Sensory feedback in cockroach locomotion: current knowledge and open questions

Sensorimotor delays constrain robust locomotion in a 3D kinematic model of fly walking

Walking animals must maintain stability in the presence of external perturbations, despite significant temporal delays in neural signaling and muscle actuation. Here, we develop a 3D kinematic model with a layered control architecture to investigate how sensorimotor delays constrain robustness of walking behavior in the fruit fly, Drosophila. Motivated by the anatomical architecture of insect locomotor control circuits, our model consists of three component layers: a neural network that generates realistic 3D joint kinematics for each leg, an optimal controller that executes the joint kinematics while accounting for delays, and an inter-leg coordinator. The model generates realistic simulated walking that matches real fly walking kinematics and sustains walking even when subjected to unexpected perturbations, generalizing beyond its training data. However, we found that the model's robustness to perturbations deteriorates when sensorimotor delay parameters exceed the physiological range. These results suggest that fly sensorimotor control circuits operate close to the temporal limit at which they can detect and respond to external perturbations. More broadly, we show how a modular, layered model architecture can be used to investigate physiological constraints on animal behavior.

The processing of proprioceptive signals in distributed networks: insights from insect motor control

The integration of sensory information is required to maintain body posture and to generate robust yet flexible locomotion through unpredictable environments. To anticipate required adaptations in limb posture and enable compensation of sudden perturbations, an animal's nervous system assembles external (exteroception) and internal (proprioception) cues. Coherent neuronal representations of the proprioceptive context of the body and the appendages arise from the concerted action of multiple sense organs monitoring body kinetics and kinematics. This multimodal proprioceptive information, together with exteroceptive signals and brain-derived descending motor commands, converges onto premotor networks - i.e. the local neuronal circuitry controlling motor output and movements - within the ventral nerve cord (VNC), the insect equivalent of the vertebrate spinal cord. This Review summarizes existing knowledge and recent advances in understanding how local premotor networks in the VNC use convergent information to generate contextually appropriate activity, focusing on the example of posture control. We compare the role and advantages of distributed sensory processing over dedicated neuronal pathways, and the challenges of multimodal integration in distributed networks. We discuss how the gain of distributed networks may be tuned to enable the behavioral repertoire of these systems, and argue that insect premotor networks might compensate for their limited neuronal population size by, in comparison to vertebrate networks, relying more heavily on the specificity of their connections. At a time in which connectomics and physiological recording techniques enable anatomical and functional circuit dissection at an unprecedented resolution, insect motor systems offer unique opportunities to identify the mechanisms underlying multimodal integration for flexible motor control.

Environmental force sensing helps robots traverse cluttered large obstacles

Robots can traverse sparse obstacles by sensing environmental geometry and avoiding contact with obstacles. However, for search and rescue in rubble, environmental monitoring through dense vegetation, and planetary exploration over Martian and lunar rocks, robots must traverse cluttered obstacles as large as themselves by physically interacting with them. Previous work discovered that the forest floor-dwelling discoid cockroach and a sensor-less minimalistic robot can traverse cluttered grass-like beam obstacles of various stiffness by transitioning across different locomotor modes. Yet the animal was better at traversal than the sensor-less robot, likely by sensing forces during obstacle interaction to control its locomotor transitions. Inspired by this, here we demonstrated in simulation that environmental force sensing helps robots traverse cluttered large obstacles. First, we developed a multi-body dynamics simulation and a physics model of the minimalistic robot interacting with beams to estimate beam stiffness from the sensed contact forces. Then, we developed a force feedback strategy for the robot to use the sensed beam stiffness to choose the locomotor mode with a lower mechanical energy cost. With feedforward pushing, the robot was stuck in front of stiff beams if it has a limited force capacity; without force limit, it traversed but suffered a high energy cost. Using obstacle avoidance, the robot traversed beams by avoiding beam contact regardless of beam stiffness, resulting in a high energy cost for flimsy beams. With force feedback, the robot determined beam stiffness, then traversed flimsy beams by pushing them over and stiff beams by rolling through the gap between them with a low energy cost. Stiffness estimation based on force sensing was accurate across varied body oscillation amplitude and frequency and position sensing uncertainty. Mechanical energy cost of traversal increased with sensorimotor delay. Future work should demonstrate cluttered large obstacle traversal using force feedback in a physical robot.

