Route-segment odometry and its interactions with global path-integration

Route retracing: way pointing and multiple vector memories in trail-following ants

Maintaining positional estimates of goal locations is a fundamental task for navigating animals. Diverse animal groups, including both vertebrates and invertebrates, can accomplish this through path integration. During path integration, navigators integrate movement changes, tracking both distance and direction, to generate a spatial estimate of their start location, or global vector, allowing efficient direct return travel without retracing the outbound route. In ants, path integration is accomplished through the coupling of pedometer and celestial compass estimates. Within path integration, it has been theorized navigators may use multiple vector memories for way pointing. However, in many instances, these navigators may instead be homing via view alignment. Here, we present evidence that trail-following ants can attend to segments of their global vector to retrace their non-straight pheromone trails, without the confound of familiar views. Veromessor pergandei foragers navigate to directionally distinct intermediate sites via path integration by orienting along separate legs of their inbound route at unfamiliar locations, indicating these changes are not triggered by familiar external cues, but by vector state. These findings contrast with path integration as a singular memory estimate in ants and underscore the system's ability to way point to intermediate goals along the inbound route via multiple vector memories, akin to trapline foraging in bees visiting multiple flower patches. We discuss how reliance on non-straight pheromone-marked trails may support attending to separate vectors to remain on the pheromone rather than attempting straight-line shortcuts back to the nest.

Pheromone cue triggers switch between vectors in the desert harvest ant, Veromessor pergandei

The desert harvester ant (Veromessor pergandei) employs a mixture of social and individual navigational strategies at separate stages of their foraging trip. Individuals leave the nest along a pheromone-based column, travelling 3-40 m before spreading out to forage individually in a fan. Foragers use path integration while in this fan, accumulating a direction and distance estimate (vector) to return to the end of the column (column head), yet foragers' potential use of path integration in the pheromone-based column is less understood. Here we show foragers rely on path integration both in the foraging fan and while in the column to return to the nest, using separate vectors depending on their current foraging stage in the fan or column. Returning foragers displaced while in the fan oriented and travelled to the column head location while those displaced after reaching the column travel in the nest direction, signifying the maintenance of a two-vector system with separate fan and column vectors directing a forager to two separate spatial locations. Interestingly, the trail pheromone and not the surrounding terrestrial cues mediate use of these distinct vectors, as fan foragers briefly exposed to the pheromone cues of the column in isolation altered their paths to a combination of the fan and column vectors. The pheromone acts as a contextual cue triggering both the retrieval of the column-vector memory and its integration with the forager's current fan-vector.

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.

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.

A Neurocomputational Model of Goal-Directed Navigation in Insect-Inspired Artificial Agents

Despite their small size, insect brains are able to produce robust and efficient navigation in complex environments. Specifically in social insects, such as ants and bees, these navigational capabilities are guided by orientation directing vectors generated by a process called path integration. During this process, they integrate compass and odometric cues to estimate their current location as a vector, called the home vector for guiding them back home on a straight path. They further acquire and retrieve path integration-based vector memories globally to the nest or based on visual landmarks. Although existing computational models reproduced similar behaviors, a neurocomputational model of vector navigation including the acquisition of vector representations has not been described before. Here we present a model of neural mechanisms in a modular closed-loop control—enabling vector navigation in artificial agents. The model consists of a path integration mechanism, reward-modulated global learning, random search, and action selection. The path integration mechanism integrates compass and odometric cues to compute a vectorial representation of the agent's current location as neural activity patterns in circular arrays. A reward-modulated learning rule enables the acquisition of vector memories by associating the local food reward with the path integration state. A motor output is computed based on the combination of vector memories and random exploration. In simulation, we show that the neural mechanisms enable robust homing and localization, even in the presence of external sensory noise. The proposed learning rules lead to goal-directed navigation and route formation performed under realistic conditions. Consequently, we provide a novel approach for vector learning and navigation in a simulated, situated agent linking behavioral observations to their possible underlying neural substrates.

The acquisition and expression of memories of distance and direction in navigating wood ants

Wood ants, like other central place foragers, rely on route memories to guide them to and from a reliable food source. They use visual memories of the surrounding scene and probably compass information to control their direction. Do they also remember the length of their route and do they link memories of direction and distance? To answer these questions, we trained wood ant (Formica rufa) foragers in a channel to perform either a single short foraging route or two foraging routes in opposite directions. By shifting the starting position of the route within the channel, but keeping the direction and distance fixed, we tried to ensure that the ants would rely upon vector memories rather than visual memories to decide when to stop. The homeward memories that the ants formed were revealed by placing fed or unfed ants directly into a channel and assessing the direction and distance that they walked without prior performance of the food-ward leg of the journey. This procedure prevented the distance and direction walked being affected by a home-vector derived from path integration. Ants that were unfed walked in the feeder direction. Fed ants walked in the opposite direction for a distance related to the separation between start and feeder. Vector memories of a return route can thus be primed by the ants' feeding state and expressed even when the ants have not performed the food-ward route. Tests on ants that have acquired two routes indicate that memories of the direction and distance of the return routes are linked, suggesting that these memories may be encoded by a common neural population within the ant brain.