Drosophila flight: How flies control casts and surges

In the absence of directional cues, most foraging animals explore space by turning and zigzagging in search of sensory information. Recent progress in the identification of the neural correlates of turns in flies offers exciting new perspectives on the evolution of neural circuits controlling fundamental aspects of orientation responses.

Descending control and regulation of spontaneous flight turns in Drosophila

The clumped distribution of resources in the world has influenced the pattern of foraging behavior since the origins of locomotion, selecting for a common search motif in which straight movements through resource-poor regions alternate with zig-zag exploration in resource-rich domains. For example, during local search, flying flies spontaneously execute rapid flight turns, called body saccades, but suppress these maneuvers during long-distance dispersal or when surging upstream toward an attractive odor. Here, we describe the key cellular components of a neural network in flies that generate spontaneous turns as well as a specialized pair of neurons that inhibits the network and suppresses turning. Using 2-photon imaging, optogenetic activation, and genetic ablation, we show that only four descending neurons appear sufficient to generate the descending commands to execute flight saccades. The network is organized into two functional units-one for right turns and one for left-with each unit consisting of an excitatory (DNae014) and an inhibitory (DNb01) neuron that project to the flight motor neuropil within the ventral nerve cord. Using resources from recently published connectomes of the fly, we identified a pair of large, distinct interneurons (VES041) that form inhibitory connections to all four saccade command neurons and created specific genetic driver lines for this cell. As predicted by its connectivity, activation of VES041 strongly suppresses saccades, suggesting that it promotes straight flight to regulate the transition between local search and long-distance dispersal. These results thus identify the key elements of a network that may play a crucial role in foraging ecology.

Emergent spatial goals in an integrative model of the insect central complex

The insect central complex appears to encode and process spatial information through vector manipulation. Here, we draw on recent insights into circuit structure to fuse previous models of sensory-guided navigation, path integration and vector memory. Specifically, we propose that the allocentric encoding of location provided by path integration creates a spatially stable anchor for converging sensory signals that is relevant in multiple behavioural contexts. The allocentric reference frame given by path integration transforms a goal direction into a goal location and we demonstrate through modelling that it can enhance approach of a sensory target in noisy, cluttered environments or with temporally sparse stimuli. We further show the same circuit can improve performance in the more complex navigational task of route following. The model suggests specific functional roles for circuit elements of the central complex that helps explain their high preservation across insect species.

Descending control and regulation of spontaneous flight turns in Drosophila

The clumped distribution of resources in the world has influenced the pattern of foraging behavior since the origins of life, selecting for a common locomotor search motif in which straight movements through resource-poor regions alternate with zig -zag exploration in resource-rich domains. For example, flies execute rapid changes in flight heading called body saccades during local search, but suppress these turns during long-distance dispersal or when surging upwind after encountering an attractive odor plume. Here, we describe the key cellular components of a neural network in flies that generates spontaneous turns as well as a specialized neuron that inhibits the network to promote straight flight. Using 2-photon imaging, optogenetic activation, and genetic ablation, we show that only four descending neurons appear sufficient to generate the descending commands to execute flight saccades. The network is organized into two functional couplets-one for right turns and one for left-with each couplet consisting of an excitatory (DNae014) and inhibitory (DNb01) neuron that project to the flight motor neuropil within the ventral nerve cord. Using resources from recently published connectomes of the fly brain, we identified a large, unique interneuron (VES041) that forms inhibitory connections to all four saccade command neurons and created specific genetic driver lines for this cell. As suggested by its connectivity, activation of VES041 strongly suppresses saccades, suggesting that it regulates the transition between local search and long-distance dispersal. These results thus identify the critical elements of a network that not only structures the locomotor behavior of flies, but may also play a crucial role in their natural foraging ecology.

