Deciding which way to go: how do insects alter movements to negotiate barriers?

Mechanosensory bristles mediate avoidance behavior by triggering sustained local motor activity in Drosophila melanogaster

During locomotion, most vertebrates-and invertebrates such as Drosophila melanogaster-are able to quickly adapt to terrain irregularities or avoid physical threats by integrating sensory information along with motor commands. Key to this adaptability are leg mechanosensory structures, which assist in motor coordination by transmitting external cues and proprioceptive information to motor centers in the central nervous system. Nevertheless, how different mechanosensory structures engage these locomotor centers remains poorly understood. Here, we tested the role of mechanosensory structures in movement initiation by optogenetically stimulating specific classes of leg sensory structures. We found that stimulation of leg mechanosensory bristles (MsBs) and the femoral chordotonal organ (ChO) is sufficient to initiate forward movement in immobile animals. While the stimulation of the ChO required brain centers to induce forward movement, unexpectedly, brief stimulation of leg MsBs triggered a fast response and sustained motor activity dependent only on the ventral nerve cord (VNC). Moreover, this leg-MsB-mediated movement lacked inter- and intra-leg coordination but preserved antagonistic muscle activity within joints. Finally, we show that leg-MsB activation mediates strong avoidance behavior away from the stimulus source, which is preserved even in the absence of a central brain. Overall, our data show that mechanosensory stimulation can elicit a fast motor response, independently of central brain commands, to evade potentially harmful stimuli. In addition, it sheds light on how specific sensory circuits modulate motor control, including initiation of movement, allowing a better understanding of how different levels of coordination are controlled by the VNC and central brain locomotor circuits.

Neuroarchitecture of the central complex in the Madeira cockroach Rhyparobia maderae: Pontine and columnar neuronal cell types

Insects have evolved remarkable abilities to navigate over short distances and during long-range seasonal migrations. The central complex (CX) is a navigation center in the insect brain that controls spatial orientation and directed locomotion. It is composed of the protocerebral bridge (PB), the upper (CBU) and lower (CBL) division of the central body, and a pair of noduli. While most of its functional organization and involvement in head-direction coding has been obtained from work on flies, bees, and locusts that largely rely on vision for navigation, little contribution has been provided by work on nocturnal species. To close this gap, we have investigated the columnar organization of the CX in the cockroach Rhyparobia maderae. Rhyparobia maderae is a highly agile nocturnal insect that relies largely but not exclusively on antennal information for navigation. A particular feature of the cockroach CX is an organization of the CBU and CBL into interleaved series of eight and nine columns. Single-cell tracer injections combined with imaging and 3D analysis revealed five systems of pontine neurons connecting columns along the vertical and horizontal axis and 18 systems of columnar neurons with topographically organized projection patterns. Among these are six types of neurons with no correspondence in other species. Many neurons send processes into the anterior lip, a brain area highly reduced in bees and unknown in flies. While sharing many features with the CX in other species, the cockroach CX shows some unique attributes that may be related to the ecological niche of this insect.

The bumpy road ahead: the role of substrate roughness on animal walking and a proposed comparative metric

Outside laboratory conditions and human-made structures, animals rarely encounter flat surfaces. Instead, natural substrates are uneven surfaces with height variation that ranges from the microscopic scale to the macroscopic scale. For walking animals (which we define as encompassing any form of legged movement across the ground, such as walking, running, galloping, etc.), such substrate 'roughness' influences locomotion in a multitude of ways across scales, from roughness that influences how each toe or foot contacts the ground, to larger obstacles that animals must move over or navigate around. Historically, the unpredictability and variability of natural environments has limited the ability to collect data on animal walking biomechanics. However, recent technical advances, such as more sensitive and portable cameras, biologgers, laboratory tools to fabricate rough terrain, as well as the ability to efficiently store and analyze large variable datasets, have expanded the opportunity to study how animals move under naturalistic conditions. As more researchers endeavor to assess walking over rough terrain, we lack a consistent approach to quantifying roughness and contextualizing these findings. This Review summarizes existing literature that examines non-human animals walking on rough terrain and presents a metric for characterizing the relative substrate roughness compared with animal size. This framework can be applied across terrain and body scales, facilitating direct comparisons of walking over rough surfaces in animals ranging in size from ants to elephants.

Physiological Signatures of Changes in Honeybee's Central Complex During Wing Flapping

Many kinds of locomotion abilities of insects-including flight control, spatial orientation memory, position memory, angle information integration, and polarized light guidance are considered to be related to the central complex. However, evidence was still not sufficient to support those conclusions from the aspect of neural basis. For the locomotion form of wing flapping, little is known about the patterns of changes in brain activity of the central complex during movement. Here, we analyze the changes in honeybees' neuronal population firing activity of central complex and optic lobes with the perspectives of energy and nonlinear changes. Although the specific function of the central complex remains unknown, evidence suggests that its neural activities change remarkably during wing flapping and its delta rhythm is dominative. Together, our data reveal that the firing activity of some of the neuronal populations of the optic lobe shows reduction in complexity during wing flapping. Elucidating the brain activity changes during a flapping period of insects promotes our understanding of the neuro-mechanisms of insect locomotor control, thus can inspire the fine control of insect cyborgs.

3D-atlas of the brain of the cockroach Rhyparobia maderae

The Madeira cockroach Rhyparobia maderae is a nocturnal insect and a prominent model organism for the study of circadian rhythms. Its master circadian clock, controlling circadian locomotor activity and sleep-wake cycles, is located in the accessory medulla of the optic lobe. For a better understanding of brain regions controlled by the circadian clock and brain organization of this insect in general, we created a three-dimensional (3D) reconstruction of all neuropils of the cerebral ganglia based on anti-synapsin and anti-γ-aminobutyric acid immunolabeling of whole mount brains. Forty-nine major neuropils were identified and three-dimensionally reconstructed. Single-cell dye fills complement the data and provide evidence for distinct subdivisions of certain brain areas. Most neuropils defined in the fruit fly Drosophila melanogaster could be distinguished in the cockroach as well. However, some neuropils identified in the fruit fly do not exist as distinct entities in the cockroach while others are lacking in the fruit fly. In addition to neuropils, major fiber systems, tracts, and commissures were reconstructed and served as important landmarks separating brain areas. Being a nocturnal insect, R. maderae is an important new species to the growing collection of 3D insect brain atlases and only the second hemimetabolous insect, for which a detailed 3D brain atlas is available. This atlas will be highly valuable for an evolutionary comparison of insect brain organization and will greatly facilitate addressing brain areas that are supervised by the circadian clock.