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.

An insect-scale robot reveals the effects of different body dynamics regimes during open-loop running in feature-laden terrain

The transition from the lab to natural environments is an archetypal challenge in robotics. While larger robots can manage complex limb-ground interactions using sensing and control, such strategies are difficult to implement on small platforms where space and power are limited. The Harvard Ambulatory Microrobot (HAMR) is an insect-scale quadruped capable of effective open-loop running on featureless, hard substrates. Inspired by the predominantly feedforward strategy of rapidly-running cockroaches on uneven terrain (Sponberg, 2007), we used HAMR to explore open-loop running on two 3D printed heterogeneous terrains generated using fractional Brownian motion. The 'pocked' terrain had foot-scale features throughout while the 'jagged' terrain features increased in height in the direction of travel. We measured the performance of trot and pronk gaits while varying limb amplitude and stride frequency. The frequencies tested encompassed different dynamics regimes: body resonance (10-25 Hz) and kinematic running (30-40 Hz), with dynamics typical of biological running and walking, respectively, and limb-transmission resonance (45-60 Hz). On the featureless and pocked terrains, low mechanical cost-of-transport (mCoT) kinematic running combinations performed best without systematic differences between trot and pronk; indicating that if terrain features are not too tall, a robot can transition from homo-to heterogeneous environments in open-loop. Pronk bypassed taller features than trot on the jagged terrain, and higher mCoT, lower frequency running was more often effective. While increasing input power to the robot improved performance in general, lower frequency pronking on jagged terrain allowed the robot to bypass taller features compared with the same input power at higher frequencies. This was correlated with the increased variation in center-of-mass orientation occurring at frequencies near body resonance. This study established that appropriate choice of robot dynamics, as mediated by gait, frequency, and limb amplitude, can expand the terrains accessible to microrobots without the addition of sensing or closed-loop control.

PaOctβ2R: Identification and Functional Characterization of an Octopamine Receptor Activating Adenylyl Cyclase Activity in the American Cockroach Periplaneta americana

Biogenic amines constitute an important group of neuroactive substances that control and modulate various neural circuits. These small organic compounds engage members of the guanine nucleotide-binding protein coupled receptor (GPCR) superfamily to evoke specific cellular responses. In addition to dopamine- and 5-hydroxytryptamine (serotonin) receptors, arthropods express receptors that are activated exclusively by tyramine and octopamine. These phenolamines functionally substitute the noradrenergic system of vertebrates Octopamine receptors that are the focus of this study are classified as either α- or β-adrenergic-like. Knowledge on these receptors is scarce for the American cockroach (Periplaneta americana). So far, only an α–adrenergic-like octopamine receptor that primarily causes Ca²⁺ release from intracellular stores has been studied from the cockroach (PaOctα1R). Here we succeeded in cloning a gene from cockroach brain tissue that encodes a β-adrenergic-like receptor and leads to cAMP production upon activation. Notably, the receptor is 100-fold more selective for octopamine than for tyramine. A series of synthetic antagonists selectively block receptor activity with epinastine being the most potent. Bioinformatics allowed us to identify a total of 19 receptor sequences that build the framework of the biogenic amine receptor clade in the American cockroach. Phylogenetic analyses using these sequences and receptor sequences from model organisms showed that the newly cloned gene is an β2-adrenergic-like octopamine receptor. The functional characterization of PaOctβ2R and the bioinformatics data uncovered that the monoaminergic receptor family in the hemimetabolic P. americana is similarly complex as in holometabolic model insects like Drosophila melanogaster and the honeybee, Apis mellifera. Thus, investigating these receptors in detail may contribute to a better understanding of monoaminergic signaling in insect behavior and physiology.

