Collett et al. propose how long-term memories in the mushroom bodies (mushroom body) are transformed into an insect's guidance commands: mushroom body output on recognising a stimulus acts as a trigger signal for steering circuitry in the central complex (central complex). The central complex then fixes its current sensory inputs as short-term set-points for feedback control of travel direction.

Ants often walk backwards to drag large prey to their nest. New experiments show how they can use information from retinotopically encoded views to follow visual routes even while moving backwards. The mechanisms enabling ants to decouple body orientation and the control of travel direction are likely to be shared with other, flying, insects.

The discovery of translational optic flow detectors in the central complex of a bee has inspired a new model of path integration.

Insects such as desert ants and honeybees use visual memories to travel along familiar routes between their nest and a food-site. We trained Cataglyphis fortis foragers along a two-segment route to investigate whether they encode the lengths of route segments over which visual cues remain approximately constant. Our results support earlier studies suggesting that such route-segment odometry exists, and allows an individual to stop using a visual route memory at an appropriate point, even in the absence of any change in the visual surroundings. But we find that the behavioural effects of route-segment odometry are often complicated by interactions with guidance from the global path-integration system. If route-segment odometry and path-integration agree, they act together to produce a precise signal for search. If the endpoint of route-segment odometry arrives first, it does not trigger search but its effect can persist and cause guidance by path-integration to end early. Conversely, if ants start with their path-integration state at zero, they follow a route memory for no more than 3 m, irrespective of the route-segment length. A possible explanation for these results is that if one guidance system is made to overshoot its endpoint, it can cause the other to be cut short.

© 2014 the Author(s) Published by the Royal Society. All rights reserved.Insects such as desert ants learn stereotyped visual routes between their nests and reliable food sites. Studies here reveal an important control element for ensuring that the route memories are used appropriately. They find that visual route memories can be disengaged, so that they do not provide guidance, even when all appropriate visual cues are present and when there are no competing guidance cues. Ants were trained along a simple route dominated by a single isolated landmark. If returning ants were caught just before entering the nest and replaced at the feeder, then they often interrupted the recapitulation of their homeward route with a period of apparent confusion during which the route memories were ignored. A series of experiments showed that this confusion occurred in response to the repetition of the route, and that the ants must therefore maintain some kind of a memory of their visual experience on the current trip home. A conceptual model of route guidance is offered to explain the results here. It proposes how the memory might act and suggests a general role for disengagement in regulating route guidance.

Insects such as desert ants learn stereotyped visual routes between their nests and reliable food sites. Studies here reveal an important control element for ensuring that the route memories are used appropriately. They find that visual route memories can be disengaged, so that they do not provide guidance, even when all appropriate visual cues are present and when there are no competing guidance cues. Ants were trained along a simple route dominated by a single isolated landmark. If returning ants were caught just before entering the nest and replaced at the feeder, then they often interrupted the recapitulation of their homeward route with a period of apparent confusion during which the route memories were ignored. A series of experiments showed that this confusion occurred in response to the repetition of the route, and that the ants must therefore maintain some kind of a memory of their visual experience on the current trip home. A conceptual model of route guidance is offered to explain the results here. It proposes how the memory might act and suggests a general role for disengagement in regulating route guidance.

Desert ants have a sequence of optimized behaviours that allow them to forage efficiently. Recent work shows that after using navigational memories to reach previously rewarding areas, ants follow long crosswind sweeps that appear adapted for encountering odour plumes.

A wide variety of insects use spatial memories in behaviours like holding a position in air or flowing water, in returning to a place of safety, and in foraging. The Hymenoptera, in particular, have evolved life-histories requiring reliable spatial memories to support the task of provisioning their young. Behavioural experiments, primarily on social bees and ants, reveal the mechanisms by which these memories are employed for guidance to spatial goals and suggest how the memories, and the processing streams that use them, may be organized. We discuss three types of memory-based guidance which, together, can explain a large part of observed insect spatial behaviour. Two of these, alignment image-matching and positional image-matching, are based on an insect's remembered views of its surroundings: the first uses views to keep to a familiar heading and the second to head towards a familiar place. The third type of guidance is based on a process of path integration by which an insect monitors its distance and direction from its nest through odometric and compass information. To a large degree, these guidance mechanisms appear to involve modular computational systems. We discuss the lack of evidence for cognitive maps in insects, and in particular the evidence against a map based on path integration, in which view-based and path integration memories might be combined. We suggest instead that insects have a collective of separate guidance systems, which cooperate and train each other, and together provide reliable guidance over a range of conditions.