Cockroaches adjust body and appendages to traverse cluttered large obstacles

To traverse complex terrain, animals often transition between locomotor modes. It is well-known that locomotor transitions can be induced by switching in neural control circuits or driven by a need to minimize metabolic energetic cost. Recent work discovered that locomotor transitions in complex 3-D terrain cluttered with large obstacles can emerge from physical interaction with the environment controlled by the nervous system. For example, to traverse cluttered, stiff grass-like beams, the discoid cockroach often transitions from using a strenuous pitch mode pushing across to using a less strenuous roll mode rolling into and through the gaps, and this transition requires overcoming a potential energy barrier. Previous robotic physical modeling demonstrated that kinetic energy fluctuation of body oscillation from self-propulsion can help overcome the barrier and facilitate this transition. However, the animal was observed to transition even when the barrier still exceeded kinetic energy fluctuation. Here, we further studied whether and how the cockroach makes active adjustments to facilitate this transition to traverse cluttered beams. The animal repeatedly flexed its head and abdomen, reduced hind leg sprawl, and depressed one hind leg and elevated the other during the pitch-to-roll transition, which were absent when running on a flat ground. Using a refined potential energy landscape with additional degrees of freedom to model these adjustments, we found that head flexion did not substantially reduce the transition barrier, whereas leg sprawl reduction did so dramatically. We speculate that head flexion is for sensing the terrain to guide the transition via sensory feedback control.

Active tactile exploration and tactually induced turning in tethered walking stick insects

Many animals use their tactile sense for active exploration and tactually guided behaviors like near-range orientation. In insects, tactile sensing is often intimately linked to locomotion, resulting in the orchestration of several concurrent active movements, including turning of the entire body, rotation of the head, and searching or sampling movements of the antennae. The present study aims at linking the sequence of tactile contact events to associated changes of all three kinds of these active movements (body, head and antennae). To do so, we chose the Indian stick insect Carausius morosus, a common organism to study sensory control of locomotion. Methodologically, we combined recordings of walking speed, heading, whole-body kinematics and antennal contact sequences during stationary, tethered walking and controlled presentation of an "artificial twig" for tactile exploration. Our results show that object presentation episodes as brief as five seconds are sufficient to allow for a systematic investigation of tactually-induced turning behavior in walking stick insects. Animals began antennating the artificial twig within 0.5 s. and altered the beating-fields of both antennae in a position-dependent manner. This change was mainly carried by a systematic shift of the head-scape joint movement and accompanied by associated changes in contact likelihood, contact location and sampling direction of the antennae. The turning tendency of the insect also depended on stimulus position, whereas the active, rhythmic head rotation remained un-affected by stimulus presentation. We conclude that the azimuth of contact location is a key parameter of active tactile exploration and tactually-induced turning in stick insects.

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

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

Propelling and perturbing appendages together facilitate strenuous ground self-righting

Terrestrial animals must self-right when overturned on the ground, but this locomotor task is strenuous. To do so, the discoid cockroach often pushes its wings against the ground to begin a somersault which rarely succeeds. As it repeatedly attempts this, the animal probabilistically rolls to the side to self-right. During winged self-righting, the animal flails its legs vigorously. Here, we studied whether wing opening and leg flailing together facilitate strenuous ground self-righting. Adding mass to increase hind leg flailing kinetic energy increased the animal's self-righting probability. We then developed a robot with similar strenuous self-righting behavior and used it as a physical model for systematic experiments. The robot's self-righting probability increased with wing opening and leg flailing amplitudes. A potential energy landscape model revealed that, although wing opening did not generate sufficient kinetic energy to overcome the high pitch potential energy barrier to somersault, it reduced the barrier for rolling, facilitating the small kinetic energy from leg flailing to probabilistically overcome it to self-right. The model also revealed that the stereotyped body motion during self-righting emerged from physical interaction of the body and appendages with the ground. Our work demonstrated the usefulness of potential energy landscape for modeling self-righting transitions.

Neuropeptides as potential modulators of behavioral transitions in the ant Cataglyphis nodus

Age-related behavioral plasticity is a major prerequisite for the ecological success of insect societies. Although ecological aspects of behavioral flexibility have been targeted in many studies, the underlying intrinsic mechanisms controlling the diverse changes in behavior along the individual life history of social insects are not completely understood. Recently, the neuropeptides allatostatin-A, corazonin, and tachykinin have been associated with the regulation of behavioral transitions in social insects. Here, we investigated changes in brain localization and expression of these neuropeptides following major behavioral transitions in Cataglyphis nodus ants. Our immunohistochemical analyses in the brain revealed that the overall branching pattern of neurons immunoreactive (ir) for the three neuropeptides is largely independent of the behavioral stages. Numerous allatostatin-A- and tachykinin-ir neurons innervate primary sensory neuropils and high-order integration centers of the brain. In contrast, the number of corazonergic neurons is restricted to only four neurons per brain hemisphere with cell bodies located in the pars lateralis and axons extending to the medial protocerebrum and the retrocerebral complex. Most interestingly, the cell-body volumes of these neurons are significantly increased in foragers compared to freshly eclosed ants and interior workers. Quantification of mRNA expression levels revealed a stage-related change in the expression of allatostatin-A and corazonin mRNA in the brain. Given the presence of the neuropeptides in major control centers of the brain and the neurohemal organs, these mRNA-changes strongly suggest an important modulatory role of both neuropeptides in the behavioral maturation of Cataglyphis ants.