How honey bees make fast and accurate decisions

Honey bee ecology demands they make both rapid and accurate assessments of which flowers are most likely to offer them nectar or pollen. To understand the mechanisms of honey bee decision-making, we examined their speed and accuracy of both flower acceptance and rejection decisions. We used a controlled flight arena that varied both the likelihood of a stimulus offering reward and punishment and the quality of evidence for stimuli. We found that the sophistication of honey bee decision-making rivalled that reported for primates. Their decisions were sensitive to both the quality and reliability of evidence. Acceptance responses had higher accuracy than rejection responses and were more sensitive to changes in available evidence and reward likelihood. Fast acceptances were more likely to be correct than slower acceptances; a phenomenon also seen in primates and indicative that the evidence threshold for a decision changes dynamically with sampling time. To investigate the minimally sufficient circuitry required for these decision-making capacities, we developed a novel model of decision-making. Our model can be mapped to known pathways in the insect brain and is neurobiologically plausible. Our model proposes a system for robust autonomous decision-making with potential application in robotics.

Scanning behaviour in ants: an interplay between random-rate processes and oscillators

At the start of a journey home or to a foraging site, ants often stop, interrupting their forward movement, turn on the spot a number of times, and fixate in different directions. These scanning bouts are thought to provide visual information for choosing a path to travel. The temporal organization of such scanning bouts has implications about the neural organisation of navigational behaviour. We examined (1) the temporal distribution of the start of such scanning bouts and (2) the dynamics of saccadic body turns and fixations that compose a scanning bout in Australian desert ants, Melophorus bagoti, as they came out of a walled channel onto open field at the start of their homeward journey. Ants were caught when they neared their nest and displaced to different locations to start their journey home again. The observed parameters were mostly similar across familiar and unfamiliar locations. The turning angles of saccadic body turning to the right or left showed some stereotypy, with a peak just under 45°. The direction of such saccades appears to be determined by a slow oscillatory process as described in other insect species. In timing, however, both the distribution of inter-scanning-bout intervals and individual fixation durations showed exponential characteristics, the signature for a random-rate or Poisson process. Neurobiologically, therefore, there must be some process that switches behaviour (starting a scanning bout or ending a fixation) with equal probability at every moment in time. We discuss how chance events in the ant brain that occasionally reach a threshold for triggering such behaviours can generate the results.

Impact of central complex lesions on innate and learnt visual navigation in ants

Wood ants are excellent navigators, using a combination of innate and learnt navigational strategies to travel between their nest and feeding sites. Visual navigation in ants has been studied extensively, however, we have little direct evidence for the underlying neural mechanisms. Here, we perform lateralized mechanical lesions in the central complex (CX) of wood ants, a midline structure known to allow an insect to keep track of the direction of sensory cues relative to its own orientation and to control movement. We lesioned two groups of ants and observed their behaviour in an arena with a large visual landmark present. The first group of ants were naïve and when intact such ants show a clear innate attraction to the conspicuous landmark. The second group of ants were trained to aim to a food location to the side of the landmark. The general heading of naïve ants towards a visual cue was not altered by the lesions, but the heading of ants trained to a landmark adjacent food position was affected. Thus, CX lesions had a specific impact on learnt visual guidance. We also observed that lateralised lesions altered the fine details of turning with lesioned ants spending less time turning to the side ipsilateral of the lesion. The results confirm the role of the CX in turn control and highlight its important role in the implementation of learnt behaviours that rely on information from other brain regions.

An intrinsic oscillator underlies visual navigation in ants

Many insects display lateral oscillations while moving, but how these oscillations are produced and participate in visual navigation remains unclear. Here, we show that visually navigating ants continuously display regular lateral oscillations coupled with variations of forward speed that strongly optimize the distance covered while simultaneously enabling them to scan left and right directions. This pattern of movement is produced endogenously and conserved across navigational contexts in two phylogenetically distant ant species. Moreover, the oscillations' amplitude can be modulated by both innate or learnt visual cues to adjust the exploration/exploitation balance to the current need. This lower-level motor pattern thus drastically reduces the degree of freedom needed for higher-level strategies to control behavior. The observed dynamical signature readily emerges from a simple neural circuit model of the insect's conserved pre-motor area known as the lateral accessory lobe, offering a surprisingly simple but effective neural control and endorsing oscillation as a core, ancestral way of moving in insects.