Extracting temporal relationships between weakly coupled peptidergic and motoneuronal signaling: Application to Drosophila ecdysis behavior

Neuromodulators, such as neuropeptides, can regulate and reconfigure neural circuits to alter their output, affecting in this way animal physiology and behavior. The interplay between the activity of neuronal circuits, their modulation by neuropeptides, and the resulting behavior, is still poorly understood. Here, we present a quantitative framework to study the relationships between the temporal pattern of activity of peptidergic neurons and of motoneurons during Drosophila ecdysis behavior, a highly stereotyped motor sequence that is critical for insect growth. We analyzed, in the time and frequency domains, simultaneous intracellular calcium recordings of peptidergic CCAP (crustacean cardioactive peptide) neurons and motoneurons obtained from isolated central nervous systems throughout fictive ecdysis behavior induced ex vivo by Ecdysis triggering hormone. We found that the activity of both neuronal populations is tightly coupled in a cross-frequency manner, suggesting that CCAP neurons modulate the frequency of motoneuron firing. To explore this idea further, we used a probabilistic logistic model to show that calcium dynamics in CCAP neurons can predict the oscillation of motoneurons, both in a simple model and in a conductance-based model capable of simulating many features of the observed neural dynamics. Finally, we developed an algorithm to quantify the motor behavior observed in videos of pupal ecdysis, and compared their features to the patterns of neuronal calcium activity recorded ex vivo. We found that the motor activity of the intact animal is more regular than the motoneuronal activity recorded from ex vivo preparations during fictive ecdysis behavior; the analysis of the patterns of movement also allowed us to identify a new post-ecdysis phase.

From Motor-Output to Connectivity: An In-Depth Study of in-vitro Rhythmic Patterns in the Cockroach Periplaneta americana

The cockroach is an established model in the study of locomotion control. While previous work has offered important insights into the interplay among brain commands, thoracic central pattern generators, and the sensory feedback that shapes their motor output, there remains a need for a detailed description of the central pattern generators' motor output and their underlying connectivity scheme. To this end, we monitored pilocarpine-induced activity of levator and depressor motoneurons in two types of novel in-vitro cockroach preparations: isolated thoracic ganglia and a whole-chain preparation comprising the thoracic ganglia and the subesophageal ganglion. Our data analyses focused on the motoneuron firing patterns and the coordination among motoneuron types in the network. The burstiness and rhythmicity of the motoneurons were monitored, and phase relations, coherence, coupling strength, and frequency-dependent variability were analyzed. These parameters were all measured and compared among network units both within each preparation and among the preparations. Here, we report differences among the isolated ganglia, including asymmetries in phase and coupling strength, which indicate that they are wired to serve different functions. We also describe the intrinsic default gait and a frequency-dependent coordination. The depressor motoneurons showed mostly similar characteristics throughout the network regardless of interganglia connectivity; whereas the characteristics of the levator motoneurons activity were mostly ganglion-dependent, and influenced by the presence of interganglia connectivity. Asymmetries were also found between the anterior and posterior homolog parts of the thoracic network, as well as between ascending and descending connections. Our analyses further discover a frequency-dependent inversion of the interganglia coordination from alternations between ipsilateral homolog oscillators to simultaneous activity. We present a detailed scheme of the network couplings, formulate coupling rules, and review a previously suggested model of connectivity in light of our new findings. Our data support the notion that the inter-hemiganglia coordination derives from the levator networks and their coupling with local depressor interneurons. Our findings also support a dominant role of the metathoracic ganglion and its ascending output in governing the anterior ganglia motor output during locomotion in the behaving animal.

Leg amputation modifies coordinated activation of the middle leg muscles in the cricket Gryllus bimaculatus

Insects alter their walking pattern in order to respond to demands of an ever-changing environment, such as varying ground surface textures. They also exhibit resilient and flexible ability to retain the capacity to walk even after substantial changes in their body properties, e.g. leg amputation. While the motor control paradigm governing the inter-leg coordination in such adaptive walking has been extensively described in past studies, the mechanism remains unknown. Here, we examined this question by using the cricket (Gryllus bimaculatus), which shows a tetrapod/tripod gait on a flat surfaces, like many other insects. We performed leg amputation experiments to investigate modifications of leg movements and coordination of muscle activities. We simultaneously recorded (1) the leg movements, locomotion velocity, and body rotation and (2) the leg movements and leg muscles activities before and after leg amputation. Crickets displayed adaptive coordination of leg movement patterns in response to amputations. The activation timings of levator muscles in both middle legs tended to synchronize in phase when both legs were amputated at the coxatrochanteral joint. This supports the hypothesis that an intrinsic contralateral connection within the mesothoracic ganglion exists, and that mechanosensory feedback from the legs override this connection, resulting in the anti-phase movement of a normal gait.

