Still no convincing evidence for cognitive map use by honeybees

Vector-based navigation in desert ants: the significance of path-integration vectors

In the longstanding discussion of whether insects, especially central place foragers such as bees and ants, use metric representations of their landmark surroundings (so-called "cognitive maps"), the ability to find novel shortcuts between familiar locations has been considered one of the most decisive proofs for the use of such maps. Here we show by channel-based field experiments that desert ants Cataglyphis can travel such shortcuts between locations (defined by memorized goal vectors) just on the basis of path integration. When trained to visit two spatially separated feeders A and B they later travel the hitherto novel route A→B. This behavior may originate from the interaction of goal vectors retrieved from long-term memory and the current vector computed by the continuously running path integrator. Based on former experiments, we further argue that path integration is a necessary requirement also for acquiring landmark information (in form of learned goal-directed views). This emphasizes the paramount importance of path integration in these central place foragers. Finally we hypothesize that the ant's overall system of navigation consists in the optimal combination of path-integration vectors and view-based vectors, and thus handles and uses vectorial information without the need of constructing a "vector map", in which vectors are linked to known places in the environment others than to the origin of all journeys, the nest.

Is this scenery worth exploring? Insight into the visual encoding of navigating ants

Solitary foraging insects such as desert ants rely heavily on vision for navigation. Although ants can learn visual scenes, it is unclear what cues they use to decide whether a scene is worth exploring at the first place. To investigate this, we recorded the motor behaviour of Cataglyphis velox ants navigating in a virtual reality setup and measured their lateral oscillations in response to various unfamiliar visual scenes under both closed-loop and open-loop conditions. In naturalistic-looking panorama, ants display regular oscillations as observed outdoors, allowing them to efficiently scan the scenery. Manipulations of the virtual environment revealed distinct functions served by dynamic and static cues. Dynamic cues, mainly rotational optic flow, regulated the amplitude of oscillations but not their regularity. Conversely, static cues had little impact on the amplitude but were essential for producing regular oscillations. Regularity of oscillations decreased in scenes with only horizontal, only vertical or no edges, but was restored in scenes with both edge types together. The actual number of edges, the visual pattern heterogeneity across azimuths, the light intensity or the relative elevation of brighter regions did not affect oscillations. We conclude that ants use a simple but functional heuristic to determine whether the visual world is worth exploring, relying on the presence of at least two different edge orientations in the scene.

Parallel vector memories in the brain of a bee as foundation for flexible navigation

Insects rely on path integration (vector-based navigation) and landmark guidance to perform sophisticated navigational feats, rivaling those seen in mammals. Bees in particular exhibit complex navigation behaviors including creating optimal routes and novel shortcuts between locations, an ability historically indicative of the presence of a cognitive map. A mammalian cognitive map has been widely accepted. However, in insects, the existence of a centralized cognitive map is highly contentious. Using a controlled laboratory assay that condenses foraging behaviors to short distances in walking bumblebees, we reveal that vectors learned during path integration can be transferred to long-term memory, that multiple such vectors can be stored in parallel, and that these vectors can be recalled at a familiar location and used for homeward navigation. These findings demonstrate that bees meet the two fundamental requirements of a vector-based analog of a decentralized cognitive map: Home vectors need to be stored in long-term memory and need to be recalled from remembered locations. Thus, our data demonstrate that bees possess the foundational elements for a vector-based map. By utilizing this relatively simple strategy for spatial organization, insects may achieve high-level navigation behaviors seen in vertebrates with the limited number of neurons in their brains, circumventing the computational requirements associated with the cognitive maps of mammals.

On the 'cognitive map debate' in insect navigation

In a historical account recently published in this journal Dhein argues that the current debate whether insects like bees and ants use cognitive maps (centralized map hypothesis) or other means of navigation (decentralized network hypothesis) largely reflects the classical debate between American experimental psychologists à la Tolman and German ethologists à la Lorenz, respectively. In this dichotomy we, i.e., the proponents of the network hypothesis, are inappropriately placed on the Lorenzian line. In particular, we argue that in contrast to Dhein's claim our concepts are not based on merely instinctive or peripheral modes of information processing. In general, on the one side our approaches have largely been motivated by the early biocybernetics way of thinking. On the other side they are deeply rooted in studies on the insect's behavioral ecology, i.e., in the ecological setting within which the navigational strategies have evolved and within which the animal now operates. Following such a bottom-up approach we are not "anti-cognitive map researchers" but argue that the results we have obtained in ants, and also the results of some decisive experiments in bees, can be explained and simulated without the need of invoking metric maps.