The sky compass network in the brain of the desert locust

Many arthropods and vertebrates use celestial signals such as the position of the sun during the day or stars at night as compass cues for spatial orientation. The neural network underlying sky compass coding in the brain has been studied in great detail in the desert locust Schistocerca gregaria. These insects perform long-range migrations in Northern Africa and the Middle East following seasonal changes in rainfall. Highly specialized photoreceptors in a dorsal rim area of their compound eyes are sensitive to the polarization of the sky, generated by scattered sunlight. These signals are combined with direct information on the sun position in the optic lobe and anterior optic tubercle and converge from both eyes in a midline crossing brain structure, the central complex. Here, head direction coding is achieved by a compass-like arrangement of columns signaling solar azimuth through a 360° range of space by combining direct brightness cues from the sun with polarization cues matching the polarization pattern of the sky. Other directional cues derived from wind direction and internal self-rotation input are likely integrated. Signals are transmitted as coherent steering commands to descending neurons for directional control of locomotion and flight.

The role of learning-walk related multisensory experience in rewiring visual circuits in the desert ant brain

Efficient spatial orientation in the natural environment is crucial for the survival of most animal species. Cataglyphis desert ants possess excellent navigational skills. After far-ranging foraging excursions, the ants return to their inconspicuous nest entrance using celestial and panoramic cues. This review focuses on the question about how naïve ants acquire the necessary spatial information and adjust their visual compass systems. Naïve ants perform structured learning walks during their transition from the dark nest interior to foraging under bright sunlight. During initial learning walks, the ants perform rotational movements with nest-directed views using the earth’s magnetic field as an earthbound compass reference. Experimental manipulations demonstrate that specific sky compass cues trigger structural neuronal plasticity in visual circuits to integration centers in the central complex and mushroom bodies. During learning walks, rotation of the sky-polarization pattern is required for an increase in volume and synaptic complexes in both integration centers. In contrast, passive light exposure triggers light-spectrum (especially UV light) dependent changes in synaptic complexes upstream of the central complex. We discuss a multisensory circuit model in the ant brain for pathways mediating structural neuroplasticity at different levels following passive light exposure and multisensory experience during the performance of learning walks.

Production of adaptive movement patterns via an insect inspired spiking neural network central pattern generator

Navigation in ever-changing environments requires effective motor behaviors. Many insects have developed adaptive movement patterns which increase their success in achieving navigational goals. A conserved brain area in the insect brain, the Lateral Accessory Lobe, is involved in generating small scale search movements which increase the efficacy of sensory sampling. When the reliability of an essential navigational stimulus is low, searching movements are initiated whereas if the stimulus reliability is high, a targeted steering response is elicited. Thus, the network mediates an adaptive switching between motor patterns. We developed Spiking Neural Network models to explore how an insect inspired architecture could generate adaptive movements in relation to changing sensory inputs. The models are able to generate a variety of adaptive movement patterns, the majority of which are of the zig-zagging kind, as seen in a variety of insects. Furthermore, these networks are robust to noise. Because a large spread of network parameters lead to the correct movement dynamics, we conclude that the investigated network architecture is inherently well-suited to generating adaptive movement patterns.

Olfactory stimuli and moonwalker SEZ neurons can drive backward locomotion in Drosophila

How different sensory stimuli are collected, processed, and further transformed into a coordinated motor response is a fundamental question in neuroscience. In particular, the internal and external conditions that drive animals to switch to backward walking and the mechanisms by which the nervous system supports such behavior are still unknown. In fruit flies, moonwalker descending neurons (MDNs) are considered command-type neurons for backward locomotion as they receive visual and mechanosensory inputs and transmit motor-related signals to downstream neurons to elicit backward locomotion. Whether other modalities converge onto MDNs, which central brain neurons activate MDNs, and whether other retreat-driving pathways exist is currently unknown. Here, we show that olfactory stimulation can elicit MDN-mediated backward locomotion. Moreover, we identify the moonwalker subesophageal zone neurons (MooSEZs), a pair of bilateral neurons, which can trigger straight and rotational backward locomotion. MooSEZs act via postsynaptic MDNs and via other descending neurons. Although they respond to olfactory input, they are not required for odor-induced backward walking. Thus, this work reveals an important modality input to MDNs, a novel set of neurons presynaptic to MDNs driving backward locomotion and an MDN-independent backward locomotion pathway.