Uneven substrates constrain walking speed in ants through modulation of stride frequency more than stride length

Natural terrain is rarely flat. Substrate irregularities challenge walking animals to maintain stability, yet we lack quantitative assessments of walking performance and limb kinematics on naturally uneven ground. We measured how continually uneven 3D-printed substrates influence walking performance of Argentine ants by measuring walking speeds of workers from laboratory colonies and by testing colony-wide substrate preference in field experiments. Tracking limb motion in over 8000 videos, we used statistical models that associate walking speed with limb kinematic parameters to compare movement over flat versus uneven ground of controlled dimensions. We found that uneven substrates reduced preferred and peak walking speeds by up to 42% and that ants actively avoided uneven terrain in the field. Observed speed reductions were modulated primarily by shifts in stride frequency instead of stride length (flat R 2: 0.91 versus 0.50), a pattern consistent across flat and uneven substrates. Mixed effect modelling revealed that walking speeds on uneven substrates were accurately predicted based on flat walking data for over 89% of strides. Those strides that were not well modelled primarily involved limb perturbations, including missteps, active foot repositioning and slipping. Together these findings relate kinematic mechanisms underlying walking performance on uneven terrain to ecologically relevant measures under field conditions.

Motor control of an insect leg during level and incline walking

During walking, the leg motor system must continually adjust to changes in mechanical conditions, such as the inclination of the ground. To understand the underlying control, it is important to know how changes in leg muscle activity relate to leg kinematics (movements) and leg dynamics (forces, torques). Here, we studied these parameters in hindlegs of stick insects (Carausius morosus) during level and uphill/downhill (±45 deg) walking, using a combination of electromyography, 3D motion capture and ground reaction force measurements. We find that some kinematic parameters including leg joint angles and body height vary across walking conditions. However, kinematics vary little compared with dynamics: horizontal leg forces and torques at the thorax-coxa joint (leg protraction/retraction) and femur-tibia joint (leg flexion/extension) tend to be stronger during uphill walking and are reversed in sign during downhill walking. At the thorax-coxa joint, the different mechanical demands are met by adjustments in the timing and magnitude of antagonistic muscle activity. Adjustments occur primarily in the first half of stance after the touch-down of the leg. When insects transition from level to incline walking, the characteristic adjustments in muscle activity occur with the first step of the leg on the incline, but not in anticipation. Together, these findings indicate that stick insects adjust leg muscle activity on a step-by-step basis so as to maintain a similar kinematic pattern under different mechanical demands. The underlying control might rely primarily on feedback from leg proprioceptors signaling leg position and movement.

A kinematic model of stick-insect walking

Animal, and insect walking (locomotion) in particular, have attracted much attention from scientists over many years up to now. The investigations included behavioral, electrophysiological experiments, as well as modeling studies. Despite the large amount of material collected, there are left many unanswered questions as to how walking and related activities are generated, maintained, and controlled. It is obvious that for them to take place, precise coordination within muscle groups of one leg and between the legs is required: intra- and interleg coordination. The nature, the details, and the interactions of these coordination mechanisms are not entirely clear. To help uncover them, we made use of modeling techniques, and succeeded in developing a six-leg model of stick-insect walking. Our main goal was to prove that the same model can mimic a variety of walking-related behavioral modes, as well as the most common coordination patterns of walking just by changing the values of a few input or internal variables. As a result, the model can reproduce the basic coordination patterns of walking: tetrapod and tripod and the transition between them. It can also mimic stop and restart, change from forward-to-backward walking and back. Finally, it can exhibit so-called search movements of the front legs both while walking or standing still. The mechanisms of the model that enable it to produce the aforementioned behavioral modes can hint at and prove helpful in uncovering further details of the biological mechanisms underlying walking.

