Comparative whole-body kinematics of closely related insect species with different body morphology

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.

Comparative morphology of serotonin-immunoreactive neurons innervating the central complex in the brain of dicondylian insects

Serotonin (5-hydroxytryptamine) acts as a widespread neuromodulator in the nervous system of vertebrates and invertebrates. In insects, it promotes feeding, enhances olfactory sensitivity, modulates aggressive behavior, and, in the central complex of Drosophila, serves a role in sleep homeostasis. In addition to a role in sleep-wake regulation, the central complex has a prominent role in spatial orientation, goal-directed locomotion, and navigation vector memory. To further understand the role of serotonergic signaling in this brain area, we analyzed the distribution and identity of serotonin-immunoreactive neurons across a wide range of insect species. While one bilateral pair of tangential neurons innervating the central body was present in all species studied, a second type was labeled in all neopterans but not in dragonflies and firebrats. Both cell types show conserved major fiber trajectories but taxon-specific differences in dendritic targets outside the central body and axonal terminals in the central body, noduli, and lateral accessory lobes. In addition, numerous tangential neurons of the protocerebral bridge were labeled in all studied polyneopteran species except for Phasmatodea, but not in Holometabola. Lepidoptera and Diptera showed additional labeling of two bilateral pairs of neurons of a third type. The presence of serotonin in systems of columnar neurons apparently evolved independently in dragonflies and desert locusts. The data suggest distinct evolutionary changes in the composition of serotonin-immunolabeled neurons of the central complex and provides a promising basis for a phylogenetic study in a wider range of arthropod species.

Flexible locomotion in complex environments: the influence of species, speed and sensory feedback on panarthropod inter-leg coordination

Panarthropods (a clade containing arthropods, tardigrades and onychophorans) can adeptly move across a wide range of challenging terrains and their ability to do so given their relatively simple nervous systems makes them compelling study organisms. Studies of forward walking on flat terrain excitingly point to key features in inter-leg coordination patterns that seem to be 'universally' shared across panarthropods. However, when movement through more complex, naturalistic terrain is considered, variability in coordination patterns - from the intra-individual to inter-species level - becomes more apparent. This variability is likely to be due to the interplay between sensory feedback and local pattern-generating activity, and depends crucially on species, walking speed and behavioral goal. Here, I gather data from the literature of panarthropod walking coordination on both flat ground and across more complex terrain. This Review aims to emphasize the value of: (1) designing experiments with an eye towards studying organisms in natural environments; (2) thoughtfully integrating results from various experimental techniques, such as neurophysiological and biomechanical studies; and (3) ensuring that data is collected and made available from a wider range of species for future comparative analyses.

Behavioural function and development of body-to-limb proportions and active movement ranges in three stick insect species

Overall body proportions and relative limb length are highly characteristic for most insect taxa. In case of the legs, limb length has mostly been discussed with regard to parameters of locomotor performance and, in particular cases, as an adaptation to environmental factors or to the mating system. Here, we compare three species of stick and leaf insects (Phasmatodea) that differ strongly in the length ratio between antennae and walking legs, with the antennae of Medauroidea extradentata being much shorter than its legs, nearly equal length of antennae and legs in Carausius morosus, and considerably longer antennae than front legs in Aretaon asperrimus. We show that that relative limb length is directly related to the near-range exploration effort, with complementary function of the antennae and front legs irrespective of their length ratio. Assuming that these inter-species differences hold for both sexes and all developmental stages, we further explore how relative limb length differs between sexes and how it changes throughout postembryonic development. We show that the pattern of limb-to-body proportions is species-characteristic despite sexual dimorphism, and find that the change in sexual dimorphism is strongest during the last two moults. Finally, we show that antennal growth rate is consistently higher than that of front legs, but differs categorically between the species investigated. Whereas antennal growth rate is constant in Carausius, the antennae grow exponentially in Medauroidea and with a sudden boost during the last moult in Aretaon.

Adaptive load feedback robustly signals force dynamics in robotic model of Carausius morosus stepping

Animals utilize a number of neuronal systems to produce locomotion. One type of sensory organ that contributes in insects is the campaniform sensillum (CS) that measures the load on their legs. Groups of the receptors are found on high stress regions of the leg exoskeleton and they have significant effects in adapting walking behavior. Recording from these sensors in freely moving animals is limited by technical constraints. To better understand the load feedback signaled by CS to the nervous system, we have constructed a dynamically scaled robotic model of the Carausius morosus stick insect middle leg. The leg steps on a treadmill and supports weight during stance to simulate body weight. Strain gauges were mounted in the same positions and orientations as four key CS groups (Groups 3, 4, 6B, and 6A). Continuous data from the strain gauges were processed through a previously published dynamic computational model of CS discharge. Our experiments suggest that under different stepping conditions (e.g., changing "body" weight, phasic load stimuli, slipping foot), the CS sensory discharge robustly signals increases in force, such as at the beginning of stance, and decreases in force, such as at the end of stance or when the foot slips. Such signals would be crucial for an insect or robot to maintain intra- and inter-leg coordination while walking over extreme terrain.