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.

Navigation and dance communication in honeybees: a cognitive perspective

Flying insects like the honeybee experience the world as a metric layout embedded in a compass, the time-compensated sun compass. The focus of the review lies on the properties of the landscape memory as accessible by data from radar tracking and analyses of waggle dance following. The memory formed during exploration and foraging is thought to be composed of multiple elements, the aerial pictures that associate the multitude of sensory inputs with compass directions. Arguments are presented that support retrieval and use of landscape memory not only during navigation but also during waggle dance communication. I argue that bees expect landscape features that they have learned and that are retrieved during dance communication. An intuitive model of the bee's navigation memory is presented that assumes the picture memories form a network of geographically defined locations, nodes. The intrinsic components of the nodes, particularly their generalization process leads to binding structures, the edges. In my view, the cognitive faculties of landscape memory uncovered by these experiments are best captured by the term cognitive map.

In search of behavioral and brain processes involved in honey bee dance communication

Honey bees represent an iconic model animal for studying the underlying mechanisms affecting advanced sensory and cognitive abilities during communication among colony mates. After von Frisch discovered the functional value of the waggle dance, this complex motor pattern led ethologists and neuroscientists to study its neural mechanism, behavioral significance, and implications for a collective organization. Recent studies have revealed some of the mechanisms involved in this symbolic form of communication by using conventional behavioral and pharmacological assays, neurobiological studies, comprehensive molecular and connectome analyses, and computational models. This review summarizes several critical behavioral and brain processes and mechanisms involved in waggle dance communication. We focus on the role of neuromodulators in the dancer and the recruited follower, the interneurons and their related processing in the first mechano-processing, and the computational navigation centers of insect brains.

The cognitive map debate in insects: A historical perspective on what is at stake

Though well established in mammals, the cognitive map hypothesis has engendered a decades-long, ongoing debate in insect navigation studies involving many of the field's most prominent researchers. In this paper, I situate the debate within the broader context of 20th century animal behavior research and argue that the debate persists because competing research groups are guided by different constellations of epistemic aims, theoretical commitments, preferred animal subjects, and investigative practices. The expanded history of the cognitive map provided in this paper shows that more is at stake in the cognitive map debate than the truth value of propositions characterizing insect cognition. What is at stake is the future direction of an extraordinarily productive tradition of insect navigation research stretching back to Karl von Frisch. Disciplinary labels like ethology, comparative psychology, and behaviorism became less relevant at the turn of the 21st century, but as I show, the different ways of knowing animals associated with these disciplines continue to motivate debates about animal cognition. This examination of scientific disagreement surrounding the cognitive map hypothesis also has significant consequences for philosophers' use of cognitive map research as a case study.

Cognitive maps in the wild: revealing the use of metric information in black howler monkey route navigation

When navigating, wild animals rely on internal representations of the external world – called ‘cognitive maps’ – to take movement decisions. Generally, flexible navigation is hypothesized to be supported by sophisticated spatial skills (i.e. Euclidean cognitive maps); however, constrained movements along habitual routes are the most commonly reported navigation strategy. Even though incorporating metric information (i.e. distances and angles between locations) in route-based cognitive maps would likely enhance an animal's navigation efficiency, there has been no evidence of this strategy reported for non-human animals to date. Here, we examined the properties of the cognitive map used by a wild population of primates by testing a series of cognitive hypotheses against spatially explicit movement simulations. We collected 3104 h of ranging and behavioural data on five groups of black howler monkeys (Alouatta pigra) at Palenque National Park, Mexico, from September 2016 through August 2017. We simulated correlated random walks mimicking the ranging behaviour of the study subjects and tested for differences between observed and simulated movement patterns. Our results indicated that black howler monkeys engaged in constrained movement patterns characterized by a high path recursion tendency, which limited their capacity to travel in straight lines and approach feeding trees from multiple directions. In addition, we found that the structure of observed route networks was more complex and efficient than simulated route networks, suggesting that black howler monkeys incorporate metric information into their cognitive map. Our findings not only expand the use of metric information during route navigation to non-human animals, but also highlight the importance of considering efficient route-based navigation as a cognitively demanding mechanism.

