Insect Walking Research Articles

Interleg coordination in free-walking bug Erthesina fullo (Hemiptera: Pentatomidae).

Insects can adapt their walking patterns to complex and varied environments and retain the ability to walk even after significant changes in their physical attributes, such as amputation. Although the interleg coordination of intact insects has been widely described in previous studies, the adaptive walking patterns in free-walking insects with amputation of 1 or more legs are still unclear. The pentatomid bug Erthesina fullo exhibits a tripod gait, when walking freely on horizontal substrates, like many other insects. In this study, amputations were performed on this species to investigate changes in interleg coordination. The walking parameters were analyzed, such as the locations of touchdown and liftoff, cycle period, walking speed, and head displacement of intact and amputated insects. The results show that E. fullo displays adaptive interleg coordination in response to amputations. With 1 amputated leg, bugs changed to a 3-unit gait, whereas with 2 amputated legs they employed a wave gait. These data are helpful in exploring the motion mode control in walking insects and provide the theoretical basis for the gait control strategy of robots, when leg failure occurs.

Kinematics and coordination of moth flies walking on smooth and rough surfaces.

The moth fly, Clogmia albipunctata, is a common synanthropic insect with a worldwide range that lives in nearly any area with moist, decaying organic matter. These habitats comprise both smooth, slippery substrates (e.g., bathroom drains) and heterogeneous, bumpy ground (e.g., soil in plant pots). By using terrain of varying levels of roughness, we focus specifically on how substrate roughness at the approximate size scale of the organism affects kinematics and coordination in adult moth flies. Finally, we compare and contrast our characterizations of locomotion in C. albipunctata with previous work of insect walking in naturalistic environments.

Dominant patterns in small directed bipartite networks: ubiquitous generalized tripod gait

The synchronization patterns exhibited by small networks of neurons that regulate biological processes (CPGs) have aroused growing scientific interest. In many of these networks there is a main behavioral pattern within the parameter space. In particular, in the context of insect locomotion, tripod walking stands out as a predominant pattern, both in natural observations (where insects walk on tripod gait) and in mathematical models. This predominance appears to be stable under parameter variations within the network, suggesting a possible correlation with the underlying network topology. Tripod walking can be naturally extended to all CPGs with a bipartite connectivity. Then a natural question arises: Are “generalized tripod gaits” equally dominant among synchronization patterns within those networks? To investigate this, we carried out a comprehensive study covering all bipartite networks of up to nine neurons. For each of those networks we numerically explore the phase space using a quasi-MonteCarlo method to see what are the main synchronization patterns that the network can achieve. Then, all those patterns are grouped according to their dynamics. Generalized tripod gait was observed in all cases examined as the dominant pattern again. However, certain cases revealed additional stable patterns, mainly associated with the 3-colorings of the respective graph structures.

The synaptic drive of central pattern-generating networks to leg motor neurons of a walking insect is motor neuron pool specific.

Rhythmic locomotor activity, such as flying, swimming, or walking, results from an interplay between higher-order centers in the central nervous system, which initiate, maintain, and modify task-specific motor activity, downstream central pattern-generating neural circuits (CPGs) that can generate a default rhythmic motor output, and, finally, feedback from sense organs that modify basic motor activity toward functionality.1,2,3 In this context, CPGs provide phasic synaptic drive to motor neurons (MNs) and thereby support the generation of rhythmic activity for locomotion. We analyzed the synaptic drive that the leg MNs supplying the three main leg joints receive from CPGs in pharmacologically activated and deafferented preparations of the stick insect (Carausius morosus). We show that premotor CPGs pattern the tonic activity of five of the six leg MN pools by phasic inhibitory synaptic drive. These are the antagonistic MN pools supplying the thoraco-coxal joint and the femur-tibial joint4,5 and the levator MN pool supplying the coxa-trochanteral (CTr) joint. In contrast, rhythmic activity of the depressor MN pool supplying the CTr joint was found to be primarily based on a phasic excitatory drive. This difference is likely related to the pivotal role of the depressor muscle in generating leg stance during any walking situation. Thus, our results provide evidence for qualitatively differing mechanisms to generate rhythmic activity between MN pools in the same locomotor system.