Neural Design Principles for Subjective Experience: Implications for Insects

How subjective experience is realized in nervous systems remains one of the great challenges in the natural sciences. An answer to this question should resolve debate about which animals are capable of subjective experience. We contend that subjective experience of sensory stimuli is dependent on the brain's awareness of its internal neural processing of these stimuli. This premise is supported by empirical evidence demonstrating that disruption to either processing streams or awareness states perturb subjective experience. Given that the brain must predict the nature of sensory stimuli, we reason that conscious awareness is itself dependent on predictions generated by hierarchically organized forward models of the organism's internal sensory processing. The operation of these forward models requires a specialized neural architecture and hence any nervous system lacking this architecture is unable to subjectively experience sensory stimuli. This approach removes difficulties associated with extrapolations from behavioral and brain homologies typically employed in addressing whether an animal can feel. Using nociception as a model sensation, we show here that the Drosophila brain lacks the required internal neural connectivity to implement the computations required of hierarchical forward models. Consequently, we conclude that Drosophila, and those insects with similar neuroanatomy, do not subjectively experience noxious stimuli and therefore cannot feel pain.

Locomotor transitions in the potential energy landscape-dominated regime

To traverse complex three-dimensional terrain with large obstacles, animals and robots must transition across different modes. However, the most mechanistic understanding of terrestrial locomotion concerns how to generate and stabilize near-steady-state, single-mode locomotion (e.g. walk, run). We know little about how to use physical interaction to make robust locomotor transitions. Here, we review our progress towards filling this gap by discovering terradynamic principles of multi-legged locomotor transitions, using simplified model systems representing distinct challenges in complex three-dimensional terrain. Remarkably, general physical principles emerge across diverse model systems, by modelling locomotor-terrain interaction using a potential energy landscape approach. The animal and robots' stereotyped locomotor modes are constrained by physical interaction. Locomotor transitions are stochastic, destabilizing, barrier-crossing transitions on the landscape. They can be induced by feed-forward self-propulsion and are facilitated by feedback-controlled active adjustment. General physical principles and strategies from our systematic studies already advanced robot performance in simple model systems. Efforts remain to better understand the intelligence aspect of locomotor transitions and how to compose larger-scale potential energy landscapes of complex three-dimensional terrains from simple landscapes of abstracted challenges. This will elucidate how the neuromechanical control system mediates physical interaction to generate multi-pathway locomotor transitions and lead to advancements in biology, physics, robotics and dynamical systems theory.

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.

Reverse Engineering and Robotics as Tools for Analyzing Neural Circuits

Understanding neuronal circuits that have evolved over millions of years to control adaptive behavior may provide us with alternative solutions to problems in robotics. Recently developed genetic tools allow us to study the connectivity and function of the insect nervous system at the single neuron level. However, neuronal circuits are complex, so the question remains, can we unravel the complex neuronal connectivity to understand the principles of the computations it embodies? Here, I illustrate the plausibility of incorporating reverse engineering to analyze part of the central complex, an insect brain structure essential for navigation behaviors such as maintaining a specific compass heading and path integration. I demonstrate that the combination of reverse engineering with simulations allows the study of both the structure and function of the underlying circuit, an approach that augments our understanding of both the computation performed by the neuronal circuit and the role of its components.

The Insecticidal Activity of Rhinella schneideri (Werner, 1894) Paratoid Secretion in Nauphoeta cinerea Cocroaches

Rhinella schneideri is a common toad found in South America, whose paratoid toxic secretion has never been explored as an insecticide. In order to evaluate its insecticidal potential, Nauphoeta cinerea cockroaches were used as an experimental model in biochemical, physiological and behavioral procedures. Lethality assays with Rhinella schneideri paratoid secretion (RSPS) determined the LD₅₀ value after 24 h (58.07µg/g) and 48 h exposure (44.07 µg/g) (R² = 0.882 and 0.954, respectively). Acetylcholinesterase activity (AChE) after RSPS at its highest dose promoted an enzyme inhibition of 40%, a similar effect observed with neostigmine administration (p < 0.001, n= 5). Insect locomotion recordings revealed that RSPS decreased the distance traveled by up to 37% with a concomitant 85% increase in immobile episodes (p < 0.001, n = 36). RSPS added to in vivo cockroach semi-isolated heart preparation promoted an irreversible and dose dependent decrease in heart rate, showing a complete failure after 30 min recording (p < 0.001, n ≥ 6). In addition, RSPS into nerve-muscle preparations induced a dose-dependent neuromuscular blockade, reaching a total blockage at 70 min at the highest dose applied (p < 0.001, n ≥ 6). The effect of RSPS on spontaneous sensorial action potentials was characterized by an increase in the number of spikes 61% (p < 0.01). Meanwhile, there was 42% decrease in the mean area of those potentials (p < 0.05, n ≥ 6). The results obtained here highlight the potential insecticidal relevance of RSPS and its potential biotechnological application.

An energy landscape approach to locomotor transitions in complex 3D terrain

Effective locomotion in nature happens by transitioning across multiple modes (e.g., walk, run, climb). Despite this, far more mechanistic understanding of terrestrial locomotion has been on how to generate and stabilize around near-steady-state movement in a single mode. We still know little about how locomotor transitions emerge from physical interaction with complex terrain. Consequently, robots largely rely on geometric maps to avoid obstacles, not traverse them. Recent studies revealed that locomotor transitions in complex three-dimensional (3D) terrain occur probabilistically via multiple pathways. Here, we show that an energy landscape approach elucidates the underlying physical principles. We discovered that locomotor transitions of animals and robots self-propelled through complex 3D terrain correspond to barrier-crossing transitions on a potential energy landscape. Locomotor modes are attracted to landscape basins separated by potential energy barriers. Kinetic energy fluctuation from oscillatory self-propulsion helps the system stochastically escape from one basin and reach another to make transitions. Escape is more likely toward lower barrier direction. These principles are surprisingly similar to those of near-equilibrium, microscopic systems. Analogous to free-energy landscapes for multipathway protein folding transitions, our energy landscape approach from first principles is the beginning of a statistical physics theory of multipathway locomotor transitions in complex terrain. This will not only help understand how the organization of animal behavior emerges from multiscale interactions between their neural and mechanical systems and the physical environment, but also guide robot design, control, and planning over the large, intractable locomotor-terrain parameter space to generate robust locomotor transitions through the real world.