Adaptive Interlimb Coordination Mechanism for Hexapod Locomotion Based on Active Load Sensing

Insects can flexibly coordinate their limbs to adapt to various locomotor conditions, e.g., complex environments, changes in locomotion speed, and leg amputation. An interesting aspect of insect locomotion is that the gait patterns are not necessarily stereotypical but are often highly variable, e.g., searching behavior to obtain stable footholds in complex environments. Several previous studies have focused on the mechanism for the emergence of variable limb coordination patterns. However, the proposed mechanisms are complicated and the essential mechanism underlying insect locomotion remains elusive. To address this issue, we proposed a simple mathematical model for the mechanism of variable interlimb coordination in insect locomotion. The key idea of the proposed model is “decentralized active load sensing,” wherein each limb actively moves and detects the reaction force from the ground to judge whether it plays a pivotal role in maintaining the steady support polygon. Based on active load sensing, each limb stays in the stance phase when the limb is necessary for body support. To evaluate the proposed model, we conducted simulation experiments using a hexapod robot. The results showed that the proposed simple mechanism allows the hexapod robot to exhibit typical gait patterns in response to the locomotion speed. Furthermore, the proposed mechanism improves the adaptability of the hexapod robot for leg amputations and lack of footholds by changing each limb's walking and searching behavior in a decentralized manner based on the physical interaction between the body and the environment.

Interspecies variation of larval locomotion kinematics in the genus Drosophila and its relation to habitat temperature

BACKGROUND

Speed and trajectory of locomotion are the characteristic traits of individual species. Locomotion kinematics may have been shaped during evolution towards increased survival in the habitats of each species. Although kinematics of locomotion is thought to be influenced by habitats, the quantitative relation between the kinematics and environmental factors has not been fully revealed. Here, we performed comparative analyses of larval locomotion in 11 Drosophila species.

RESULTS

We found that larval locomotion kinematics are divergent among the species. The diversity is not correlated to the body length but is correlated instead to the habitat temperature of the species. Phylogenetic analyses using Bayesian inference suggest that the evolutionary rate of the kinematics is diverse among phylogenetic tree branches.

CONCLUSIONS

The results of this study imply that the kinematics of larval locomotion has diverged in the evolutionary history of the genus Drosophila and evolved under the effects of the ambient temperature of habitats.

Evaluation of force feedback in walking using joint torques as "naturalistic" stimuli

Control of adaptive walking requires the integration of sensory signals of muscle force and load. We have studied how mechanoreceptors (tibial campaniform sensilla) encode “naturalistic” stimuli derived from joint torques of stick insects walking on a horizontal substrate. Previous studies showed that forces applied to the legs using the mean torque profiles of a proximal joint were highly effective in eliciting motor activities. However, substantial variations in torque direction and magnitude occurred at the more distal femorotibial joint, which can generate braking or propulsive forces and provide lateral stability. To determine how these forces are encoded, we used torque waveforms of individual steps that had maximum values in stance in the directions of flexion or extension. Analysis of kinematic data showed that the torques in different directions tended to occur in different ranges of joint angles. Variations within stance were not accompanied by comparable changes in joint angle but often reflected vertical ground reaction forces and leg support of body load. Application of torque waveforms elicited sensory discharges with variations in firing frequency similar to those seen in freely walking insects. All sensilla directionally encoded the dynamics of force increases and showed hysteresis to transient force decreases. Smaller receptors exhibited more tonic firing. Our findings suggest that dynamic sensitivity in force feedback can modulate ongoing muscle activities to stabilize distal joints when large forces are generated at proximal joints. Furthermore, use of “naturalistic” stimuli can reproduce characteristics seen in freely moving animals that are absent in conventional restrained preparations.

NEW & NOTEWORTHY Sensory encoding of forces during walking by campaniform sensilla was characterized in stick insects using waveforms of joint torques calculated by inverse dynamics as mechanical stimuli. Tests using the mean joint torque and torques of individual steps showed the system is highly sensitive to force dynamics (dF/dt). Use of “naturalistic” stimuli can reproduce characteristics of sensory discharges seen in freely walking insects, such as load transfer among legs.

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.