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MooSEZs elicit backward locomotion via MDN-dependent and MDN-independent pathways

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MooSEZs are connected to MDNs and other descending neurons

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MooSEZs and MDNs both respond to olfactory input

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MooSEZs can trigger rotational backward locomotion

Rotation of skylight polarization during learning walks is necessary to trigger neuronal plasticity in Cataglyphis ants

Many animals use celestial cues for impressive navigational performances in challenging habitats. Since the position of the sun and associated skylight cues change throughout the day and season, it is crucial to correct for these changes. Cataglyphis desert ants possess a time-compensated skylight compass allowing them to navigate back to their nest using the shortest way possible. The ants have to learn the sun's daily course (solar ephemeris) during initial learning walks (LW) before foraging. This learning phase is associated with substantial structural changes in visual neuronal circuits of the ant's brain. Here, we test whether the rotation of skylight polarization during LWs is the necessary cue to induce learning-dependent rewiring in synaptic circuits in high-order integration centres of the ant brain. Our results show that structural neuronal changes in the central complex and mushroom bodies are triggered only when LWs were performed under a rotating skylight polarization pattern. By contrast, when naive ants did not perform LWs, but were exposed to skylight cues, plasticity was restricted to light spectrum-dependent changes in synaptic complexes of the lateral complex. The results identify sky-compass cues triggering learning-dependent versus -independent neuronal plasticity during the behavioural transition from interior workers to outdoor foragers.

How the insect central complex could coordinate multimodal navigation

The central complex of the insect midbrain is thought to coordinate insect guidance strategies. Computational models can account for specific behaviours, but their applicability across sensory and task domains remains untested. Here, we assess the capacity of our previous model (Sun et al. 2020) of visual navigation to generalise to olfactory navigation and its coordination with other guidance in flies and ants. We show that fundamental to this capacity is the use of a biologically plausible neural copy-and-shift mechanism that ensures sensory information is presented in a format compatible with the insect steering circuit regardless of its source. Moreover, the same mechanism is shown to allow the transfer cues from unstable/egocentric to stable/geocentric frames of reference, providing a first account of the mechanism by which foraging insects robustly recover from environmental disturbances. We propose that these circuits can be flexibly repurposed by different insect navigators to address their unique ecological needs.

A projectome of the bumblebee central complex

Insects have evolved diverse and remarkable strategies for navigating in various ecologies all over the world. Regardless of species, insects share the presence of a group of morphologically conserved neuropils known collectively as the central complex (CX). The CX is a navigational center, involved in sensory integration and coordinated motor activity. Despite the fact that our understanding of navigational behavior comes predominantly from ants and bees, most of what we know about the underlying neural circuitry of such behavior comes from work in fruit flies. Here, we aim to close this gap, by providing the first comprehensive map of all major columnar neurons and their projection patterns in the CX of a bee. We find numerous components of the circuit that appear to be highly conserved between the fly and the bee, but also highlight several key differences which are likely to have important functional ramifications.