On the Role of the Head Ganglia in Posture and Walking in Insects

In insects, locomotion is the result of rhythm generating thoracic circuits and their modulation by sensory reflexes and by inputs from the two head ganglia, the cerebral and the gnathal ganglia (GNG), which act as higher order neuronal centers playing different functions in the initiation, goal-direction, and maintenance of movement. Current knowledge on the various roles of major neuropiles of the cerebral ganglia (CRG), such as mushroom bodies (MB) and the central complex (CX), in particular, are discussed as well as the role of the GNG. Thoracic and head ganglia circuitries are connected by ascending and descending neurons. While less is known about the ascending neurons, recent studies in large insects and Drosophila have begun to unravel the identity of descending neurons and their appropriate roles in posture and locomotion. Descending inputs from the head ganglia are most important in initiating and modulating thoracic central pattern generating circuitries to achieve goal directed locomotion. In addition, the review will also deal with some known monoaminergic descending neurons which affect the motor circuits involved in posture and locomotion. In conclusion, we will present a few issues that have, until today, been little explored. For example, how and which descending neurons are selected to engage a specific motor behavior and how feedback from thoracic circuitry modulate the head ganglia circuitries. The review will discuss results from large insects, mainly locusts, crickets, and stick insects but will mostly focus on cockroaches and the fruit fly, Drosophila.

Tyrosine hydroxylase immunolabeling reveals the distribution of catecholaminergic neurons in the central nervous systems of the spiders Hogna lenta (Araneae: Lycosidae) and Phidippus regius (Araneae: Salticidae)

With over 48,000 species currently described, spiders (Arthropoda: Chelicerata: Araneae) comprise one of the most diverse groups of animals on our planet, and exhibit an equally wide array of fascinating behaviors. Studies of central nervous systems (CNSs) in spiders, however, are relatively sparse, and no reports have yet characterized catecholaminergic (dopamine [DA]- or norepinephrine-synthesizing) neurons in any spider species. Because these neuromodulators are especially important for sensory and motor processing across animal taxa, we embarked on a study to identify catecholaminergic neurons in the CNS of the wolf spider Hogna lenta (Lycosidae) and the jumping spider Phidippus regius (Salticidae). These neurons were most effectively labeled with an antiserum raised against tyrosine hydroxylase (TH), the rate-limiting enzyme in catecholamine synthesis. We found extensive catecholamine-rich neuronal fibers in the first- and second-order optic neuropils of the supraesophageal mass (brain), as well as in the arcuate body, a region of the brain thought to receive visual input and which may be involved in higher order sensorimotor integration. This structure likely shares evolutionary origins with the DA-enriched central complex of the Mandibulata. In the subesophageal mass, we detected an extensive filigree of TH-immunoreactive (TH-ir) arborizations in the appendage neuromeres, as well as three prominent plurisegmental fiber tracts. A vast abundance of TH-ir somata were located in the opisthosomal neuromeres, the largest of which appeared to project to the brain and decorate the appendage neuromeres. Our study underscores the important roles that the catecholamines likely play in modulating spider vision, higher order sensorimotor processing, and motor patterning.

A dynamical model exploring sensory integration in the insect central complex substructures

It is imperative that an animal has the ability to contextually integrate received sensory information to formulate appropriate behavioral responses. Determining a body heading based on a multitude of ego-motion cues and visual landmarks is an example of such a task that requires this context dependent integration. The work presented here simulates a sensory integrator in the insect brain called the central complex (CX). Based on the architecture of the CX, we assembled a dynamical neural simulation of two structures called the protocerebral bridge (PB) and the ellipsoid body (EB). Using non-spiking neuronal dynamics, our simulation was able to recreate in vivo neuronal behavior such as correlating body rotation direction and speed to activity bumps within the EB as well as updating the believed heading with quick secondary system updates. With this model, we performed sensitivity analysis of certain neuronal parameters as a possible means to control multi-system gains during sensory integration. We found that modulation of synapses in the memory network and EB inhibition are two possible mechanisms in which a sensory system could affect the memory stability and gain of another input, respectively. This model serves as an exploration in network design for integrating simultaneous idiothetic and allothetic cues in the task of body tracking and determining contextually dependent behavioral outputs.

Inverse Control of Turning Behavior by Dopamine D1 Receptor Signaling in Columnar and Ring Neurons of the Central Complex in Drosophila

Action selection is a prerequisite for decision-making and a fundamental aspect to any goal-directed locomotion; it requires integration of sensory signals and internal states to translate them into action sequences. Here, we introduce a novel behavioral analysis to study neural circuits and mechanisms underlying action selection and decision-making in freely moving Drosophila. We discovered preferred patterns of motor activity and turning behavior. These patterns are impaired in FoxP mutant flies, which present an altered temporal organization of motor actions and turning behavior, reminiscent of indecisiveness. Then, focusing on central complex (CX) circuits known to integrate different sensory modalities and controlling premotor regions, we show that action sequences and turning behavior are regulated by dopamine D1-like receptor (Dop1R1) signaling. Dop1R1 inputs onto CX columnar ellipsoid body-protocerebral bridge gall (E-PG) neuron and ellipsoid body (EB) R2/R4m ring neuron circuits both negatively gate motor activity but inversely control turning behavior. Although flies deficient of D1 receptor signaling present normal turning behavior despite decreased activity, restoring Dop1R1 level in R2/R4m-specific circuitry affects the temporal organization of motor actions and turning. We finally show EB R2/R4m neurons are in contact with E-PG neurons that are thought to encode body orientation and heading direction of the fly. These findings suggest that Dop1R1 signaling in E-PG and EB R2/4 m circuits are compared against each other, thereby modulating patterns of activity and turning behavior for goal-directed locomotion.