Motion Compensator for an Untethered Walking Insect Using Adaptive Model Predictive Control

Abstract A locomotion compensator is normally utilized to observe the behavior of walking insects. These compensators cancel out the movement of freely walking insects to facilitate long-term imaging for studying behavior. However, controlling the locomotion compensator with a small error (≤1 mm) has been challenging due to the random motion of walking insects. This study introduces an adaptive model predictive control (MPC) approach combined with trajectory prediction to effectively control the Transparent Omnidirectional Locomotion Compensator (TOLC) for a randomly walking fire ant. The proposed MPC with prediction (MPCwP) utilizes the average velocity from the previous gaiting cycle to estimate its future trajectory. Experimental results demonstrate that MPCwP significantly outperforms MPC without prediction (MPCwoP), which relies solely on the current position and orientation. The distance error of the MPCwP method remains below 0.6 mm for 90.3% and 1.0 mm for 99.2% of the time, whereas MPCwoP achieves this only 32.6% and 69.1% of the time, respectively. Furthermore, the proposed method enhances the tracking performance of the heading angle, with the heading angle error staying below 8° for 92.6% of the time (ωθ = 1.0). The enhanced performance of the proposed MPC has the potential to improve the observation images and enable the integration of additional equipment such as an optical microscope for brain or organ imaging.

A Computer Vision Milky Way Compass

The Milky Way is used by nocturnal flying and walking insects for maintaining heading while navigating. In this study, we have explored the feasibility of the method for machine vision systems on autonomous vehicles by measuring the visual features and characteristics of the Milky Way. We also consider the conditions under which the Milky Way is used by insects and the sensory systems that support their detection of the Milky Way. Using a combination of simulated and real Milky Way imagery, we demonstrate that appropriate computer vision methods are capable of reliably and accurately extracting the orientation of the Milky Way under an unobstructed night sky. The technique presented achieves angular accuracy of better then ±2° under moderate light pollution conditions but also demonstrates that higher light pollution levels will adversely effect orientation estimates by systems depending on the Milky Way for navigation.

Physiological properties of the visual system in the Green Weaver ant, Oecophylla smaragdina

The Green Weaver ants, Oecophylla smaragdina are iconic animals known for their extreme cooperative behaviour where they bridge gaps by linking to each other to build living chains. They are visually oriented animals, build chains towards closer targets, use celestial compass cues for navigation and are visual predators. Here, we describe their visual sensory capacity. The major workers of O. smaragdina have more ommatidia (804) in each eye compared to minor workers (508), but the facet diameters are comparable between both castes. We measured the impulse responses of the compound eye and found their response duration (42 ms) was similar to that seen in other slow-moving ants. We determined the flicker fusion frequency of the compound eye at the brightest light intensity to be 132 Hz, which is relatively fast for a walking insect suggesting the visual system is well suited for a diurnal lifestyle. Using pattern-electroretinography we identified the compound eye has a spatial resolving power of 0.5 cycles deg−1 and reached peak contrast sensitivity of 2.9 (35% Michelson contrast threshold) at 0.05 cycles deg−1. We discuss the relationship of spatial resolution and contrast sensitivity, with number of ommatidia and size of the lens.

A virtuous cycle between invertebrate and robotics research: perspective on a decade of Living Machines research

Many invertebrates are ideal model systems on which to base robot design principles due to their success in solving seemingly complex tasks across domains while possessing smaller nervous systems than vertebrates. Three areas are particularly relevant for robot designers: Research on flying and crawling invertebrates has inspired new materials and geometries from which robot bodies (their morphologies) can be constructed, enabling a new generation of softer, smaller, and lighter robots. Research on walking insects has informed the design of new systems for controlling robot bodies (their motion control) and adapting their motion to their environment without costly computational methods. And research combining wet and computational neuroscience with robotic validation methods has revealed the structure and function of core circuits in the insect brain responsible for the navigation and swarming capabilities (their mental faculties) displayed by foraging insects. The last decade has seen significant progress in the application of principles extracted from invertebrates, as well as the application of biomimetic robots to model and better understand how animals function. This Perspectives paper on the past 10 years of the Living Machines conference outlines some of the most exciting recent advances in each of these fields before outlining lessons gleaned and the outlook for the next decade of invertebrate robotic research.

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.