Animals use information from multiple sources in order to navigate between goals. Ants such as Cataglyphis fortis use an odometer and a sun-based compass to provide input for path integration (PI). They also use configurations of visual features to learn both goal locations and habitual routes to the goals. Information is not combined into a unified representation but appears to be exploited by separate expert guidance systems. Visual and PI goal memories are acquired rapidly and provide the consistency for route memories to be formed. Do established route memories then suppress the guidance from PI? a series of manipulations putting PI and route memories into varying levels of conflict found that ants follow compromise trajectories. The guidance systems are therefore active together and share the control of behavior. Route memories do not suppress the other guidance systems. A simple model shows that observed patterns of control could arise from a superposition of the output commands from the guidance systems, potentially approximating Bayesian inference. These results help show how an insect's relatively simple decision-making can produce navigation that is reliable and efficient and that also adapts to changing demands.

Many animals learn to follow habitual routes between important locations, but how they encode their routes is still largely unknown. Desert ants traveling between their nest and a food site develop stable, visually guided routes that can wind through desert scrub without the use of trail pheromones. Their route memories are sufficiently robust that if a nest-bound ant is caught at the end of its route and replaced somewhere earlier along it, the ant will recapitulate the route from the release site. Insects appear to use panoramas to recognize when they are on a familiar route. I examine here the cues then used for their guidance. Several mechanisms are known for straight segments of a route; but how does an ant encode a curved route along which both the views it sees, and the directions it takes, are constantly changing? the results here suggest that when an ant travels past a landmark on a familiar route, it uses the gradually changing direction of the landmark to trigger a set of associated learned heading directions. A route through a complex 2D environment could thus be encoded and followed economically if it is divided into panorama-defined segments, with each segment controlled by such a 1D mapping. The solution proposed for the ants would be simple to implement in an autonomous robot.

While foraging, the desert ant Cataglyphis fortis keeps track of its position with respect to its nest through a process of path integration (PI). Once it finds food, it can then follow a direct home vector to its nest. Furthermore, it remembers the coordinates of a food site, and uses these coordinates to return to the site. Previous studies suggest, however, that it does not associate any coordinates remembered from previous trips with familiar views such that it can produce a home vector when displaced to a familiar site. We ask here whether a desert ant uses any association between PI coordinates and familiar views to ensure consistent PI coordinates as it travels along a habitual route. We describe an experiment in which we manipulated the PI coordinates an ant has when reaching a distinctive point along a habitual route on the way to a feeder. The subsequent home vectors of the manipulated ants, when displaced from the food-site to a test ground, show that also when a route memory is evoked at a significant point on the way to a food site, C. fortis does not reset its PI coordinates to those it normally has at that point. We use this result to argue that local vector memories, which encode the metric properties of a segment of a habitual route, must be encoded in a route-based coordinate system that is separate from the nest-based global coordinates. We propose a model for PI-based guidance that can account for several puzzling observations, and that naturally produces the route-based coordinate system required for learning and following local vectors.

The migratory movements of seabirds (especially smaller species) remain poorly understood, despite their role as harvesters of marine ecosystems on a global scale and their potential as indicators of ocean health. Here we report a successful attempt, using miniature archival light loggers (geolocators), to elucidate the migratory behaviour of the Manx shearwater Puffinus puffinus, a small (400 g) Northern Hemisphere breeding procellariform that undertakes a trans-equatorial, trans-Atlantic migration. We provide details of over-wintering areas, of previously unobserved marine stopover behaviour, and the long-distance movements of females during their pre-laying exodus. Using salt-water immersion data from a subset of loggers, we introduce a method of behaviour classification based on Bayesian machine learning techniques. We used both supervised and unsupervised machine learning to classify each bird's daily activity based on simple properties of the immersion data. We show that robust activity states emerge, characteristic of summer feeding, winter feeding and active migration. These can be used to classify probable behaviour throughout the annual cycle, highlighting the likely functional significance of stopovers as refuelling stages.

