of stick insect and adapted to cockroach. The 3D joint kinematic data on straight, forward walking for cockroach were taken from a paper that describes these movements in all joints simultaneously as the cockroach walked on an oiled-plate tether (Bender et al. in PloS one 5(10):1-15, 2010b). Joint kinematics for turning were only available for some leg joints (Mu and Ritzmann in J Comp Physiol A Neuroethol Sens Neural Behav Physiol 191(11):1037-54, 2005) and thus had to be obtained using the methods that were applied for straight walking by Bender et al. (PloS one 5(10):1-15, 2010b). Once walking, inside turning, and outside turning were characterized, phase and amplitude changes for each joint of each leg were quantified. Apparent reflex reversals and joint activity changes were used to modify sensory coupling pathways between the CPG at each joint of the simulation. Oiled-plate experiments in simulation produced tarsus trajectories in stance similar to those seen in the animal. Simulations including forces that would be experienced if the insect was walking freely (i.e., weight support and friction) again produced similar results. These data were not considered during the design of the simulation, suggesting that the simulation captures some key underlying the principles of walking, turning, and transitioning in the cockroach. In addition, since the nervous system was modeled with realistic neuron models, biologically plausible reflex reversals are simulated, motivating future neurobiological research.

A neuro-mechanical model explaining the physiological role of fast and slow muscle fibres at stop and start of stepping of an insect leg

Stop and start of stepping are two basic actions of the musculo-skeletal system of a leg. Although they are basic phenomena, they require the coordinated activities of the leg muscles. However, little is known of the details of how these activities are generated by the interactions between the local neuronal networks controlling the fast and slow muscle fibres at the individual leg joints. In the present work, we aim at uncovering some of those details using a suitable neuro-mechanical model. It is an extension of the model in the accompanying paper and now includes all three antagonistic muscle pairs of the main joints of an insect leg, together with their dedicated neuronal control, as well as common inhibitory motoneurons and the residual stiffness of the slow muscles. This model enabled us to study putative processes of intra-leg coordination during stop and start of stepping. We also made use of the effects of sensory signals encoding the position and velocity of the leg joints. Where experimental observations are available, the corresponding simulation results are in good agreement with them. Our model makes detailed predictions as to the coordination processes of the individual muscle systems both at stop and start of stepping. In particular, it reveals a possible role of the slow muscle fibres at stop in accelerating the convergence of the leg to its steady-state position. These findings lend our model physiological relevance and can therefore be used to elucidate details of the stop and start of stepping in insects, and perhaps in other animals, too.

Deriving neural network controllers from neuro-biological data: implementation of a single-leg stick insect controller

This article presents modular recurrent neural network controllers for single legs of a biomimetic six-legged robot equipped with standard DC motors. Following arguments of Ekeberg et al. (Arthropod Struct Dev 33:287-300, 2004), completely decentralized and sensori-driven neuro-controllers were derived from neuro-biological data of stick-insects. Parameters of the controllers were either hand-tuned or optimized by an evolutionary algorithm. Employing identical controller structures, qualitatively similar behaviors were achieved for robot and for stick insect simulations. For a wide range of perturbing conditions, as for instance changing ground height or up- and downhill walking, swing as well as stance control were shown to be robust. Behavioral adaptations, like varying locomotion speeds, could be achieved by changes in neural parameters as well as by a mechanical coupling to the environment. To a large extent the simulated walking behavior matched biological data. For example, this was the case for body support force profiles and swing trajectories under varying ground heights. The results suggest that the single-leg controllers are suitable as modules for hexapod controllers, and they might therefore bridge morphological- and behavioral-based approaches to stick insect locomotion control.