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Freely moving Drosophila present preferred patterns of activity and turning behavior

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FoxP mutations affect temporal distribution of motor actions and turning behavior

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Central complex columnar E-PG and R2/4 m ring neurons inversely regulate turning

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Dopamine D1-like receptor signaling in R2/R4m ring neurons modulates behavior

Investigating the efficiency of a bio-inspired insect repellent surface structure

Most insects with smooth or hairy adhesive pads have very little problems in attaching to smooth substrates. A careful selection of surface roughness, however, can effectively limit the contact area of the adhesive organs with the surface. In comparison to conventional toxin-based insect repelling methods, biologically inspired micro- and nanostructured insect repellent surface structures, thus, offer a great potential to effective and environmentally-friendly control insect pests. We here present a simple experimental approach to qualitatively and quantitatively analyse the efficiency of a micro- and nanorough surface structure. Nauphoeta cinerea and Gastrophysa viridula as model organisms for insects with smooth and hairy adhesive pads, respectively, were placed in an enclosed environment. The escape movements of freely running insects over either the repellent or a control surfaces were counted and analyzed in detail. The tested surface structures were able to significantly reduce the escape of cockroaches with smooth adhesive pads by 44.1%. Interestingly, the data indicates that N. cinerea might use mechanical cues from the antenna to discriminate between surfaces before making contact with the adhesive pads. G. viridula with hairy adhesive pads were not significantly affected by the surface structure. By carefully adjusting 'critical' surface topography parameters relevant for insect adhesion, more efficient and selective repellent surfaces might be achieved. Such nanostructure-based insect repellent surfaces could also help to utilize recruitment behavior of certain insect species and might present a novel approach to effectively control insect pests.

Dynamic traversal of large gaps by insects and legged robots reveals a template

It is well known that animals can use neural and sensory feedback via vision, tactile sensing, and echolocation to negotiate obstacles. Similarly, most robots use deliberate or reactive planning to avoid obstacles, which relies on prior knowledge or high-fidelity sensing of the environment. However, during dynamic locomotion in complex, novel, 3D terrains, such as a forest floor and building rubble, sensing and planning suffer bandwidth limitation and large noise and are sometimes even impossible. Here, we study rapid locomotion over a large gap-a simple, ubiquitous obstacle-to begin to discover the general principles of the dynamic traversal of large 3D obstacles. We challenged the discoid cockroach and an open-loop six-legged robot to traverse a large gap of varying length. Both the animal and the robot could dynamically traverse a gap as large as one body length by bridging the gap with its head, but traversal probability decreased with gap length. Based on these observations, we developed a template that accurately captured body dynamics and quantitatively predicted traversal performance. Our template revealed that a high approach speed, initial body pitch, and initial body pitch angular velocity facilitated dynamic traversal, and successfully predicted a new strategy for using body pitch control that increased the robot's maximal traversal gap length by 50%. Our study established the first template of dynamic locomotion beyond planar surfaces, and is an important step in expanding terradynamics into complex 3D terrains.

A Scalable Weight-Free Learning Algorithm for Regulatory Control of Cell Activity in Spiking Neuronal Networks

Recent developments in neural stimulation and recording technologies are providing scientists with the ability of recording and controlling the activity of individual neurons in vitro or in vivo, with very high spatial and temporal resolution. Tools such as optogenetics, for example, are having a significant impact in the neuroscience field by delivering optical firing control with the precision and spatiotemporal resolution required for investigating information processing and plasticity in biological brains. While a number of training algorithms have been developed to date for spiking neural network (SNN) models of biological neuronal circuits, exiting methods rely on learning rules that adjust the synaptic strengths (or weights) directly, in order to obtain the desired network-level (or functional-level) performance. As such, they are not applicable to modifying plasticity in biological neuronal circuits, in which synaptic strengths only change as a result of pre- and post-synaptic neuron firings or biological mechanisms beyond our control. This paper presents a weight-free training algorithm that relies solely on adjusting the spatiotemporal delivery of neuron firings in order to optimize the network performance. The proposed weight-free algorithm does not require any knowledge of the SNN model or its plasticity mechanisms. As a result, this training approach is potentially realizable in vitro or in vivo via neural stimulation and recording technologies, such as optogenetics and multielectrode arrays, and could be utilized to control plasticity at multiple scales of biological neuronal circuits. The approach is demonstrated by training SNNs with hundreds of units to control a virtual insect navigating in an unknown environment.

An Ultralightweight and Living Legged Robot

In this study, we describe the most ultralightweight living legged robot to date that makes it a strong candidate for a search and rescue mission. The robot is a living beetle with a wireless electronic backpack stimulator mounted on its thorax. Inheriting from the living insect, the robot employs a compliant body made of soft actuators, rigid exoskeletons, and flexure hinges. Such structure would allow the robot to easily adapt to any complex terrain due to the benefit of soft interface, self-balance, and self-adaptation of the insect without any complex controller. The antenna stimulation enables the robot to perform not only left/right turning but also backward walking and even cessation of walking. We were also able to grade the turning and backward walking speeds by changing the stimulation frequency. The power required to drive the robot is low as the power consumption of the antenna stimulation is in the order of hundreds of microwatts. In contrast to the traditional legged robots, this robot is of low cost, easy to construct, simple to control, and has ultralow power consumption.

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

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

Insect-Like Organization of the Stomatopod Central Complex: Functional and Phylogenetic Implications

One approach to investigating functional attributes of the central complex is to relate its various elaborations to pancrustacean phylogeny, to taxon-specific behavioral repertoires and ecological settings. Here we review morphological similarities between the central complex of stomatopod crustaceans and the central complex of dicondylic insects. We discuss whether their central complexes possess comparable functional properties, despite the phyletic distance separating these taxa, with mantis shrimp (Stomatopoda) belonging to the basal branch of Eumalacostraca. Stomatopods possess the most elaborate visual receptor system in nature and display a fascinating behavioral repertoire, including refined appendicular dexterity such as independently moving eyestalks. They are also unparalleled in their ability to maneuver during both swimming and substrate locomotion. Like other pancrustaceans, stomatopods possess a set of midline neuropils, called the central complex, which in dicondylic insects have been shown to mediate the selection of motor actions for a range of behaviors. As in dicondylic insects, the stomatopod central complex comprises a modular protocerebral bridge (PB) supplying decussating axons to a scalloped fan-shaped body (FB) and its accompanying ellipsoid body (EB), which is linked to a set of paired noduli and other recognized satellite regions. We consider the functional implications of these attributes in the context of stomatopod behaviors, particularly of their eyestalks that can move independently or conjointly depending on the visual scene.