The desert ant Cataglyphis fortis has at least three types of navigational strategy that can guide it between its nest and a familiar food site. The initial strategy after first finding a food site is based on a path integration memory of the position of the food site with respect to the nest. A second strategy is based on visual snapshot memories of features viewed from near or on the way to the food site. A third strategy uses local vector memories of the direction and length of habitual route segments. We show here that while such local vectors encode sufficient information to guide an individual along both the direction and distance of a route segment, its acquisition and long-term maintenance requires support from the other two strategies. We trained ants along an L-shaped route, designed to show that ants can learn local vectors on the way to a food site. The sharp turn appears to present particular difficulties for the ants. When low bushes 20-30 m from the route were removed, local vectors were briefly unaffected, but then deteriorated. The vectors improved again once the missing bushes were replaced by artificial landmarks. The fragility of local vector memories may permit an ant the flexibility to adapt its route to fluctuations in the distribution of its resources.

Walking insects probably monitor leg movements to estimate how far they travel, whereas flying insects monitor optic flow.

It is often suggested that animals may link landmark memories to a global coordinate system provided by path integration, thereby obtaining a map-like representation of familiar terrain. In an attempt to discover if desert ants form such associations we have performed experiments that test whether desert ants recall a long-term memory of a global path integration vector on arriving at a familiar food site. Ants from three nests were trained along L-shaped routes to a feeder. Each route was entirely within open-topped channels that obscured all natural landmarks. Conspicuous artificial landmarks were attached to the channelling that formed the latter part of the route. The homeward vectors of ants accustomed to the route were tested with the foodward route, either as in training, or with the first leg of the L shortened or extended. These ants were taken from the feeder to a test area and released, whereupon they performed a home vector. If travelling the latter part of a familiar route and arriving at a familiar food site triggers the recall of an accustomed home vector, then the home vector should be the same under both test conditions. We find instead that the home vector tended to reflect the immediately preceding outward journey. In conjunction with earlier work, these experiments led us to conclude in the case of desert ants that landmark memories do not prime the recall of long-term global path integration memories. On the other hand, landmark memories are known to be linked to local path integration vectors that guide ants along a segment of a route. Landmarks thus seem to provide procedural information telling ants what action to perform next but not the positional information that gives an ant its location relative to its nest.

The navigational strategies that are used by foraging ants and bees to reach a goal are similar to those of birds and mammals. Species from all these groups use path integration and memories of visual landmarks to navigate through familiar terrain. Insects have far fewer neural resources than vertebrates, so data from insects might be useful in revealing the essential components of efficient navigation. Recent work on ants and bees has uncovered a major role for associative links between long-term memories. We emphasize the roles of these associations in the reliable recognition of visual landmarks and the reliable performance of learnt routes. It is unknown whether such associations also provide insects with a map-like representation of familiar terrain. We suggest, however, that landmarks act primarily as signposts that tell insects what particular action they need to perform, rather than telling them where they are.

Bees seem to use landmarks to segment familiar routes. They can associate, with a landmark, a memory that encodes the direction and distance of the path segment between that landmark and the next. The expression of the memory results in the performance of a local vector matching the distance and direction of the path segment. The memories of path segments appear to be 'chained' together, so that the performance of one local vector is sometimes sufficient to elicit the subsequent local vector, even in the absence of the associated landmark. We have investigated the effect of visual panoramic context on the expression of local vectors. Bees were trained to fly along a narrow channel to collect sucrose from a feeder positioned partway along it. Panoramic context was provided by various types of patterning on the walls. The channel was partitioned into different segments using landmarks of two kinds: a boundary landmark that marked a change in the pattern on one or both side-walls of the channel, and an isolated landmark, consisting of a baffle through which the bee passed, for which the wall pattern was the same before as after. In tests, we removed the feeder and analysed the search distribution of the bees for various arrangements of landmarks. Altering the spatial relationship between landmarks has different consequences for the two types of landmark. If the final boundary landmark is shifted, the centre of the search distribution shifts by approximately the same amount. Changes in the position of an isolated landmark have a weaker effect. In the absence of the final context, the search is disrupted. We suggest that for local vectors to be expressed the surrounding panoramic context needs to be appropriate. A comparison of search patterns from two different training configurations of landmarks supports the hypothesis that local vector memories merely encode route segments and that global positional coordinates are not linked to landmark memories.

Desert ants (Cataglyphis fortis) were trained to follow a fixed route around a barrier to a feeder. Their homeward trajectories were recorded on a test field containing a similar barrier, oriented either as in training or rotated through 22 or 45. Under one set of experimental conditions, the homeward trajectories rotated with the orientation of the barrier, implying that the visual features of this extended landmark can determine the route independently of compass cues: the barrier provided a "visual scene" that controlled the trajectories of the ants. Under other conditions, the trajectories after rotation were a compromise between the habitual compass direction and the direction with respect to the rotated barrier. Trajectories were determined primarily by the visual scene when ants were allowed to return close to the nest before being caught and tested. The compromise trajectories were observed when ants were taken from the feeder. It seems that ants exhibit at least two separate learnt responses to the barrier: (i) a habitual compass direction triggered by the sight of the barrier and (ii) a visual scene direction that is compass-independent. We suggest that the weighting accorded to these different learnt responses changes with the state of the path integration system.