Highlighted Article: Black howler monkeys rely on route-based cognitive maps, which constrain their movement decisions, but likely incorporate metric information to navigate more efficiently along frequently used routes.

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.

An Important Step toward Understanding the Role of Body-based Cues on Human Spatial Memory for Large-Scale Environments

Moving our body through space is fundamental to human navigation; however, technical and physical limitations have hindered our ability to study the role of these body-based cues experimentally. We recently designed an experiment using novel immersive virtual-reality technology, which allowed us to tightly control the availability of body-based cues to determine how these cues influence human spatial memory [Huffman, D. J., & Ekstrom, A. D. A modality-independent network underlies the retrieval of large-scale spatial environments in the human brain. Neuron, 104, 611-622, 2019]. Our analysis of behavior and fMRI data revealed a similar pattern of results across a range of body-based cues conditions, thus suggesting that participants likely relied primarily on vision to form and retrieve abstract, holistic representations of the large-scale environments in our experiment. We ended our paper by discussing a number of caveats and future directions for research on the role of body-based cues in human spatial memory. Here, we reiterate and expand on this discussion, and we use a commentary in this issue by A. Steel, C. E. Robertson, and J. S. Taube (Current promises and limitations of combined virtual reality and functional magnetic resonance imaging research in humans: A commentary on Huffman and Ekstrom (2019). Journal of Cognitive Neuroscience, 2020) as a helpful discussion point regarding some of the questions that we think will be the most interesting in the coming years. We highlight the exciting possibility of taking a more naturalistic approach to study the behavior, cognition, and neuroscience of navigation. Moreover, we share the hope that researchers who study navigation in humans and nonhuman animals will synergize to provide more rapid advancements in our understanding of cognition and the brain.

Opponent processes in visual memories: A model of attraction and repulsion in navigating insects' mushroom bodies

Solitary foraging insects display stunning navigational behaviours in visually complex natural environments. Current literature assumes that these insects are mostly driven by attractive visual memories, which are learnt when the insect's gaze is precisely oriented toward the goal direction, typically along its familiar route or towards its nest. That way, an insect could return home by simply moving in the direction that appears most familiar. Here we show using virtual reconstructions of natural environments that this principle suffers from fundamental drawbacks, notably, a given view of the world does not provide information about whether the agent should turn or not to reach its goal. We propose a simple model where the agent continuously compares its current view with both goal and anti-goal visual memories, which are treated as attractive and repulsive respectively. We show that this strategy effectively results in an opponent process, albeit not at the perceptual level-such as those proposed for colour vision or polarisation detection-but at the level of the environmental space. This opponent process results in a signal that strongly correlates with the angular error of the current body orientation so that a single view of the world now suffices to indicate whether the agent should turn or not. By incorporating this principle into a simple agent navigating in reconstructed natural environments, we show that it overcomes the usual shortcomings and produces a step-increase in navigation effectiveness and robustness. Our findings provide a functional explanation to recent behavioural observations in ants and why and how so-called aversive and appetitive memories must be combined. We propose a likely neural implementation based on insects' mushroom bodies' circuitry that produces behavioural and neural predictions contrasting with previous models.

The Role of Landscapes and Landmarks in Bee Navigation: A Review

The ability of animals to explore landmarks in their environment is essential to their fitness. Landmarks are widely recognized to play a key role in navigation by providing information in multiple sensory modalities. However, what is a landmark? We propose that animals use a hierarchy of information based upon its utility and salience when an animal is in a given motivational state. Focusing on honeybees, we suggest that foragers choose landmarks based upon their relative uniqueness, conspicuousness, stability, and context. We also propose that it is useful to distinguish between landmarks that provide sensory input that changes ("near") or does not change ("far") as the receiver uses these landmarks to navigate. However, we recognize that this distinction occurs on a continuum and is not a clear-cut dichotomy. We review the rich literature on landmarks, focusing on recent studies that have illuminated our understanding of the kinds of information that bees use, how they use it, potential mechanisms, and future research directions.