Activity Patterns and Timing of Muscle Activity in the Forward Walking and Backward Walking Stick Insect Carausius morosus

Understanding how animals control locomotion in different behaviors requires understanding both the kinematics of leg movements and the neural activity underlying these movements. Stick insect leg kinematics differ in forward and backward walking. Describing leg muscle activity in these behaviors is a first step toward understanding the neuronal basis for these differences. We report here the phasing of EMG activities and latencies of first spikes relative to precise electrical measurements of middle leg tarsus touchdown and liftoff of three pairs ( protractor/retractor coxae, levator/depressor trochanteris, extensor/flexor tibiae) of stick insect middle leg antagonistic muscles that play central roles in generating leg movements during forward and backward straight walking. Forward walking stance phase muscle (depressor, flexor, and retractor) activities were tightly coupled to touchdown, beginning on average 93 ms prior to and 9 and 35 ms after touchdown, respectively. Forward walking swing phase muscle (levator, extensor, and protractor) activities were less tightly coupled to liftoff, beginning on average 100, 67, and 37 ms before liftoff, respectively. In backward walking the protractor/retractor muscles reversed their phasing compared with forward walking, with the retractor being active during swing and the protractor during stance. Comparison of intact animal and reduced two- and one-middle-leg preparations during forward straight walking showed only small alterations in overall EMG activity but changes in first spike latencies in most muscles. Changing body height, most likely due to changes in leg joint loading, altered the intensity, but not the timing, of depressor muscle activity.

Organizing network action for locomotion: insights from studying insect walking

The operational basis for the generation of a functional motor output during walking is formed by the interaction between central pattern generating networks, local feedback from sensory neurons about movements and forces generated in the locomotor organs and coordinating signals from neighboring segments or appendages. This review primarily addresses the current knowledge about network organization underlying the control of an insect walking leg and recent advances in understanding the ways by which modifications in the motor output for walking are generated. Here we focus especially on modifications of the walking motor pattern that are associated with changing walking speed and walking direction. We will place the current knowledge and new results into the broad context gained from other locomotor behaviors and organisms.

Tethered stick insect walking: A modified slippery surface setup with optomotor stimulation and electrical monitoring of tarsal contact

A modified and improved setup based on Epstein and Graham [Epstein S, Graham D. Behaviour and motor output of stick insects walking on a slippery surface. I. Forward walking. J Exp Biol 1983;105: 215-29] to study straight and curve walking in the stick insect was developed and applications for its use are described. The animal is fixed on a balsa stick and walks freely on a slippery surface created with a thin film of a glycerin/water solution on a black, Ni-coated, polished brass plate. The glycerine/water ratio controls the viscosity of the lubricant and thereby the forces necessary to move the legs of the stick insect. A small amount of NaCl is added to ensure electric conductivity. Walking is induced through an optomotor stimulus given by two stripe-projectors producing rotatory and translatory stimuli to influence walking direction. The walking pattern is monitored in two ways: (1) tarsal contact with the slippery surface is measured electrically using a lock-in-amplifier. The tarsal contact signal allows correlation with the activity in different muscles of the stick insect leg recorded with EMG electrodes; (2) leg kinematics in the horizontal plane is monitored using synchronized high speed video. This setup allows us to determine the coupling of activity in different leg muscles to either swing or stance phase during straight and curve walking in the intact animal or the reduced single-leg preparation with a high time resolution.

The insecticide pymetrozine selectively affects chordotonal mechanoreceptors

Pymetrozine is a neuroactive insecticide but its site of action in the nervous system is unknown. Based on previous studies of symptoms in the locust, the feedback loop controlling the femur-tibia joint of the middle leg was chosen to examine possible targets of the insecticide. The femoral chordotonal organ, which monitors joint position and movement, turned out to be the primary site of pymetrozine action, while interneurons, motoneurons and central motor control circuitry in general did not noticeably respond to the insecticide. The chordotonal organs associated with the wing hinge stretch receptor and the tegula were influenced by pymetrozine in the same way as the femoral chordotonal organ, indicating that the insecticide affects chordotonal sensillae in general. Pymetrozine at concentrations down to 10(-8) mol l(-1) resulted in the loss of stimulus-related responses and either elicited (temporary) tonic discharges or eliminated spike activity altogether. Remarkably, pymetrozine affected the chordotonal organs in an all-or-none fashion, in agreement with previous independent studies. Other examined sense organs did not respond to pymetrozine, namely campaniform sensillae on the tibia and the subcosta vein, hair sensillae of the tegula (type I sensillae), and the wing hinge stretch receptor (type II sensillae).