Spatial Navigation and the Central Complex: Sensory Acquisition, Orientation, and Motor Control

Cockroaches are scavengers that forage through dark, maze-like environments. Like other foraging animals, for instance rats, they must continually asses their situation to keep track of targets and negotiate barriers. While navigating a complex environment, all animals need to integrate sensory information in order to produce appropriate motor commands. The integrated sensory cues can be used to provide the animal with an environmental and contextual reference frame for the behavior. To successfully reach a goal location, navigational cues continuously derived from sensory inputs have to be utilized in the spatial guidance of motor commands. The sensory processes, contextual and spatial mechanisms, and motor outputs contributing to navigation have been heavily studied in rats. In contrast, many insect studies focused on the sensory and/or motor components of navigation, and our knowledge of the abstract representation of environmental context and spatial information in the insect brain is relatively limited. Recent reports from several laboratories have explored the role of the central complex (CX), a sensorimotor region of the insect brain, in navigational processes by recording the activity of CX neurons in freely-moving insects and in more constrained, experimenter-controlled situations. The results of these studies indicate that the CX participates in processing the temporal and spatial components of sensory cues, and utilizes these cues in creating an internal representation of orientation and context, while also directing motor control. Although these studies led to a better understanding of the CX's role in insect navigation, there are still major voids in the literature regarding the underlying mechanisms and brain regions involved in spatial navigation. The main goal of this review is to place the above listed findings in the wider context of animal navigation by providing an overview of the neural mechanisms of navigation in rats and summarizing and comparing our current knowledge on the CX's role in insect navigation to these processes. By doing so, we aimed to highlight some of the missing puzzle pieces in insect navigation and provide a different perspective for future directions.

Behavioural integration of auditory and antennal stimulation during phonotaxis in the field cricket Gryllus bimaculatus

Animals need to flexibly respond to stimuli from their environment without compromising behavioural consistency. For example, female crickets orienting toward a conspecific male's calling song in search of a mating partner need to stay responsive to other signals that provide information about obstacles and predators. Here, we investigate how spontaneously walking crickets and crickets engaging in acoustically guided goal-directed navigation, i.e. phonotaxis, respond to mechanosensory stimuli detected by their long antennae. We monitored walking behaviour of female crickets on a trackball during lateral antennal stimulation, which was achieved by moving a wire mesh transiently into reach of one antenna. During antennal stimulation alone, females reduced their walking speed, oriented toward the object and actively explored it with antennal movements. Additionally, some crickets initially turned away from the approaching object. Females responded in a similar way when the antennal stimulus was presented during ongoing phonotaxis: forward velocity was reduced and phonotactic steering was suppressed while the females turned toward and explored the object. Further, rapid steering bouts to individual chirps, typical for female phonotaxis, no longer occurred. Our data reveal that in this experimental situation, antennal stimulation overrides phonotaxis for extended time periods. Phonotaxis in natural environments, which require the integration of multiple sensory cues, may therefore be more variable than phonotaxis measured under ideal laboratory conditions. Combining this new behavioural paradigm with neurophysiological methods will show where the sensory-motor integration of antennal and acoustic stimulation occurs and how this is achieved on a mechanistic level.

Evolutionarily conserved mechanisms for the selection and maintenance of behavioural activity

Survival and reproduction entail the selection of adaptive behavioural repertoires. This selection manifests as phylogenetically acquired activities that depend on evolved nervous system circuitries. Lorenz and Tinbergen already postulated that heritable behaviours and their reliable performance are specified by genetically determined programs. Here we compare the functional anatomy of the insect central complex and vertebrate basal ganglia to illustrate their role in mediating selection and maintenance of adaptive behaviours. Comparative analyses reveal that central complex and basal ganglia circuitries share comparable lineage relationships within clusters of functionally integrated neurons. These clusters are specified by genetic mechanisms that link birth time and order to their neuronal identities and functions. Their subsequent connections and associated functions are characterized by similar mechanisms that implement dimensionality reduction and transition through attractor states, whereby spatially organized parallel-projecting loops integrate and convey sensorimotor representations that select and maintain behavioural activity. In both taxa, these neural systems are modulated by dopamine signalling that also mediates memory-like processes. The multiplicity of similarities between central complex and basal ganglia suggests evolutionarily conserved computational mechanisms for action selection. We speculate that these may have originated from ancestral ground pattern circuitries present in the brain of the last common ancestor of insects and vertebrates.

Compass Cells in the Brain of an Insect Are Sensitive to Novel Events in the Visual World

The central complex of the insect brain comprises a group of neuropils involved in spatial orientation and memory. In fruit flies it mediates place learning based on visual landmarks and houses neurons that encode the orientation for goal-directed locomotion, based on landmarks and self-motion cues for angular path-integration. In desert locusts, the central complex holds a compass-like representation of head directions, based on the polarization pattern of skylight. Through intracellular recordings from immobilized locusts, we investigated whether sky compass neurons of the central complex also represent the position or any salient feature of possible landmarks, in analogy to the observations in flies. Neurons showed strongest responses to the novel appearance of a small moving square, but we found no evidence for a topographic representation of object positions. Responses to an individual square were independent of direction of motion and trajectory, but showed rapid adaptation to successive stimulation, unaffected by changing the direction of motion. Responses reappeared, however, if the moving object changed its trajectory or if it suddenly reversed moving direction against the movement of similar objects that make up a coherent background-flow as induced by ego-motion. Response amplitudes co-varied with the precedent state of dynamic background activity, a phenomenon that has been related to attention-dependent saliency coding in neurons of the mammalian primary visual cortex. The data show that neurons of the central complex of the locust brain are visually bimodal, signaling sky compass direction and the novelty character of moving objects. These response properties might serve to attune compass-aided locomotor control to unexpected events in the environment. The difference to data obtained in fruit flies might relate to differences in the lifestyle of landmark learners (fly) and compass navigators (locust), point to the existence of parallel networks for the two orientation strategies, or reflect differences in experimental conditions.