A cognitive map in a poison frog

A fundamental question in cognitive science is whether an animal can use a cognitive map. A cognitive map is a mental representation of the external world, and knowledge of one's place in this world, that can be used to determine efficient routes to any destination. Many birds and mammals are known to employ a cognitive map, but whether other vertebrates can create a cognitive map is less clear. Amphibians are capable of using beacons, gradients and landmarks when navigating, and many are proficient at homing. Yet only one prior study directly tested for a cognitive map in amphibians, with negative results. Poison frogs exhibit unusually complex social and spatial behaviors and are capable of long-distance homing after displacement, suggesting that they may be using complex spatial navigation strategies in nature. Here, we trained the poison frog Dendrobates auratus in a modified Morris water maze that was designed to suppress thigmotaxis to the maze wall, promoting exploration of the arena. In our moat maze, the poison frogs were able to use a configuration of visual cues to find the hidden platform. Moreover, we demonstrate that they chose direct paths to the goal from multiple random initial positions, a hallmark of a cognitive map. The performance of the frogs in the maze was qualitatively similar to that of rodents, suggesting that the potential to evolve a cognitive map is an evolutionarily conserved trait of vertebrates.

The Central Complex as a Potential Substrate for Vector Based Navigation

Insects use path integration (PI) to maintain a home vector, but can also store and recall vector-memories that take them from home to a food location, and even allow them to take novel shortcuts between food locations. The neural circuit of the Central Complex (a brain area that receives compass and optic flow information) forms a plausible substrate for these behaviors. A recent model, grounded in neurophysiological and neuroanatomical data, can account for PI during outbound exploratory routes and the control of steering to return home. Here, we show that minor, hypothetical but neurally plausible, extensions of this model can additionally explain how insects could store and recall PI vectors to follow food-ward paths, take shortcuts, search at the feeder and re-calibrate their vector-memories with experience. In addition, a simple assumption about how one of multiple vector-memories might be chosen at any point in time can produce the development and maintenance of efficient routes between multiple locations, as observed in bees. The central complex circuitry is therefore well-suited to allow for a rich vector-based navigational repertoire.

Non-Euclidean navigation

A basic set of navigation strategies supports navigational tasks ranging from homing to novel detours and shortcuts. To perform these last two tasks, it is generally thought that humans, mammals and perhaps some insects possess Euclidean cognitive maps, constructed on the basis of input from the path integration system. In this article, I review the rationale and behavioral evidence for this metric cognitive map hypothesis, and find it unpersuasive: in practice, there is little evidence for truly novel shortcuts in animals, and human performance is highly unreliable and biased by environmental features. I develop the alternative hypothesis that spatial knowledge is better characterized as a labeled graph: a network of paths between places augmented with local metric information. What distinguishes such a cognitive graph from a metric cognitive map is that this local information is not embedded in a global coordinate system, so spatial knowledge is often geometrically inconsistent. Human path integration appears to be better suited to piecewise measurements of path lengths and turn angles than to building a consistent map. In a series of experiments in immersive virtual reality, we tested human navigation in non-Euclidean environments and found that shortcuts manifest large violations of the metric postulates. The results are contrary to the Euclidean map hypothesis and support the cognitive graph hypothesis. Apparently Euclidean behavior, such as taking novel detours and approximate shortcuts, can be explained by the adaptive use of non-Euclidean strategies.

The internal maps of insects

Insect navigation is strikingly geometric. Many species use path integration to maintain an accurate estimate of their distance and direction (a vector) to their nest and can store the vector information for multiple salient locations in the world, such as food sources, in a common coordinate system. Insects can also use remembered views of the terrain around salient locations or along travelled routes to guide return, which is a fundamentally geometric process. Recent modelling of these abilities shows convergence on a small set of algorithms and assumptions that appear sufficient to account for a wide range of behavioural data. Notably, this 'base model' does not include any significant topological knowledge: the insect does not need to recover the information (implicit in their vector memory) about the relationships between salient places; nor to maintain any connectedness or ordering information between view memories; nor to form any associations between views and vectors. However, there remains some experimental evidence not fully explained by this base model that may point towards the existence of a more complex or integrated mental map in insects.