Invertebrate central pattern generation moves along

Central pattern generators (CPGs) are circuits that generate organized and repetitive motor patterns, such as those underlying feeding, locomotion and respiration. We summarize recent work on invertebrate CPGs which has provided new insights into how rhythmic motor patterns are produced and how they are controlled by higher-order command and modulatory interneurons.

Sensory control and organization of neural networks mediating coordination of multisegmental organs for locomotion

It is well established that locomotor patterns result from the interaction between central pattern generating networks in the nervous system, local feedback from sensory neurons about movements and forces generated in the locomotor organs, and coordinating signals from neighboring segments or appendages. This review addresses the issue of how the movements of multi-segmented locomotor organs are coordinated and provides an overview of recent advances in understanding sensory control and the internal organization of central pattern generating networks that operate multi-segmented locomotor organs, such as a walking leg. Findings from the stick insect and the cat are compared and discussed in relation to new findings on the lamprey swimming network. These findings support the notion that common schemes of sensory feedback are used for generating walking and that central neural networks controlling multi-segmented locomotor organs generally encompass multiple central pattern generating networks that correspond with the segmental structure of the locomotor organ.

Quantitative Characterization and Classification of Leech Behavior

This paper describes an automatic system for the analysis and classification of leech behavior. Three colored beads were attached to the dorsal side of a free moving or pinned leech, and color CCD camera images were taken of the animal. The leech was restrained to moving in a small tank or petri dish, where the water level can be varied. An automatic system based on color processing tracked the colored beads over time, allowing real-time monitoring of the leech motion for several hours. At the end of each experimental session, six time series (2 for each bead) describing the leech body motion were obtained. A statistical analysis based on the speed and frequency content of bead motion indicated the existence of several stereotypical patterns of motion, corresponding to different leech behaviors. The identified patterns corresponded to swimming, pseudo-swimming, crawling, exploratory behavior, stationary states, abrupt movements, and combinations of these behaviors. The automatic characterization of leech behavior demonstrated here represents an important step toward understanding leech behavior and its properties. This method can be used to characterize the behavior of other invertebrates and also for some small vertebrates.

Intersegmental coordination of walking movements in stick insects

Locomotion requires the coordination of movements across body segments, which in walking animals is expressed as gaits. We studied the underlying neural mechanisms of this coordination in a semi-intact walking preparation of the stick insect Carausius morosus. During walking of a single front leg on a treadmill, leg motoneuron (MN) activity tonically increased and became rhythmically modulated in the ipsilateral deafferented and deefferented mesothoracic (middle leg) ganglion. The pattern of modulation was correlated with the front leg cycle and specific for a given MN pool, although it was not consistent with functional leg movements for all MN pools. In an isolated preparation of a pair of ganglia, where one ganglion was made rhythmically active by application of pilocarpine, we found no evidence for coupling between segmental central pattern generators (CPGs) that could account for the modulation of MN activity observed in the semi-intact walking preparation. However, a third preparation provided evidence that signals from the front leg's femoral chordotonal organ (fCO) influenced activity of ipsilateral MNs in the adjacent mesothoracic ganglion. These intersegmental signals could be partially responsible for the observed MN activity modulation during front leg walking. While afferent signals from a single walking front leg modulate the activity of MNs in the adjacent segment, additional afferent signals, local or from contralateral or posterior legs, might be necessary to produce the functional motor pattern observed in freely walking animals.