Central-complex control of movement in the freely walking cockroach

To navigate in the world, an animal's brain must produce commands to move, change direction, and negotiate obstacles. In the insect brain, the central complex integrates multiple forms of sensory information and guides locomotion during behaviors such as foraging, climbing over barriers, and navigating to memorized locations. These roles suggest that the central complex influences motor commands, directing the appropriate movement within the current context. Such commands are ultimately carried out by the limbs and must therefore interact with pattern generators and reflex circuits that coordinate them. Recent studies have described how neurons of the central complex encode sensory information: neurons subdivide the space around the animal, encoding the direction or orientation of stimuli used in navigation. Does a similar central-complex code directing movement exist, and if so, how does it effect changes in the control of limbs? Recording from central-complex neurons in freely walking cockroaches (Blaberus discoidalis), we identified classes of movement-predictive cells selective for slow or fast forward walking, left or right turns, or combinations of forward and turning speeds. Stimulation through recording wires produced consistent trajectories of forward walking or turning in these animals, and those that elicited turns also altered an inter-joint reflex to a pattern resembling spontaneous turning. When an animal transitioned to climbing over an obstacle, the encoding of movement in this new context changed for a subset of cells. These results indicate that encoding of movement in the central complex participates in motor control by a distributed, flexible code targeting limb reflex circuits.

How cockroaches exploit tactile boundaries to find new shelters

Animals such as cockroaches depend on exploration of unknown environments, and their strategies may inspire robotic approaches. We have previously shown that cockroach behavior, with respect to shelters and the walls of an otherwise empty arena, can be captured with a stochastic state-based algorithm. We call this algorithm RAMBLER, randomized algorithm mimicking biased lone exploration in roaches. In this work, we verified and extended this model by adding a barrier in the previously used arena and conducted more cockroach experiments. In two arena configurations, our simulated model's path length distribution was similar to the experimental distribution (mean experimental path length 3.4 and 3.2 m, mean simulated path length 3.9 and 3.3 m). By analyzing cockroach behavior before, along, and at the end of the barrier, we have generalized RAMBLER to address arbitrarily complex 2D mazes. For biology, this is an abstract behavioral model of a decision-making process in the cockroach brain. For robotics, this is a strategy that may improve exploration for goals, especially in unpredictable environments with non-convex obstacles. Generally, cockroach behavior seems to recommend variability in the absence of planning, and following paths defined by walls.

Controlling legs for locomotion-insights from robotics and neurobiology

Walking is the most common terrestrial form of locomotion in animals. Its great versatility and flexibility has led to many attempts at building walking machines with similar capabilities. The control of walking is an active research area both in neurobiology and robotics, with a large and growing body of work. This paper gives an overview of the current knowledge on the control of legged locomotion in animals and machines and attempts to give walking control researchers from biology and robotics an overview of the current knowledge in both fields. We try to summarize the knowledge on the neurobiological basis of walking control in animals, emphasizing common principles seen in different species. In a section on walking robots, we review common approaches to walking controller design with a slight emphasis on biped walking control. We show where parallels between robotic and neurobiological walking controllers exist and how robotics and biology may benefit from each other. Finally, we discuss where research in the two fields diverges and suggest ways to bridge these gaps.

Amplitude and dynamics of polarization-plane signaling in the central complex of the locust brain

The polarization pattern of skylight provides a compass cue that various insect species use for allocentric orientation. In the desert locust, Schistocerca gregaria, a network of neurons tuned to the electric field vector (E-vector) angle of polarized light is present in the central complex of the brain. Preferred E-vector angles vary along slices of neuropils in a compasslike fashion (polarotopy). We studied how the activity in this polarotopic population is modulated in ways suited to control compass-guided locomotion. To this end, we analyzed tuning profiles using measures of correlation between spike rate and E-vector angle and, furthermore, tested for adaptation to stationary angles. The results suggest that the polarotopy is stabilized by antagonistic integration across neurons with opponent tuning. Downstream to the input stage of the network, responses to stationary E-vector angles adapted quickly, which may correlate with a tendency to steer a steady course previously observed in tethered flying locusts. By contrast, rotating E-vectors corresponding to changes in heading direction under a natural sky elicited nonadapting responses. However, response amplitudes were particularly variable at the output stage, covarying with the level of ongoing activity. Moreover, the responses to rotating E-vector angles depended on the direction of rotation in an anticipatory manner. Our observations support a view of the central complex as a substrate of higher-stage processing that could assign contextual meaning to sensory input for motor control in goal-driven behaviors. Parallels to higher-stage processing of sensory information in vertebrates are discussed.

Static antennae act as locomotory guides that compensate for visual motion blur in a diurnal, keen-eyed predator

High visual acuity allows parallel processing of distant environmental features, but only when photons are abundant enough. Diurnal tiger beetles (Carabidae: Cicindelinae) have acute vision for insects and visually pursue prey in open, flat habitats. Their fast running speed causes motion blur that degrades visual contrast, forces stop-and-go pursuit and potentially impairs obstacle detection. We demonstrate here that vision is insufficient for obstacle detection during running, and show instead that antennal touch is both necessary and sufficient for obstacle detection. While running, tiger beetle vision appears to be photon-limited in a way reminiscent of animals in low-light habitats. Such animals often acquire wide-field spatial information through mechanosensation mediated by longer, more mobile appendages. We show that a nocturnal tiger beetle species waves its antennae in elliptical patterns typical of poorly sighted insects. While antennae of diurnal species are also used for mechanosensation, they are rigidly held forward with the tips close to the substrate. This enables timely detection of path obstructions followed by an increase in body pitch to avoid collision. Our results demonstrate adaptive mechanosensory augmentation of blurred visual information during fast locomotion, and suggest that future studies may reveal non-visual sensory compensation in other fast-moving animals.