Guidance of Navigating Honeybees by Learned Elongated Ground Structures

Elongated landscape features like forest edges, rivers, roads or boundaries of fields are particularly salient landmarks for navigating animals. Here, we ask how honeybees learn such structures and how they are used during their homing flights after being released at an unexpected location (catch-and-release paradigm). The experiments were performed in two landscapes that differed with respect to their overall structure: a rather feature-less landscape, and one rich in close and far distant landmarks. We tested three different forms of learning: learning during orientation flights, learning during training to a feeding site, and learning during homing flights after release at an unexpected site within the explored area. We found that bees use elongated ground structures, e.g., a field boundary separating two pastures close to the hive (Experiment 1), an irrigation channel (Experiment 2), a hedgerow along which the bees were trained (Experiment 3), a gravel road close to the hive and the feeder (Experiment 4), a path along an irrigation channel with its vegetation close to the feeder (Experiment 5) and a gravel road along which bees performed their homing flights (Experiment 6). Discrimination and generalization between the learned linear landmarks and similar ones in the test area depend on their object properties (irrigation channel, gravel road, hedgerow) and their compass orientation. We conclude that elongated ground structures are embedded into multiple landscape features indicating that memory of these linear structures is one component of bee navigation. Elongated structures interact and compete with other references. Object identification is an important part of this process. The objects are characterized not only by their appearance but also by their alignment in the compass. Their salience is highest if both components are close to what had been learned. High similarity in appearance can compensate for (partial) compass misalignment, and vice versa.

The role of attractive and repellent scene memories in ant homing (Myrmecia croslandi)

Solitary foraging ants rely on vision when travelling along routes and when pinpointing their nest. We tethered foragers of Myrmecia croslandi on a trackball and recorded their intended movements when the trackball was located on their normal foraging corridor (on-route), above their nest and at a location several meters away where they have never been before (off-route). We find that at on- and off-route locations, most ants walk in the nest or foraging direction and continue to do so for tens of metres in a straight line. In contrast, above the nest, ants walk in random directions and change walking direction frequently. In addition, the walking direction of ants above the nest oscillates at a fine scale, reflecting search movements that are absent from the paths of ants at the other locations. An agent-based simulation shows that the behaviour of ants at all three locations can be explained by the integration of attractive and repellent views directed towards or away from the nest, respectively. Ants are likely to acquire such views via systematic scanning movements during their learning walks. The model predicts that ants placed in a completely unfamiliar environment should behave as if at the nest, which our subsequent experiments confirmed. We conclude first, that the ants’ behaviour at release sites is exclusively driven by what they currently see and not by information on expected outcomes of their behaviour. Second, that navigating ants might continuously integrate attractive and repellent visual memories. We discuss the benefits of such a procedure.

What is a cognitive map? Unravelling its mystery using robots

Despite years of research into cognitive mapping, the process remains controversial and little understood. A computational theory of cognitive mapping is needed, but developing it is difficult due to the lack of a clear interpretation of the empirical findings. For example, without knowing what a cognitive map is or how landmarks are defined, how does one develop a computational theory for it? We thus face the conundrum of trying to develop a theory without knowing what is computed. In this paper, we overcome the conundrum by abandoning the idea that the process begins by integrating successive views to form a global map of the environment experienced. Instead, we argue that cognitive mapping begins by remembering views as local maps and we empower a mobile robot with the process and study its behaviour as it acquires its "cognitive map". Our results show that what is computed initially could be described as a "route" map and from it, some form of a "survey map" can be computed. The latter, as it turns out, bears much of the characteristics of a cognitive map. Based on our findings, we discuss what a cognitive map is, how cognitive mapping evolves and why such a process also supports the perception of a stable world.

Exploratory behavior of re-orienting foragers differs from other flight patterns of honeybees

Honeybees, Apis mellifera, perform re-orientation flights to learn about the new surroundings of the hive when their hive is transported to a new location. Since the pattern of re-orientation flights has not yet been studied, we asked whether this form of exploratory behavior differs from the well described exploratory orientation flights performed by young honeybees before they start foraging. We also investigated whether the exploratory components of re-orientation flights differ from foraging flights and if so how. We recorded re-orientation flights using harmonic radar technology and compared the patterns and flight parameters of these flights with the first exploratory orientation flights of young honeybees and foraging flights of experienced foragers. Just as exploratory orientation flights of young honeybees, re-orientation flights can be classified into short- and long-range flights, and most short-range re-orientation flights were performed under unfavorable weather conditions. This indicates that bees adapt the flight pattern of their re-orientation and orientation flights to changing weather conditions in a similar way. Unlike exploratory orientation flights, more than one sector of the landscape was explored during a long-range re-orientation flight, and significantly longer flight durations and flight distances were observed. Thus, re-orienting bees explored a larger terrain than bees performing their first exploratory orientation flight. By displacing some bees after their first re-orientation flight, we could demonstrate that a single re-orientation flight seems to be sufficient to learn the new location of the hive. The flight patterns of re-orientation flights differed clearly from those of foraging flights. Thus, re-orientation flights represent a special exploratory behavior that is triggered by a change in the location of the hive.