We combine experimental findings on ants and bees, and build on earlier models, to give an account of how these insects navigate using path integration, and how path integration interacts with other modes of navigation. At the core of path integration is an accumulator. This is set to an initial state at the nest and is updated as the insect moves so that it always reports the insect's current position relative to the nest. Navigation that uses path integration requires, in addition, a way of storing states of the accumulator at significant places for subsequent recall as goals, and a means of computing the direction to such goals. We discuss three models of how path integration might be used for this process, which we call vector navigation. Vector navigation is the principal means of navigating over unfamiliar terrain, or when landmarks are unavailable. Under other conditions, insects often navigate by landmarks, and ignore the output of the vector navigation system. Landmark navigation does not interfere with the updating of the accumulator. There is an interesting symmetry in the use of landmarks and path integration. In the short term, vector navigation can be independent of landmarks, and landmark navigation needs no assistance from path integration. In the longer term, visual landmarks help keep path vector navigation calibrated, and the learning of visual landmarks is guided by path integration.

The most notable advance in our knowledge of path integration in insects is a new understanding of how the honeybee measures the distance that it travels during its foraging trips. Data from two groups show that the bee's odometer records distance in terms of the net amount of image motion over the retina that is accumulated during a flight. Progress has also been made in clarifying the relation between path integration and other navigational strategies. On unfamiliar ground, path integration is the only available means of navigation. In familiar surroundings, however, guidance by landmarks may override guidance by path integration. Path integration then becomes a back-up strategy that is used primarily when landmarks fail.

Desert locusts (Schistocerca gregaria) change phase in response to population density: 'solitarious' insects avoid one another, but when crowded they shift to the gregarious phase and aggregate. This individual-level process is the basis for population-level responses that may ultimately include swarm formation. We have recently developed an individual-based model of locust behavior in which contagious resource distribution leads to phase change. This model shows how population gregarization can result from simple processes operating at the individual level. In the present study, we performed a series of laboratory experiments in which vegetation pattern and locust phase state were assigned quantitative, measurable indices. The pattern of distribution of the resource was represented via fractal dimension; the phase state was evaluated using a behavioral assay based on logistic regression analysis. Locusts were exposed to different patterns of food resource in an artificial arena, after which their behavioral phase state was assayed. These experiments showed that when the distribution of the vegetation was patchy, locusts were more active, experienced higher levels of crowding, and became more gregarious. These results are consistent with simulation predictions and field observations, and demonstrate that small-scale vegetation distribution influences individual behavior and phase state and plays a role in population-level responses.

Desert ants (Cataglyphis sp.) monitor their position relative to the nest using a form of dead reckoning [1] [2] [3] known as path integration (PI) [4]. They do this with a sun compass and an odometer to update an accumulator that records their current position [1]. Ants can use PI to return to the nest [2] [3]. Here, we report that desert ants, like honeybees [5] and hamsters [6], can also use PI to approach a previously visited food source. To navigate to a goal using only PI information, a forager must recall a previous state of the accumulator specifying the goal, and compare it with the accumulator's current state [4]. The comparison - essentially vector subtraction - gives the direction to the goal. This whole process, which we call vector navigation, was found to be calibrated at recognised sites, such as the nest and a familiar feeder, throughout the life of a forager. If a forager was trained around a one-way circuit in which the result of PI on the return route did not match the result on the outward route, calibration caused the ant's trajectories to be misdirected. We propose a model of vector navigation to suggest how calibration could produce such trajectories.

Central to swarm formation in migratory locusts is a crowding-induced change from a "solitarious" to a "gregarious" phenotype. This change can occur within the lifetime of a single locust and accrues across generations. It represents an extreme example of phenotypic plasticity. We present computer simulations and a laboratory experiment that show how differences in resource distributions, conspicuous only at small spatial scales, can have significant effects on phase change at the population level; local spatial concentration of resource induces gregarization. Simulations also show that populations inhabiting a locally concentrated resource tend to change phase rapidly and synchronously in response to altered population densities. Our results show why information about the structure of resource at small spatial scales should become key components in monitoring and control strategies.