The routes of one-eyed ants suggest a revised model of normal route following

The prevailing account of visually controlled routes is that an ant learns views as it follows a route, while guided by other path-setting mechanisms. Once a set of route views is memorised, the insect follows the route by turning and moving forwards when the view on the retina matches a stored view. We engineered a situation in which this account cannot suffice in order to discover whether there may be additional components to the performance of routes. One-eyed wood ants were trained to navigate a short route in the laboratory, guided by a single black, vertical bar placed in the blinded visual field. Ants thus had to turn away from the route to see the bar. They often turned to look at or beyond the bar and then turned to face in the direction of the goal. Tests in which the bar was shifted to be more peripheral or more frontal than in training produced a corresponding directional change in the ants' paths, demonstrating that they were guided by the bar. Examination of the endpoints of turns towards and away from the bar indicate that ants use the bar for guidance by learning how large a turn-back is needed to face the goal. We suggest that the ants' zigzag paths are, in part, controlled by turns of a learnt amplitude and that these turns are an integral component of visually guided route following.

Organization and neural connections of the lateral complex in the brain of the desert locust

The lateral complexes (LXs) are bilaterally paired neuropils in the insect brain that mediate communication between the central complex (CX), a brain center controlling spatial orientation, various sensory processing areas, and thoracic motor centers that execute locomotion. The LX of the desert locust consists of the lateral accessory lobe (LAL), and the medial and lateral bulb. We have analyzed the anatomical organization and the neuronal connections of the LX in the locust, to provide a basis for future functional studies. Reanalyzing the morphology of neurons connecting the CX and the LX revealed likely feedback loops in the sky compass network of the CX via connections in the gall of the LAL and a newly identified neuropil termed ovoid body. In addition, we characterized 16 different types of neuron that connect the LAL with other areas in the brain. Eight types of neuron provide information flow between both LALs, five types are LAL input neurons, and three types are LAL output neurons. Among these are neurons providing input from sensory brain areas such as the lobula and antennal neuropils. Brain regions most often targeted by LAL neurons are the posterior slope, the wedge, and the crepine. Two descending neurons with dendrites in the LAL were identified. Our data support and complement existing knowledge about how the LAL is embedded in the neuronal network involved in processing of sensory information and generation of appropriate behavioral output for goal-directed locomotion.

Auditory Virtual Reality for Insect Phonotaxis

Insects have a sophisticated ability to navigate real environments. Virtual reality (VR) is a powerful tool for analyzing animal navigation in laboratory studies and is the most successful when used in the study of visually guided behaviors. However, the use of VR with non-visual sensory information, such as sound, on which nocturnal insects rely, for analyzing animal navigation has not been fully studied. We developed an auditory VR for the study of auditory navigation in crickets, Gryllus bimaculatus. The system consisted of a spherical treadmill on which a tethered female cricket walked. Sixteen speakers were placed around the cricket for auditory stimuli. The two optical mice attached to the treadmill measured the cricket’s locomotion, and the sound pressure and direction of the auditory stimuli were controlled at 100 Hz based on the position and heading of the cricket relative to a sound source in a virtual arena. We demonstrated that tethered female crickets selectively responded to the conspecific male calling song and localized the sound source in a virtual arena, which was similar to the behavior of freely walking crickets. Further combinations of our system with neurophysiological techniques will help understand the neural mechanisms for insect auditory navigation.

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.

Movements, embodiment and the emergence of decisions. Insights from insect navigation

We readily infer that animals make decisions, but what this implies is usually not clearly defined. The notion of 'decision-making' ultimately stems from human introspection, and is thus loaded with anthropomorphic assumptions. Notably, the decision is made internally, is based on information, and precedes the goal directed behaviour. Also, making a decision implies that 'something' did it, thus hints at the presence of a cognitive mind, whose existence is independent of the decision itself. This view may convey some truth, but here I take the opposite stance. Using examples from research in insect navigation, this essay highlights how apparent decisions can emerge without a brain, how actions can precede information or how sophisticated goal directed behaviours can be implemented without neural decisions. This perspective requires us to shake off the idea that behaviour is a consequence of the brain; and embrace the concept that movements arise from - as much as participate in - distributed interactions between various computational centres - including the body - that reverberate in closed-loop with the environment. From this perspective we may start to picture how a cognitive mind can be the consequence, rather than the cause, of such neural and body movements.