Human spatial representation: what we cannot learn from the studies of rodent navigation

Studies of human and rodent navigation often reveal a remarkable cross-species similarity between the cognitive and neural mechanisms of navigation. Such cross-species resemblance often overshadows some critical differences between how humans and nonhuman animals navigate. In this review, I propose that a navigation system requires both a storage system (i.e., representing spatial information) and a positioning system (i.e., sensing spatial information) to operate. I then argue that the way humans represent spatial information is different from that inferred from the cellular activity observed during rodent navigation. Such difference spans the whole hierarchy of spatial representation, from representing the structure of an environment to the representation of subregions of an environment, routes and paths, and the distance and direction relative to a goal location. These cross-species inconsistencies suggest that what we learn from rodent navigation does not always transfer to human navigation. Finally, I argue for closing the loop for the dominant, unidirectional animal-to-human approach in navigation research so that insights from behavioral studies of human navigation may also flow back to shed light on the cellular mechanisms of navigation for both humans and other mammals (i.e., a human-to-animal approach).

A neural network model for familiarity and context learning during honeybee foraging flights

How complex is the memory structure that honeybees use to navigate? Recently, an insect-inspired parsimonious spiking neural network model was proposed that enabled simulated ground-moving agents to follow learned routes. We adapted this model to flying insects and evaluate the route following performance in three different worlds with gradually decreasing object density. In addition, we propose an extension to the model to enable the model to associate sensory input with a behavioral context, such as foraging or homing. The spiking neural network model makes use of a sparse stimulus representation in the mushroom body and reward-based synaptic plasticity at its output synapses. In our experiments, simulated bees were able to navigate correctly even when panoramic cues were missing. The context extension we propose enabled agents to successfully discriminate partly overlapping routes. The structure of the visual environment, however, crucially determines the success rate. We find that the model fails more often in visually rich environments due to the overlap of features represented by the Kenyon cell layer. Reducing the landmark density improves the agents route following performance. In very sparse environments, we find that extended landmarks, such as roads or field edges, may help the agent stay on its route, but often act as strong distractors yielding poor route following performance. We conclude that the presented model is valid for simple route following tasks and may represent one component of insect navigation. Additional components might still be necessary for guidance and action selection while navigating along different memorized routes in complex natural environments.

Vision for navigation: What can we learn from ants?

The visual systems of all animals are used to provide information that can guide behaviour. In some cases insects demonstrate particularly impressive visually-guided behaviour and then we might reasonably ask how the low-resolution vision and limited neural resources of insects are tuned to particular behavioural strategies. Such questions are of interest to both biologists and to engineers seeking to emulate insect-level performance with lightweight hardware. One behaviour that insects share with many animals is the use of learnt visual information for navigation. Desert ants, in particular, are expert visual navigators. Across their foraging life, ants can learn long idiosyncratic foraging routes. What's more, these routes are learnt quickly and the visual cues that define them can be implemented for guidance independently of other social or personal information. Here we review the style of visual navigation in solitary foraging ants and consider the physiological mechanisms that underpin it. Our perspective is to consider that robust navigation comes from the optimal interaction between behavioural strategy, visual mechanisms and neural hardware. We consider each of these in turn, highlighting the value of ant-like mechanisms in biomimetic endeavours.

In silico Interrogation of Insect Central Complex Suggests Computational Roles for the Ellipsoid Body in Spatial Navigation

The central complex in the insect brain is a composite of midline neuropils involved in processing sensory cues and mediating behavioral outputs to orchestrate spatial navigation. Despite recent advances, however, the neural mechanisms underlying sensory integration and motor action selections have remained largely elusive. In particular, it is not yet understood how the central complex exploits sensory inputs to realize motor functions associated with spatial navigation. Here we report an in silico interrogation of central complex-mediated spatial navigation with a special emphasis on the ellipsoid body. Based on known connectivity and function, we developed a computational model to test how the local connectome of the central complex can mediate sensorimotor integration to guide different forms of behavioral outputs. Our simulations show integration of multiple sensory sources can be effectively performed in the ellipsoid body. This processed information is used to trigger continuous sequences of action selections resulting in self-motion, obstacle avoidance and the navigation of simulated environments of varying complexity. The motor responses to perceived sensory stimuli can be stored in the neural structure of the central complex to simulate navigation relying on a collective of guidance cues, akin to sensory-driven innate or habitual behaviors. By comparing behaviors under different conditions of accessible sources of input information, we show the simulated insect computes visual inputs and body posture to estimate its position in space. Finally, we tested whether the local connectome of the central complex might also allow the flexibility required to recall an intentional behavioral sequence, among different courses of actions. Our simulations suggest that the central complex can encode combined representations of motor and spatial information to pursue a goal and thus successfully guide orientation behavior. Together, the observed computational features identify central complex circuitry, and especially the ellipsoid body, as a key neural correlate involved in spatial navigation.