The Metastability of the Double-Tripod Gait in Locust Locomotion

Insect locomotion represents a fundamental example of neuronal oscillating circuits generating different motor patterns or gaits by controlling their phase coordination. Walking gaits are assumed to represent stable states of the system, often modeled as coupled oscillators. This view is challenged, however, by recent experimental observations, in which in vitro locust preparations consistently converged to synchronous rhythms (all legs oscillating as one), a locomotive pattern never seen in vivo. To reconcile this inconsistency, we developed a modeling framework to capture the trade-off between the two competing mechanisms: the endogenous neuronal circuitry, expressed in vitro, and the feedback mechanisms from sensory and descending inputs, active only in vivo. We show that the ubiquitously observed double-tripod walking gait emerges precisely from this balance. The outcome is a short-lived meta-stable double-tripod gait, which transitions and alternates with stable idling, thus recovering the observed intermittent bouts of locomotion, typical of many insects' locomotion behavior.

•

Isolated in vitro locust preparations indicate that idling is a stable fictive gait

•

This is in contrast to the dominant in vivo locomotive pattern (i.e., double tripod)

•

Hence functional locomotion behavior is dependent on descending and sensory inputs

•

The presented model generates intermittent double-tripod bouts as seen empirically

The functional connectivity between the locust leg pattern generators and the subesophageal ganglion higher motor center

Higher motor centers and central pattern generators (CPGs) interact in the control of coordinated leg movements during locomotion throughout the animal kingdom. The subesophageal ganglion (SEG) is one of the insect head ganglia reported to have a role in the control of walking behavior. Here we explored the functional relations between the SEG and the thoracic leg CPGs in the desert locust. Backfill staining revealed about 300 SEG descending interneurons (DINs) altogether. Recordings from an in-vitro isolated chain of thoracic ganglia, with intact or severed connections to the SEG, during pharmacological activation were used to determine how the SEG affects the centrally generated motor output to the legs. The SEG was demonstrated to both activate leg CPGs and synchronize their bilateral activity. The role of the SEG in insect locomotion is discussed in light of these findings.

The use of MEMRI for monitoring central nervous system activity during intact insect walking

BACKGROUND

Monitoring neuronal activity in the intact behaving animal is most desired in neuroethological research, yet it is rarely straightforward or even feasible. Here we present the use of manganese enhanced magnetic resonance imaging (MEMRI), a technique allowing monitoring the activity of an animal's nervous system during specific behavioral patterns. Using MEMRI we were able to show activity in different ganglia of the central nervous system of intact locusts during walking.

RESULTS

We injected two groups of locusts with manganese, which serves as a magnetic contrast agent. One group was forced to walk on a treadmill for two hours, while the other was immobilized and served as a control. Subsequently, all animals were scanned in a T1 MRI protocol, and the accumulation of manganese in the neuronal tissues that were active during walking was demonstrated by comparing the scans of the two groups. Two neuronal sites showed significantly higher T1 signal in the walking locusts compared to the immobilized ones: the prothoracic ganglion, which locally controls the front legs, and the subesophageal ganglion, a head ganglion which takes part in initiation and maintenance of walking.

CONCLUSION

MEMRI is a potent, non-invasive technique for monitoring neuronal activity in intact locusts, and arthropods in general. Specifically, it provides a promising way for revealing the role of central and high-order neuronal structures in motor behaviors such as walking.