Prediction of Whole-Body Velocity and Direction From Local Leg Joint Movements in Insect Walking via LSTM Neural Networks

Extracting motion information from videos is important for quantifying data from behavioral experiments to deepen the understanding of generation mechanisms of animal behavior. For insect walking, inter-leg coordination plays a crucial role, and the thorax-coxa (ThC) and femur-tibia (FTi) joint motions of six legs reflect the walking velocity and direction. This suggests that joint-motion information based on a continuous time series is beneficial for dynamic behavior prediction. Since pose estimation from markerless videos has been extensively studied, the joint angle can be calculated accurately from videos via deep-learning algorithms such as DeepLabCut. Herein, we propose a method for the single-step and multi-step prediction of whole-body velocity and direction using leg joint angles. The method constructs models using long short-term memory (LSTM) and Hammerstein LSTM (HLSTM), with joint data as input, to predict the whole-body velocity and direction of insect walking. We investigated motion prediction with ThC and FTi joint angles using LSTM and HLSTM. The trained models predicted single-step motion information with the accuracy in the range of 73.28%–92.12% for velocity and 66.66%–87.46% for direction. Multi-step prediction for the next 10 steps showed the accuracy in the range of 99.56%–99.99% for velocity and 99.43%–99.95% for direction.

Motion Hacking – Understanding by Controlling Animals –

Insects exhibit resilient and flexible capabilities allowing them to adapt their walk in response to changes of the environment or body properties, for example the loss of a leg. While the motor control paradigm governing inter-leg coordination has been extensively studied in the past for such adaptive walking, the neural mechanism remains unknown. To overcome this situation, the project “Motion Hacking” develops a method for hacking leg movements by electrostimulating leg muscles while retaining the natural sensorimotor functions of the insect. This research aims to elucidate the flexible inter-leg coordination mechanism underlying insect walking by observing the adapting process of inter-leg coordination with the insect nervous system when leg movements are externally controlled via motion hacking.

Tardigrades exhibit robust interlimb coordination across walking speeds and terrains

Tardigrades must negotiate heterogeneous, fluctuating environments and accordingly utilize locomotive strategies capable of dealing with variable terrain. We analyze the kinematics and interleg coordination of freely walking tardigrades (species: Hypsibius exemplaris). We find that tardigrade walking replicates several key features of walking in insects despite disparities in size, skeleton, and habitat. To test the effect of environmental changes on tardigrade locomotor control circuits we measure kinematics and interleg coordination during walking on two substrates of different stiffnesses. We find that the phase offset between contralateral leg pairs is flexible, while ipsilateral coordination is preserved across environmental conditions. This mirrors similar results in insects and crustaceans. We propose that these functional similarities in walking coordination between tardigrades and arthropods is either due to a generalized locomotor control circuit common to panarthropods or to independent convergence onto an optimal strategy for robust multilegged control in small animals with simple circuitry. Our results highlight the value of tardigrades as a comparative system toward understanding the mechanisms-neural and/or mechanical-underlying coordination in panarthropod locomotion.

Universal Features in Panarthropod Inter-Limb Coordination during Forward Walking.

SynopsisTerrestrial animals must often negotiate heterogeneous, varying environments. Accordingly, their locomotive strategies must adapt to a wide range of terrain, as well as to a range of speeds to accomplish different behavioral goals. Studies in Drosophila have found that inter-leg coordination patterns (ICPs) vary smoothly with walking speed, rather than switching between distinct gaits as in vertebrates (e.g., horses transitioning between trotting and galloping). Such a continuum of stepping patterns implies that separate neural controllers are not necessary for each observed ICP. Furthermore, the spectrum of Drosophila stepping patterns includes all canonical coordination patterns observed during forward walking in insects. This raises the exciting possibility that the controller in Drosophila is common to all insects, and perhaps more generally to panarthropod walkers. Here, we survey and collate data on leg kinematics and inter-leg coordination relationships during forward walking in a range of arthropod species, as well as include data from a recent behavioral investigation into the tardigrade Hypsibius exemplaris. Using this comparative dataset, we point to several functional and morphological features that are shared among panarthropods. The goal of the framework presented in this review is to emphasize the importance of comparative functional and morphological analyses in understanding the origins and diversification of walking in Panarthropoda.Introduction

