Sequential learning of relative size by the Neotropical ant Gigantiops destructor

Evidence for the effect of brief exposure to food, but not learning interference, on maze solving in desert ants

Theories of forgetting highlight two active mechanisms through which animals forget prior knowledge by reciprocal disruption of memories. According to "proactive interference", information learned previously interferes with the acquisition of new information, whereas "retroactive interference" suggests that newly gathered information interferes with already existing information. Our goal was to examine the possible effect of both mechanisms in the desert ant Cataglyphis niger, which does not use pheromone recruitment, when learning spatial information while searching for food in a maze. Our experiment indicated that neither proactive nor retroactive interference took place in this system although this awaits confirmation with individual-level learning assays. Rather, the ants' persistence or readiness to search for food grew with successive runs in the maze. Elevated persistence led to more ant workers arriving at the food when retested a day later, even if the maze was shifted between runs. We support this finding in a second experiment, where ant workers reached the food reward at the maze end in higher numbers after encountering food in the maze entry compared to a treatment, in which food was present only at the maze end. This result suggests that spatial learning and search persistence are two parallel behavioral mechanisms, both assisting foraging ants. We suggest that their relative contribution should depend on habitat complexity. This article is protected by copyright. All rights reserved.

A motion compensation treadmill for untethered wood ants (Formica rufa): evidence for transfer of orientation memories from free-walking training

The natural scale of insect navigation during foraging makes it challenging to study under controlled conditions. Virtual reality and trackball setups have offered experimental control over visual environments while studying tethered insects, but potential limitations and confounds introduced by tethering motivates the development of alternative untethered solutions. In this paper, we validate the use of a motion compensator (or ‘treadmill’) to study visually driven behaviour of freely moving wood ants (Formica rufa). We show how this setup allows naturalistic walking behaviour and preserves foraging motivation over long time frames. Furthermore, we show that ants are able to transfer associative and navigational memories from classical maze and arena contexts to our treadmill. Thus, we demonstrate the possibility to study navigational behaviour over ecologically relevant durations (and virtual distances) in precisely controlled environments, bridging the gap between natural and highly controlled laboratory experiments.

Summary: We have developed and validated a motion compensating treadmill for wood ants which opens new perspectives to study insect navigation behaviour in a fully controlled manner over ecologically relevant durations.

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.

Counting insects

When counting-like abilities were first described in the honeybee in the mid-1990s, many scholars were sceptical, but such capacities have since been confirmed in a number of paradigms and also in other insect species. Counter to the intuitive notion that counting is a cognitively advanced ability, neural network analyses indicate that it can be mediated by very small neural circuits, and we should therefore perhaps not be surprised that insects and other small-brained animals such as some small fish exhibit such abilities. One outstanding question is how bees actually acquire numerical information. For perception of small numerosities, working-memory capacity may limit the number of items that can be enumerated, but within these limits, numerosity can be evaluated accurately and (at least in primates) in parallel. However, presentation of visual stimuli in parallel does not automatically ensure parallel processing. Recent work on the question of whether bees can see ‘at a glance’ indicates that bees must acquire spatial detail by sequential scanning rather than parallel processing. We explore how this might be tested for a numerosity task in bees and other animals.

This article is part of a discussion meeting issue ‘The origins of numerical abilities’.

The interplay between maze complexity, colony size, learning and memory in ants while solving a maze: A test at the colony level

Central-place foragers need to explore their immediate habitat in order to reach food. We let colonies of the individually foraging desert ant Cataglyphis niger search for a food reward in a maze. We did so for three tests per day over two successive days and an additional test after a time interval of 4-20 days (seven tests in total). We examined whether the colonies reached the food reward faster, consumed more food and changed the number of workers searching over time, within and between days. Colonies' food-discovery time shortened within and between days, indicating that some workers learnt and became more efficient in moving through the maze. Such workers, however, also forgot and deteriorated in their food-discovery time, leveling off back to initial performance after about two weeks. We used mazes of increasing complexity levels, differing in the potential number of wrong turns. The number of workers searching increased with colony size. Food-discovery time also increased with colony size in complex mazes but not in simple ones, perhaps due to the more frequent interactions among workers in large colonies having to move through narrow routes. Finally, the motivation to solve the maze was probably not only the food reward, because food consumption did not change over time.