The subesophageal ganglion modulates locust inter-leg sensory-motor interactions via contralateral pathways

The neural control of insect locomotion is distributed among various body segments. Local pattern-generating circuits at the thoracic ganglia interact with incoming sensory signals and central descending commands from the head ganglia. The evidence from different insect preparations suggests that the subesophageal ganglion (SEG) may play an important role in locomotion-related tasks. In a previous study, we demonstrated that the locust SEG modulates the coupling pattern between segmental leg CPGs in the absence of sensory feedback. Here, we investigated its role in processing and transmitting sensory information to the leg motor centers and mapped the major related neural pathways. Specifically, the intra- and inter-segmental transfer of leg-feedback were studied by simultaneously monitoring motor responses and descending signals from the SEG. Our findings reveal a crucial role of the SEG in the transfer of intersegmental, but not intrasegmental, signals. Additional lesion experiments, in which the intersegmental connectives were cut at different locations, together with double nerve staining, indicated that sensory signals are mainly transferred to the SEG via the connective contralateral to the stimulated leg. We therefore suggest that, similar to data reported for vertebrates, insect leg sensory-motor loops comprise contralateral ascending pathways to the head and ipsilateral descending ones.

The role of phase shifts of sensory inputs in walking revealed by means of phase reduction

Detailed neural network models of animal locomotion are important means to understand the underlying mechanisms that control the coordinated movement of individual limbs. Daun-Gruhn and Tóth, Journal of Computational Neuroscience 31(2), 43-60 (2011) constructed an inter-segmental network model of stick insect locomotion consisting of three interconnected central pattern generators (CPGs) that are associated with the protraction-retraction movements of the front, middle and hind leg. This model could reproduce the basic locomotion coordination patterns, such as tri- and tetrapod, and the transitions between them. However, the analysis of such a system is a formidable task because of its large number of variables and parameters. In this study, we employed phase reduction and averaging theory to this large network model in order to reduce it to a system of coupled phase oscillators. This enabled us to analyze the complex behavior of the system in a reduced parameter space. In this paper, we show that the reduced model reproduces the results of the original model. By analyzing the interaction of just two coupled phase oscillators, we found that the neighboring CPGs could operate within distinct regimes, depending on the phase shift between the sensory inputs from the extremities and the phases of the individual CPGs. We demonstrate that this dependence is essential to produce different coordination patterns and the transition between them. Additionally, applying averaging theory to the system of all three phase oscillators, we calculate the stable fixed points - they correspond to stable tripod or tetrapod coordination patterns and identify two ways of transition between them.

Rigidity and Flexibility: The Central Basis of Inter-Leg Coordination in the Locust

Many motor behaviors, and specifically locomotion, are the product of an intricate interplay between neuronal oscillators known as central pattern generators (CPGs), descending central commands, and sensory feedback loops. The relative contribution of each of these components to the final behavior determines the trade-off between fixed movements and those that are carefully adapted to the environment. Here we sought to decipher the endogenous, default, motor output of the CPG network controlling the locust legs, in the absence of any sensory or descending influences. We induced rhythmic activity in the leg CPGs in isolated nervous system preparations, using different application procedures of the muscarinic agonist pilocarpine. We found that the three thoracic ganglia, each controlling a pair of legs, have different inherent bilateral coupling. Furthermore, we found that the pharmacological activation of one ganglion is sufficient to induce activity in the other, untreated, ganglia. Each ganglion was thus capable to impart its own bilateral inherent pattern onto the other ganglia via a tight synchrony among the ipsilateral CPGs. By cutting a connective and severing the lateral-longitudinal connections, we were able to uncouple the oscillators’ activity. While the bilateral connections demonstrated a high modularity, the ipsilateral CPGs maintained a strict synchronized activity. These findings suggest that the central infrastructure behind locust walking features both rigid elements, which presumably support the generation of stereotypic orchestrated leg movements, and flexible elements, which might provide the central basis for adaptations to the environment and to higher motor commands.

Mechanosensation and Adaptive Motor Control in Insects

The ability of animals to flexibly navigate through complex environments depends on the integration of sensory information with motor commands. The sensory modality most tightly linked to motor control is mechanosensation. Adaptive motor control depends critically on an animal's ability to respond to mechanical forces generated both within and outside the body. The compact neural circuits of insects provide appealing systems to investigate how mechanical cues guide locomotion in rugged environments. Here, we review our current understanding of mechanosensation in insects and its role in adaptive motor control. We first examine the detection and encoding of mechanical forces by primary mechanoreceptor neurons. We then discuss how central circuits integrate and transform mechanosensory information to guide locomotion. Because most studies in this field have been performed in locusts, cockroaches, crickets, and stick insects, the examples we cite here are drawn mainly from these 'big insects'. However, we also pay particular attention to the tiny fruit fly, Drosophila, where new tools are creating new opportunities, particularly for understanding central circuits. Our aim is to show how studies of big insects have yielded fundamental insights relevant to mechanosensation in all animals, and also to point out how the Drosophila toolkit can contribute to future progress in understanding mechanosensory processing.