Drosophila uses a tripod gait across all walking speeds, and the geometry of the tripod is important for speed control

Changes in walking speed are characterized by changes in both the animal's gait and the mechanics of its interaction with the ground. Here we study these changes in walking Drosophila. We measured the fly's center of mass movement with high spatial resolution and the position of its footprints. Flies predominantly employ a modified tripod gait that only changes marginally with speed. The mechanics of a tripod gait can be approximated with a simple model - angular and radial spring-loaded inverted pendulum (ARSLIP) - which is characterized by two springs of an effective leg that become stiffer as the speed increases. Surprisingly, the change in the stiffness of the spring is mediated by the change in tripod shape rather than a change in stiffness of individual legs. The effect of tripod shape on mechanics can also explain the large variation in kinematics among insects, and ARSLIP can model these variations.

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.

Neurodynamic modeling of the fruit fly Drosophila melanogaster

This manuscript describes neuromechanical modeling of the fruit fly Drosophila melanogaster in the form of a hexapod robot, Drosophibot, and an accompanying dynamic simulation. Drosophibot is a testbed for real-time dynamical neural controllers modeled after the anatomy and function of the insect nervous system. As such, Drosophibot has been designed to capture features of the animal's biomechanics in order to better test the neural controllers. These features include: dynamically scaling the robot to match the fruit fly by designing its joint elasticity and movement speed; a biomimetic actuator control scheme that converts neural activity into motion in the same way as observed in insects; biomimetic sensing, including proprioception from all leg joints and strain sensing from all leg segments; and passively compliant tarsi that mimic the animal's passive compliance to the walking substrate. We incorporated these features into a dynamical simulation of Drosophibot, and demonstrate that its actuators and sensors perform in an animal-like way. We used this simulation to test a neural walking controller based on anatomical and behavioral data from insects. Finally, we describe Drosophibot's hardware and show that the animal-like features of the simulation transfer to the physical robot.

Attachment performance of stick insects (Phasmatodea) on convex substrates

Phasmatodea (stick and leaf insects) are herbivorous insects well camouflaged on plant substrates as a result of cryptic masquerade. Also, their close association with plants has allowed them to adapt to different substrate geometries and surface topographies of the plants they imitate. Stick insects are gaining increasing attention in attachment- and locomotion-focused research. However, most studies experimentally investigating stick insect attachment have been performed either on single attachment pads or on flat surfaces. In contrast, curved surfaces, especially twigs or stems of plants, are dominant substrates for phytophagous insects, but not much is known about the influence of curvature on their attachment. In this study, by combining analysis of tarsal usage with mechanical traction and pull-off force measurements, we investigated the attachment performance on curved substrates with different diameters in two species of stick insects with different tarsal lengths. We provide the first quantitative data for forces generated by stick insects on convex curved substrates and show that the curvature significantly influences attachment ability in both species. Within the studied range of substrate curvatures, traction force decreases and pull-off force increases with increasing curvature. Shorter tarsi demonstrate reduced forces; however, tarsus length only has an influence for diameters thinner than the tarsal length. The attachment force generally depends on the number of tarsi/tarsomeres in contact, tarsus/leg orientation and body posture on the surface. Pull-off force is also influenced by the tibiotarsal angle, with higher pull-off force for lower angles, while traction force is mainly influenced by load, i.e. adduction force.

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.

Complementary effect of attachment devices in stick insects (Phasmatodea)

Stick insects are well adapted in their locomotion to various surfaces and topographies of natural substrates. Single pad measurements characterised the pretarsal arolia of these insects as shear-sensitive adhesive pads and the tarsal euplantulae as load-sensitive friction pads. Different attachment microstructures on the euplantulae reveal an adaptation of smooth euplantulae to smooth surfaces and nubby eupantulae to a broader range of surface roughness. However, how different attachment pads and claws work in concert and how strong the contribution of different structures is to the overall attachment performance remains unclear. We therefore assessed combinatory effects in the attachment system of two stick insect species with different types of euplantular microstructures by analysing their usage in various posture situations and the performance on different levels of substrate roughness. For comparison, we provide attachment force data of the whole attachment system. The combination of claws, arolia and euplantulae provides mechanical interlocking on rough surfaces, adhesion and friction on smooth surfaces in different directions, and facilitates attachment on different inclines and on a broad range of surface roughness, with the least performance in the range 0.3-1.0 µm. On smooth surfaces, stick insects use arolia always, but employ euplantulae if the body weight can generate load on them (upright, wall). On structured surfaces, claws enable mechanical interlocking at roughnesses higher than 12 µm. On less-structured surfaces, the attachment strength depends on the use of pads and, corroborating earlier studies, favours smooth pads on smooth surfaces, but nubby euplantulae on micro-rough surfaces.