Dynamic simulation of insect walking

Insect walking relies on a complex interaction between the environment, body segments, muscles and the nervous system. For the stick insect in particular, previous investigations have highlighted the role of specific sensory signals in the timing of activity of central neural networks driving the individual leg joints. The objective of the current study was to relate specific sensory and neuronal mechanisms, known from experiments on reduced preparations, to the generation of the natural sequence of events forming the step cycle in a single leg. We have done this by simulating a dynamic 3D-biomechanical model of the stick insect coupled to a reduced model of the neural control system, incorporating only the mechanisms under study. The neural system sends muscle activation levels to the biomechanical system, which in turn provides correctly timed propriosensory signals back to the neural model. The first simulations were designed to test if the currently known mechanisms would be sufficient to explain the coordinated activation of the different leg muscles in the middle leg. Two experimental situations were mimicked: restricted stepping where only the coxa-trochanteral joint and the femur-tibia joint were free to move, and the unrestricted single leg movements on a friction-free surface. The first of these experimental situations is in fact similar to the preparation used in gathering much of the detailed knowledge on sensory and neuronal mechanisms. The simulations show that the mechanisms included can indeed account for the entire step cycle in both situations. The second aim was to test to what extent the same sensory and neuronal mechanisms would be adequate also for controlling the front and hind legs, despite the large differences in both leg morphology and kinematic patterns. The simulations show that front leg stepping can be generated by basically the same mechanisms while the hind leg control requires some reorganization. The simulations suggest that the influence from the femoral chordotonal organs on the network controlling levation-depression may have a reversed effect in the hind legs as compared to the middle and front legs. This, and other predictions from the model will have to be confirmed by additional experiments.

Signals From Load Sensors Underlie Interjoint Coordination During Stepping Movements of the Stick Insect Leg

During stance and swing phase of a walking stick insect, the retractor coxae (RetCx) and protractor coxae (ProCx) motoneurons and muscles supplying the thorax-coxa (TC)-joint generate backward and forward movements of the leg. Their activity is tightly coupled to the movement of the more distal leg segments, i.e., femur, tibia, and tarsus. We used the single middle leg preparation to study how this coupling is generated. With only the distal leg segments of the middle leg being free to move, motoneuronal activity of the de-afferented and -efferented TC-joint is similarly coupled to leg stepping. RetCx motoneurons are active during stance and ProCx motoneurons during swing. We studied whether sensory signals are involved in this coordination of TC-joint motoneuronal activity. Ablation of the load measuring campaniform sensilla (CS) revealed that they substantially contribute to the coupling of TC-joint motoneuronal activity to leg stepping. Individually ablating trochanteral and femoral CS revealed the trochanteral CS to be necessary for establishing the coupling between leg stepping and coxal motoneuron activity. When the locomotor system was active and generated alternating bursts of activity in ProCx and RetCx motoneurons, stimulation of the CS by rearward bending of the femur in otherwise de-afferented mesothoracic ganglion terminated ongoing ProCx motoneuronal activity and initiated RetCx motoneuronal activity. We show that cuticular strain signals from the trochanteral CS play a major role in shaping TC-joint motoneuronal activity during walking and contribute to their coordination with the stepping pattern of the distal leg joints. We present a model for the sensory control of timing of motoneuronal activity in walking movements of the single middle leg.

Synaptic drive contributing to rhythmic activation of motoneurons in the deafferented stick insect walking system

A general feature of motor patterns for locomotion is their cyclic and alternating organization. In walking, for example, rhythmic activity in leg motoneurons innervating antagonistic muscles of a joint is primarily antiphasic within each cycle. We investigate which role central pattern generating networks play in the generation of leg motoneuron activity in the absence of sensory feedback. We elicited activity in antagonistic flexor and extensor tibiae motoneurons in the deafferented mesothoracic ganglion of the stick insect by mechanically stimulating the head or abdomen, while recording intracellularly from their neuropilar processes. In most cases, tactile stimulation induced coactivation of tibial motoneurons. However, in approximately 25% of the trials, tibial motoneurons generated alternating cycles consisting of bursts of action potentials that were terminated by strong inhibitory synaptic inputs. Injection of depolarizing current increased the amplitude of the inhibitory phase of the oscillation, while hyperpolarizing current decreased it and revealed a tonic depolarization of the motor neurons during the bout of rhythmic motor activity. The same results were gathered from recording tibial leg motoneurons during 'twitching' motor activity in decerebrated animals. Our results indicate that alternating rhythmic motoneuron activity in the deafferented stick insect walking system results from phasic inhibitory drive provided by central pattern generating networks. This inhibitory input patterns the firing of the motoneurons that results from a tonic depolarizing drive. This tonic depolarizing drive was also observed in tibial motoneurons of the deafferented mesothoracic ganglion during walking movements of the intact ipsilateral front leg.