Organization and functional roles of the central complex in the insect brain

The central complex is a group of modular neuropils across the midline of the insect brain. Hallmarks of its anatomical organization are discrete layers, an organization into arrays of 16 slices along the right-left axis, and precise inter-hemispheric connections via chiasmata. The central complex is connected most prominently with the adjacent lateral complex and the superior protocerebrum. Its developmental appearance corresponds with the appearance of compound eyes and walking legs. Distinct dopaminergic neurons control various forms of arousal. Electrophysiological studies provide evidence for roles in polarized light vision, sky compass orientation, and integration of spatial information for locomotor control. Behavioral studies on mutant and transgenic flies indicate roles in spatial representation of visual cues, spatial visual memory, directional control of walking and flight, and place learning. The data suggest that spatial azimuthal directions (i.e., where) are represented in the slices, and cue information (i.e., what) are represented in different layers of the central complex.

Encoding of near-range spatial information by descending interneurons in the stick insect antennal mechanosensory pathway

Much like mammals use their whiskers, insects use their antennae for tactile near-range orientation during locomotion. Stick insects rapidly transfer spatial information about antennal touch location to the front legs, allowing for aimed reach-to-grasp movements. This adaptive behavior requires a spatial coordinate transformation from “antennal contact space” to “leg posture space.” Therefore, a neural pathway must convey proprioceptive and tactile information about antennal posture and contact site to thoracic motor networks. Here we analyze proprioceptive encoding properties of descending interneurons (DINs) that convey information about antennal posture and movement to the thoracic ganglia. On the basis of response properties of 110 DINs to imposed movement of the distal antennal joint, we distinguish five functional DIN groups according to their sensitivity to three parameters: movement direction, movement velocity, and antennal joint angle. These groups are simple position-sensitive DINs, which signal the antennal joint angle; dynamic position-sensitive DINs, which signal the joint angle with strong dependence on movement; unspecific movement-sensitive DINs, which signal movement but not the velocity, position, or direction of movement; and ON- and OFF-type velocity-sensitive DINs. The activity of the latter two groups is increased/attenuated during antennal movement, with the spike rate increasing/decreasing linearly with antennal joint angle velocity. Some movement-sensitive DINs convey spikes to the thorax within 11 ms, suggesting a rapid, direct pathway from antennal mechanosensory to thoracic motor networks. We discuss how the population of DINs could provide the neural basis for the intersegmental spatial coordinate transfer between a touch sensor of the head and thoracic motor networks.

Widespread sensitivity to looming stimuli and small moving objects in the central complex of an insect brain

In many situations animals are confronted with approaching objects. Depending on whether the approach represents a potential threat or is intended during a goal-oriented approach, the adequate behavioral strategies differ. In all of these cases the visual system experiences an expanding or looming shape. The neuronal machinery mediating looming elicited behavioral responses has been studied most comprehensively in insects but is still far from being fully understood. It is particularly unknown how insects adjust their behavior to objects approaching from different directions. A brain structure that is thought to play an important role in spatial orientation in insects is the central complex (CC). We investigated whether CC neurons process information about approaching objects on a collision course. We recorded intracellularly from CC neurons in the locust Schistocerca gregaria during visual stimulation via lateral LCD screens. Many neurons in the locust CC, including columnar and tangential neurons, were sensitive to looming stimuli. Some of the neurons also responded to small moving targets. Several cell types showed binocular responses to looming objects, and some neurons were excited or inhibited depending on which eye was stimulated. These neurons may, therefore, detect the gross azimuthal direction of approaching objects and may mediate directional components of escape or steering movements.

Neural control and adaptive neural forward models for insect-like, energy-efficient, and adaptable locomotion of walking machines

Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs) and sensory feedback (afferent-based control) but also on internal forward models (efference copies). They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines.

Neural activity in the central complex of the cockroach brain is linked to turning behaviors

An animal moving through complex terrain must consider sensory cues around it and alter its movements accordingly. In the arthropod brain, the central complex (CC) receives highly preprocessed sensory information and sends outputs to premotor regions, suggesting that it may play a role in the central control of oriented locomotion. We performed tetrode recordings within the CC in cockroaches walking on an air-suspended ball to examine the role of the CC in turning behaviors. When a rod was placed near the cockroach's head, the cockroach touched the rod repeatedly with one or both antennae before locomotion was initiated. Some CC units responded to self-generated antennal contact with the object, but at lower levels compared with externally imposed antennal stimulation. The neural activity of other CC units responded to locomotion. We found that some CC units showed discrete firing fields corresponding to specific locomotion states. We also found that changes in firing rate of some CC units preceded changes in turning speed in one direction but not the other. Furthermore, such biased units were located in the side of the brain ipsilateral to the direction of the turning speed they could predict. Moreover, electrical stimulation of the CC elicited or modified locomotion, and the direction of some evoked locomotion could be predicted by the response property of locomotion-predictive units near the stimulation site. Therefore, our results suggest that, at the population level, asymmetrical activity in the CC precedes and influences turning behavior.

Visually guided decision making in foraging honeybees

Honeybees can easily be trained to perform different types of discrimination tasks under controlled laboratory conditions. This review describes a range of experiments carried out with free-flying forager honeybees under such conditions. The research done over the past 30 or so years suggests that cognitive abilities (learning and perception) in insects are more intricate and flexible than was originally imagined. It has become apparent that honeybees are capable of a variety of visually guided tasks, involving decision making under challenging situations: this includes simultaneously making use of different sensory modalities, such as vision and olfaction, and learning to use abstract concepts such as “sameness” and “difference.” Many studies have shown that decision making in foraging honeybees is highly flexible. The trained animals learn how to solve a task, and do so with a high accuracy, but when they are presented with a new variation of the task, they apply the learnt rules from the earlier setup to the new situation, and solve the new task as well. Honeybees therefore not only feature a rich behavioral repertoire to choose from, but also make decisions most apt to the current situation. The experiments in this review give an insight into the environmental cues and cognitive resources that are probably highly significant for a forager bee that must continually make decisions regarding patches of resources to be exploited.