Integrative Biomimetics of Autonomous Hexapedal Locomotion

Despite substantial advances in many different fields of neurorobotics in general, and biomimetic robots in particular, a key challenge is the integration of concepts: to collate and combine research on disparate and conceptually disjunct research areas in the neurosciences and engineering sciences. We claim that the development of suitable robotic integration platforms is of particular relevance to make such integration of concepts work in practice. Here, we provide an example for a hexapod robotic integration platform for autonomous locomotion. In a sequence of six focus sections dealing with aspects of intelligent, embodied motor control in insects and multipedal robots—ranging from compliant actuation, distributed proprioception and control of multiple legs, the formation of internal representations to the use of an internal body model—we introduce the walking robot HECTOR as a research platform for integrative biomimetics of hexapedal locomotion. Owing to its 18 highly sensorized, compliant actuators, light-weight exoskeleton, distributed and expandable hardware architecture, and an appropriate dynamic simulation framework, HECTOR offers many opportunities to integrate research effort across biomimetics research on actuation, sensory-motor feedback, inter-leg coordination, and cognitive abilities such as motion planning and learning of its own body size.

Transfer of Spatial Contact Information Among Limbs and the Notion of Peripersonal Space in Insects

Internal representation of far-range space in insects is well established, as it is necessary for navigation behavior. Although it is likely that insects also have an internal representation of near-range space, the behavioral evidence for the latter is much less evident. Here, we estimate the size and shape of the spatial equivalent of a near-range representation that is constituted by somatosensory sampling events. To do so, we use a large set of experimental whole-body motion capture data on unrestrained walking, climbing and searching behavior in stick insects of the species Carausius morosus to delineate ‘action volumes’ and ‘contact volumes’ for both antennae and all six legs. As these volumes are derived from recorded sampling events, they comprise a volume equivalent to a representation of coinciding somatosensory and motor activity. Accordingly, we define this volume as the peripersonal space of an insect. It is of immediate behavioral relevance, because it comprises all potential external object locations within the action range of the body. In a next step, we introduce the notion of an affordance space as that part of peripersonal space within which contact-induced spatial estimates lie within the action ranges of more than one limb. Because the action volumes of limbs overlap in this affordance space, spatial information from one limb can be used to control the movement of another limb. Thus, it gives rise to an affordance as known for contact-induced reaching movements and spatial coordination of footfall patterns in stick insects. Finally, we probe the computational properties of the experimentally derived affordance space for pairs of neighboring legs. This is done by use of artificial neural networks that map the posture of one leg into a target posture of another leg with identical foot position.

Fiber-type distribution in insect leg muscles parallels similarities and differences in the functional role of insect walking legs

Previous studies have demonstrated that myofibrillar ATPase (mATPase) enzyme activity in muscle fibers determines their contraction properties. We analyzed mATPase activities in muscles of the front, middle and hind legs of the orthopteran stick insect (Carausius morosus) to test the hypothesis that differences in muscle fiber types and distributions reflected differences in their behavioral functions. Our data show that all muscles are composed of at least three fiber types, fast, intermediate and slow, and demonstrate that: (1) in the femoral muscles (extensor and flexor tibiae) of all legs, the number of fast fibers decreases from proximal to distal, with a concomitant increase in the number of slow fibers. (2) The swing phase muscles protractor coxae and levator trochanteris, have smaller percentages of slow fibers compared to the antagonist stance muscles retractor coxae and depressor trochanteris. (3) The percentage of slow fibers in the retractor coxae and depressor trochanteris increases significantly from front to hind legs. These results suggest that fiber-type distribution in leg muscles of insects is not identical across leg muscles but tuned towards the specific function of a given muscle in the locomotor system.

Stable phase-shift despite quasi-rhythmic movements: a CPG-driven dynamic model of active tactile exploration in an insect

An essential component of autonomous and flexible behavior in animals is active exploration of the environment, allowing for perception-guided planning and control of actions. An important sensory system involved is active touch. Here, we introduce a general modeling framework of Central Pattern Generators (CPGs) for movement generation in active tactile exploration behavior. The CPG consists of two network levels: (i) phase-coupled Hopf oscillators for rhythm generation, and (ii) pattern formation networks for capturing the frequency and phase characteristics of individual joint oscillations. The model captured the natural, quasi-rhythmic joint kinematics as observed in coordinated antennal movements of walking stick insects. Moreover, it successfully produced tactile exploration behavior on a three-dimensional skeletal model of the insect antennal system with physically realistic parameters. The effect of proprioceptor ablations could be simulated by changing the amplitude and offset parameters of the joint oscillators, only. As in the animal, the movement of both antennal joints was coupled with a stable phase difference, despite the quasi-rhythmicity of the joint angle time courses. We found that the phase-lead of the distal scape-pedicel (SP) joint relative to the proximal head-scape (HS) joint was essential for producing the natural tactile exploration behavior and, thus, for tactile efficiency. For realistic movement patterns, the phase-lead could vary within a limited range of 10–30° only. Tests with artificial movement patterns strongly suggest that this phase sensitivity is not a matter of the frequency composition of the natural movement pattern. Based on our modeling results, we propose that a constant phase difference is coded into the CPG of the antennal motor system and that proprioceptors are acting locally to regulate the joint movement amplitude.