Wormholes in virtual space: From cognitive maps to cognitive graphs

Humans and other animals build up spatial knowledge of the environment on the basis of visual information and path integration. We compare three hypotheses about the geometry of this knowledge of navigation space: (a) 'cognitive map' with metric Euclidean structure and a consistent coordinate system, (b) 'topological graph' or network of paths between places, and (c) 'labelled graph' incorporating local metric information about path lengths and junction angles. In two experiments, participants walked in a non-Euclidean environment, a virtual hedge maze containing two 'wormholes' that visually rotated and teleported them between locations. During training, they learned the metric locations of eight target objects from a 'home' location, which were visible individually. During testing, shorter wormhole routes to a target were preferred, and novel shortcuts were directional, contrary to the topological hypothesis. Shortcuts were strongly biased by the wormholes, with mean constant errors of 37° and 41° (45° expected), revealing violations of the metric postulates in spatial knowledge. In addition, shortcuts to targets near wormholes shifted relative to flanking targets, revealing 'rips' (86% of cases), 'folds' (91%), and ordinal reversals (66%) in spatial knowledge. Moreover, participants were completely unaware of these geometric inconsistencies, reflecting a surprising insensitivity to Euclidean structure. The probability of the shortcut data under the Euclidean map model and labelled graph model indicated decisive support for the latter (BF_GM>100). We conclude that knowledge of navigation space is best characterized by a labelled graph, in which local metric information is approximate, geometrically inconsistent, and not embedded in a common coordinate system. This class of 'cognitive graph' models supports route finding, novel detours, and rough shortcuts, and has the potential to unify a range of data on spatial navigation.

Honeybees use the skyline in orientation

In view-based navigation, animals acquire views of the landscape from various locations and then compare the learned views with current views in order to orient in certain directions or move toward certain destinations. One landscape feature of great potential usefulness in view-based navigation is the skyline, the silhouette of terrestrial objects against the sky, as it is distant, relatively stable and easy to detect. The skyline has been shown to be important in the view-based navigation of ants, but no flying insect has yet been shown definitively to use the skyline in this way. Here, we show that honeybees do indeed orient using the skyline. A feeder was surrounded with an artificial replica of the natural skyline there, and the bees' departures toward the nest were recorded from above with a video camera under overcast skies (to eliminate celestial cues). When the artificial skyline was rotated, the bees' departures were rotated correspondingly, showing that the bees oriented by the artificial skyline alone. We discuss these findings in the context of the likely importance of the skyline in long-range homing in bees, the likely importance of altitude in using the skyline, the likely role of ultraviolet light in detecting the skyline, and what we know about the bees' ability to resolve skyline features.

Optimal search patterns in honeybee orientation flights are robust against emerging infectious diseases

Lévy flights are scale-free (fractal) search patterns found in a wide range of animals. They can be an advantageous strategy promoting high encounter rates with rare cues that may indicate prey items, mating partners or navigational landmarks. The robustness of this behavioural strategy to ubiquitous threats to animal performance, such as pathogens, remains poorly understood. Using honeybees radar-tracked during their orientation flights in a novel landscape, we assess for the first time how two emerging infectious diseases (Nosema sp. and the Varroa-associated Deformed wing virus (DWV)) affect bees' behavioural performance and search strategy. Nosema infection, unlike DWV, affected the spatial scale of orientation flights, causing significantly shorter and more compact flights. However, in stark contrast to disease-dependent temporal fractals, we find the same prevalence of optimal Lévy flight characteristics (μ ≈ 2) in both healthy and infected bees. We discuss the ecological and evolutionary implications of these surprising insights, arguing that Lévy search patterns are an emergent property of fundamental characteristics of neuronal and sensory components of the decision-making process, making them robust against diverse physiological effects of pathogen infection and possibly other stressors.