Triggering the proboscis extension reflex (PER) in Rhodnius prolixus

The heat emitted by the host body constitutes a short distance orientation cue for most blood-sucking insects, as is the case of the kissing-bug Rhodnius prolixus. We evaluated here how kissing bugs assess the distance to a warm target, in order to reach it by displaying the Proboscis Extension Reflex (PER). We confronted blind-folded insects to a thermal source either at 35° or at 40 °C under both, open- and closed-loop conditions. The results showed that nymphs were able to estimate the distance to a thermal source just using thermal information. Free walking insects displayed PER with a maximum frequency at 5 mm from the object, even without touching it. Yet, our experiments showed that the insects need to walk freely to estimate the distance to the source accurately, i.e. performing the PER at a distance allowing them to reach the target with the tip of the proboscis. The distance at which PER was triggered was independent of the temperature of the thermal source (35° or 40 °C). Moreover, our results also unravelled that mechanical stimuli can be integrated with thermal cues, being capable of affecting the triggering of PER in kissing bugs. This is the first study providing evidence that blood-sucking vector insects use mechanoreception for eliciting their bites. We discuss our findings in the light of present models explaining the ability of kissing bugs to estimate the distance and the temperature of a potential food sources.

Marker-Less Motion Capture of Insect Locomotion With Deep Neural Networks Pre-trained on Synthetic Videos.

Motion capture of unrestrained moving animals is a major analytic tool in neuroethology and behavioral physiology. At present, several motion capture methodologies have been developed, all of which have particular limitations regarding experimental application. Whereas marker-based motion capture systems are very robust and easily adjusted to suit different setups, tracked species, or body parts, they cannot be applied in experimental situations where markers obstruct the natural behavior (e.g., when tracking delicate, elastic, and/or sensitive body structures). On the other hand, marker-less motion capture systems typically require setup- and animal-specific adjustments, for example by means of tailored image processing, decision heuristics, and/or machine learning of specific sample data. Among the latter, deep-learning approaches have become very popular because of their applicability to virtually any sample of video data. Nevertheless, concise evaluation of their training requirements has rarely been done, particularly with regard to the transfer of trained networks from one application to another. To address this issue, the present study uses insect locomotion as a showcase example for systematic evaluation of variation and augmentation of the training data. For that, we use artificially generated video sequences with known combinations of observed, real animal postures and randomized body position, orientation, and size. Moreover, we evaluate the generalization ability of networks that have been pre-trained on synthetic videos to video recordings of real walking insects, and estimate the benefit in terms of reduced requirement for manual annotation. We show that tracking performance is affected only little by scaling factors ranging from 0.5 to 1.5. As expected from convolutional networks, the translation of the animal has no effect. On the other hand, we show that sufficient variation of rotation in the training data is essential for performance, and make concise suggestions about how much variation is required. Our results on transfer from synthetic to real videos show that pre-training reduces the amount of necessary manual annotation by about 50%.

Effect of Thoracic Connective Lesion on Inter-Leg Coordination in Freely Walking Stick Insects

Multi-legged locomotion requires appropriate coordination of all legs with coincident ground contact. Whereas behaviourally derived coordination rules can adequately describe many aspects of inter-leg coordination, the neural mechanisms underlying these rules are still not entirely clear. The fact that inter-leg coordination is strongly affected by cut thoracic connectives in tethered walking insects, shows that neural information exchange among legs is important. As yet, recent studies have shown that load transfer among legs can contribute to inter-leg coordination through mechanical coupling alone, i.e., without neural information exchange among legs. Since naturalistic load transfer among legs works only in freely walking animals but not in tethered animals, we tested the hypothesis that connective lesions have less strong effects if mechanical coupling through load transfer among legs is possible. To do so, we recorded protraction/retraction angles of all legs in unrestrained walking stick insects that either had one thoracic connective cut or had undergone a corresponding sham operation. In lesioned animals, either a pro-to-mesothorax or a meso-to-metathorax connective was cut. Overall, our results on temporal coordination were similar to published reports on tethered walking animals, in that the phase relationship of the legs immediately adjacent to the lesion was much less precise, although the effect on mean phase was relatively weak or absent. Lesioned animals could walk at the same speed as the control group, though with a significant sideward bias toward the intact side. Detailed comparison of lesion effects in free-walking and supported animals reveal that the strongest differences concern the spatial coordination among legs. In free walking, lesioned animals, touch-down and lift-off positions shifted significantly in almost all legs, including legs of the intact body side. We conclude that insects with disrupted neural information transfer through one connective adjust to this disruption differently if they experience naturalistic load distribution. While mechanical load transfer cannot compensate for lesion-induced effects on temporal inter-leg coordination, several compensatory changes in spatial coordination occur only if animals carry their own weight.

Descending and Ascending Signals That Maintain Rhythmic Walking Pattern in Crickets.