Endogenous rhythm and pattern-generating circuit interactions in cockroach motor centres

Cockroaches are rapid and stable runners whose gaits emerge from the intricate, and not fully resolved, interplay between endogenous oscillatory pattern-generating networks and sensory feedback that shapes their rhythmic output. Here we studied the endogenous motor output of a brainless, deafferented preparation. We monitored the pilocarpine-induced rhythmic activity of levator and depressor motor neurons in the mesothoracic and metathoracic segments in order to reveal the oscillatory networks’ architecture and interactions. Data analyses included phase relations, latencies between and overlaps of rhythmic bursts, spike frequencies, and the dependence of these parameters on cycle frequency. We found that, overall, ipsilateral connections are stronger than contralateral ones. Our findings revealed asymmetries in connectivity among the different ganglia, in which meta-to-mesothoracic ascending coupling is stronger than meso-to-metathoracic descending coupling. Within-ganglion coupling between the metathoracic hemiganglia is stronger than that in the mesothoracic ganglion. We also report differences in the role and mode of operation of homologue network units (manifested by levator and depressor nerve activity). Many observed characteristics are similar to those exhibited by intact animals, suggesting a dominant role for feedforward control in cockroach locomotion. Based on these data we posit a connectivity scheme among components of the locomotion pattern generating system.

Summary: Detailed analysis of fictive motor patterns unveils endogenous characteristics of the cockroach thoracic locomotion control networks and their interrelations and enables an explanatory connectivity model.

Differential control of temporal and spatial aspects of cockroach leg coordination

Ensembles of neuronal networks and sensory pathways participate in controlling the kinematic and dynamic parameters of animal movement necessary to achieve motor coordination. Determining the relative contribution of proprioceptive feedback is essential for understanding how animals sustain stable, coordinated locomotion in complex natural environments. Here, we focus on the role of chordotonal organs (COs), proprioceptors found in insect legs, in the spatial and temporal regulation of walking. We compare gait parameters of intact cockroaches (Periplaneta americana) and sensory-impaired ones, injected with pymetrozine, a chemical previously shown to abolish CO function in locusts. We verify that afferent CO activity in pymetrozine-treated cockroaches is inhibited, and analyze the effect of this sensory deprivation on inter-leg coordination. We find significant changes in tarsi placement and leg path trajectories after pymetrozine treatment. Leg touchdown accuracy, measured from relative tarsi positions of adjacent legs, is reduced in treated animals. Interestingly, despite poorer spatial coordination in both stance and swing, temporal properties of the gait remain largely the same as in the intact preparations, apart from changes in ipsilateral phase differences between front and middle legs. These findings provide insights into the role of COs in insect gait control and establish pymetrozine as a useful tool for further studies of insect locomotion.

Intersegmental coupling and recovery from perturbations in freely running cockroaches

Cockroaches are remarkably stable runners, exhibiting rapid recovery from external perturbations. To uncover the mechanisms behind this important behavioral trait, we recorded leg kinematics of freely running animals in both undisturbed and perturbed trials. Functional coupling underlying inter-leg coordination was monitored before and during localized perturbations, which were applied to single legs via magnetic impulses. The resulting transient effects on all legs and the recovery times to normal pre-perturbation kinematics were studied. We estimated coupling architecture and strength by fitting experimental data to a six-leg-unit phase oscillator model. Using maximum-likelihood techniques, we found that a network with nearest-neighbor inter-leg coupling best fitted the data and that, although coupling strengths vary among preparations, the overall inputs entering each leg are approximately balanced and consistent. Simulations of models with different coupling strengths encountering perturbations suggest that the coupling schemes estimated from our experiments allow animals relatively fast and uniform recoveries from perturbations.