Place recognition using batlike sonar

Echolocating bats have excellent spatial memory and are able to navigate to salient locations using bio-sonar. Navigating and route-following require animals to recognize places. Currently, it is mostly unknown how bats recognize places using echolocation. In this paper, we propose template based place recognition might underlie sonar-based navigation in bats. Under this hypothesis, bats recognize places by remembering their echo signature - rather than their 3D layout. Using a large body of ensonification data collected in three different habitats, we test the viability of this hypothesis assessing two critical properties of the proposed echo signatures: (1) they can be uniquely classified and (2) they vary continuously across space. Based on the results presented, we conclude that the proposed echo signatures satisfy both criteria. We discuss how these two properties of the echo signatures can support navigation and building a cognitive map.

The Australian Bogong Moth Agrotis infusa: A Long-Distance Nocturnal Navigator

The nocturnal Bogong moth (Agrotis infusa) is an iconic and well-known Australian insect that is also a remarkable nocturnal navigator. Like the Monarch butterflies of North America, Bogong moths make a yearly migration over enormous distances, from southern Queensland, western and northwestern New South Wales (NSW) and western Victoria, to the alpine regions of NSW and Victoria. After emerging from their pupae in early spring, adult Bogong moths embark on a long nocturnal journey towards the Australian Alps, a journey that can take many days or even weeks and cover over 1000 km. Once in the Alps (from the end of September), Bogong moths seek out the shelter of selected and isolated high ridge-top caves and rock crevices (typically at elevations above 1800 m). In hundreds of thousands, moths line the interior walls of these cool alpine caves where they “hibernate” over the summer months (referred to as “estivation”). Towards the end of the summer (February and March), the same individuals that arrived months earlier leave the caves and begin their long return trip to their breeding grounds. Once there, moths mate, lay eggs and die. The moths that hatch in the following spring then repeat the migratory cycle afresh. Despite having had no previous experience of the migratory route, these moths find their way to the Alps and locate their estivation caves that are dotted along the high alpine ridges of southeastern Australia. How naïve moths manage this remarkable migratory feat still remains a mystery, although there are many potential sensory cues along the migratory route that moths might rely on during their journey, including visual, olfactory, mechanical and magnetic cues. Here we review our current knowledge of the Bogong moth, including its natural history, its ecology, its cultural importance to the Australian Aborigines and what we understand about the sensory basis of its long-distance nocturnal migration. From this analysis it becomes clear that the Bogong moth represents a new and very promising model organism for understanding the sensory basis of nocturnal migration in insects.

Using an Insect Mushroom Body Circuit to Encode Route Memory in Complex Natural Environments

Ants, like many other animals, use visual memory to follow extended routes through complex environments, but it is unknown how their small brains implement this capability. The mushroom body neuropils have been identified as a crucial memory circuit in the insect brain, but their function has mostly been explored for simple olfactory association tasks. We show that a spiking neural model of this circuit originally developed to describe fruitfly (Drosophila melanogaster) olfactory association, can also account for the ability of desert ants (Cataglyphis velox) to rapidly learn visual routes through complex natural environments. We further demonstrate that abstracting the key computational principles of this circuit, which include one-shot learning of sparse codes, enables the theoretical storage capacity of the ant mushroom body to be estimated at hundreds of independent images.

The memory structure of navigation in honeybees

The analytical approach to navigation studies aims to identify elementary sensory motor processes that guide an animal to a remote site. This approach will be used here to characterize components of navigation in a flying insect, the honeybee. However, navigation studies need to go beyond an analysis of behavioral routines to come up with a synthesis. We will defend the concept of an active memory structure guiding navigation in bees that is best described as a mental or cognitive map. In our opinion, spatial/temporal relations of landmarks are stored in a mental map in such a way that behavioral routines such as expectation and planning, as indicated by shortcutting, are possible. We view the mental map of animals including the honeybee as an "action memory of spatial relations" rather than as a sensory representation as we humans experience it by introspection. Two components characterize the mental map, the relational representation of landmarks and the meaning of locations to the animal. As yet, there is little data to suggest that bees assign meaning to the experienced locations. To explore this possibility, further studies will be needed, whereby honeybees provide a unique model to address this question.