The cricket is one of the model animals used to investigate the neuronal mechanisms underlying adaptive locomotion. An intact cricket walks mostly with a tripod gait, similar to other insects. The motor control center of the leg movements is located in the thoracic ganglia. In this study, we investigated the walking gait patterns of the crickets whose ventral nerve cords were surgically cut to gain an understanding of how the descending signals from the head ganglia and ascending signals from the abdominal nervous system into the thoracic ganglia mediate the initiation and coordination of the walking gait pattern. Crickets whose paired connectives between the brain and subesophageal ganglion (SEG) (circumesophageal connectives) were cut exhibited a tripod gait pattern. However, when one side of the circumesophageal connectives was cut, the crickets continued to turn in the opposite direction to the connective cut. Crickets whose paired connectives between the SEG and prothoracic ganglion were cut did not walk, whereas the crickets exhibited an ordinal tripod gait pattern when one side of the connectives was intact. Crickets whose paired connectives between the metathoracic ganglion and abdominal ganglia were cut initiated walking, although the gait was not a coordinated tripod pattern, whereas the crickets exhibited a tripod gait when one side of the connectives was intact. These results suggest that the brain plays an inhibitory role in initiating leg movements and that both the descending signals from the head ganglia and the ascending signals from the abdominal nervous system are important in initiating and coordinating insect walking gait patterns.

The roles of ascending sensory signals and top-down central control in the entrainment of a locomotor CPG.

Previous authors have proposed two basic hypotheses about the factors that form the basis of locomotor rhythms in walking insects: sensory feedback only or sensory feedback together with rhythmic activity of small neural circuits called central pattern generators (CPGs). Here we focus on the latter. Following this concept, to generate functional outputs, locomotor control must feature both rhythm generation by CPGs at the level of individual joints and coordination of their rhythmic activities, so that all muscles are activated in an appropriate pattern. This work provides an in-depth analysis of an aspect of this coordination process based on an existing network model of stick insect locomotion. Specifically, we consider how the control system for a single joint in the stick insect leg may produce rhythmic output when subjected to ascending sensory signals from other joints in the leg. In this work, the core rhythm generating CPG component of the joint under study is represented by a classical half-center oscillator constrained by a basic set of experimental observations. While the dynamical features of this CPG, including phase transitions by escape and release, are well understood, we provide novel insights about how these transition mechanisms yield entrainment to the incoming sensory signal, how entrainment can be lost under variation of signal strength and period or other perturbations, how entrainment can be restored by modulation of tonic top-down drive levels, and how these factors impact the duty cycle of the motor output.

Spatio-temporal development of cuticular ridges on leaf surfaces of Hevea brasiliensis alters insect attachment.

Cuticular ridges on plant surfaces can control insect adhesion and wetting behaviour and might also offer stability to underlying cells during growth. The growth of the plant cuticle and its underlying cells possibly results in changes in the morphology of cuticular ridges and may also affect their function. We present spatial and temporal patterns in cuticular ridge development on the leaf surfaces of the model plant, Hevea brasiliensis. We have identified, by confocal laser scanning microscopy of polymer leaf replicas, an acropetally directed progression of ridges during the ontogeny of Hevea brasiliensis leaf surfaces. The use of Colorado potato beetles (Leptinotarsa decemlineata) as a model insect species has shown that the changing dimensions of cuticular ridges on plant leaves during ontogeny have a significant impact on insect traction forces and act as an effective indirect defence mechanism. The traction forces of walking insects are significantly lower on mature leaf surfaces compared with young leaf surfaces. The measured walking traction forces exhibit a strong negative correlation with the dimensions of the cuticular ridges.

Vision does not impact walking performance in Argentine ants.

Many walking insects use vision for long-distance navigation, but the influence of vision on rapid walking performance that requires close-range obstacle detection and directing the limbs towards stable footholds remains largely untested. We compared Argentine ant (Linepithema humile) workers in light versus darkness while traversing flat and uneven terrain. In darkness, ants reduced flat-ground walking speeds by only 5%. Similarly, the approach speed and time to cross a step obstacle were not significantly affected by lack of lighting. To determine whether tactile sensing might compensate for vision loss, we tracked antennal motion and observed shifts in spatiotemporal activity as a result of terrain structure but not illumination. Together, these findings suggest that vision does not impact walking performance in Argentine ant workers. Our results help contextualize eye variation across ants, including subterranean, nocturnal and eyeless species that walk in complete darkness. More broadly, our findings highlight the importance of integrating vision, proprioception and tactile sensing for robust locomotion in unstructured environments.