Analysing Head-Thorax Choreography During Free-Flights in Bumblebees

Animals coordinate their various body parts, sometimes in elaborate manners to swim, walk, climb, fly, and navigate their environment. The coordination of body parts is essential to behaviors such as, chasing, escaping, landing, and the extraction of relevant information. For example, by shaping the movement of the head and body in an active and controlled manner, flying insects structure their flights to facilitate the acquisition of distance information. They condense their turns into a short period of time (the saccade) interspaced by a relatively long translation (the intersaccade). However, due to technological limitations, the precise coordination of the head and thorax during insects' free-flight remains unclear. Here, we propose methods to analyse the orientation of the head and thorax of bumblebees Bombus terrestris, to segregate the trajectories of flying insects into saccades and intersaccades by using supervised machine learning (ML) techniques, and finally to analyse the coordination between head and thorax by using artificial neural networks (ANN). The segregation of flights into saccades and intersaccades by ML, based on the thorax angular velocities, decreased the misclassification by 12% compared to classically used methods. Our results demonstrate how machine learning techniques can be used to improve the analyses of insect flight structures and to learn about the complexity of head-body coordination. We anticipate our assay to be a starting point for more sophisticated experiments and analysis on freely flying insects. For example, the coordination of head and body movements during collision avoidance, chasing behavior, or negotiation of gaps could be investigated by monitoring the head and thorax orientation of freely flying insects within and across behavioral tasks, and in different species.

The Antarium: A Reconstructed Visual Reality Device for Ant Navigation Research

We constructed a large projection device (the Antarium) with 20,000 UV-Blue-Green LEDs that allows us to present tethered ants with views of their natural foraging environment. The ants walk on an air-cushioned trackball, their movements are registered and can be fed back to the visual panorama. Views are generated in a 3D model of the ants’ environment so that they experience the changing visual world in the same way as they do when foraging naturally. The Antarium is a biscribed pentakis dodecahedron with 55 facets of identical isosceles triangles. The length of the base of the triangles is 368 mm resulting in a device that is roughly 1 m in diameter. Each triangle contains 361 blue/green LEDs and nine UV LEDs. The 55 triangles of the Antarium have 19,855 Green and Blue pixels and 495 UV pixels, covering 360° azimuth and elevation from −50° below the horizon to +90° above the horizon. The angular resolution is 1.5° for Green and Blue LEDs and 6.7° for UV LEDs, offering 65,536 intensity levels at a flicker frequency of more than 9,000 Hz and a framerate of 190 fps. Also, the direction and degree of polarisation of the UV LEDs can be adjusted through polarisers mounted on the axles of rotary actuators. We build 3D models of the natural foraging environment of ants using purely camera-based methods. We reconstruct panoramic scenes at any point within these models, by projecting panoramic images onto six virtual cameras which capture a cube-map of images to be projected by the LEDs of the Antarium. The Antarium is a unique instrument to investigate visual navigation in ants. In an open loop, it allows us to provide ants with familiar and unfamiliar views, with completely featureless visual scenes, or with scenes that are altered in spatial or spectral composition. In closed-loop, we can study the behavior of ants that are virtually displaced within their natural foraging environment. In the future, the Antarium can also be used to investigate the dynamics of navigational guidance and the neurophysiological basis of ant navigation in natural visual environments.

A decentralised neural model explaining optimal integration of navigational strategies in insects

Insect navigation arises from the coordinated action of concurrent guidance systems but the neural mechanisms through which each functions, and are then coordinated, remains unknown. We propose that insects require distinct strategies to retrace familiar routes (route-following) and directly return from novel to familiar terrain (homing) using different aspects of frequency encoded views that are processed in different neural pathways. We also demonstrate how the Central Complex and Mushroom Bodies regions of the insect brain may work in tandem to coordinate the directional output of different guidance cues through a contextually switched ring-attractor inspired by neural recordings. The resultant unified model of insect navigation reproduces behavioural data from a series of cue conflict experiments in realistic animal environments and offers testable hypotheses of where and how insects process visual cues, utilise the different information that they provide and coordinate their outputs to achieve the adaptive behaviours observed in the wild.