Emergent control of ant learning walks using the mismatch between path-integration and visual cues
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Despite their small brains, desert ants can safely navigate back to their nest after travelling hundreds of metres to find food. This ability relies on visual memories, gathered on initial Learning Walks (LWs), during which ants slowly explore the surroundings of the nest. LWs follow a clear progression: early walks are short, spiraling, and interspersed with pirouettes: brief stops during which the ant perform a visual scan. Successive LWs become straighter and extend farther from the nest, until they transition into foraging trips. However, when the visual panorama changes, LWs reappear. Existing models explain how stored panoramic views can guide homing, but not when visual memories are collected or how LW dynamics are controlled. Here, we propose that a single error signal – generated from the mismatch between the estimated nest direction provided by path integration and visual predictions – scaffolds visual learning and drives LW dynamics. Using 3D reconstructions of desert ant experiments, we show that this mechanism reproduces the main features of LWs, including the transition to foraging and reoccurrence of LWs after environmental change. Our model is biologically plausible and consistent with known insect navigation circuits.
Author summary
A tiny nest entrance in the desert is easy to miss, but doing so may have lethal consequences for a foraging desert ant, returning home after a long scavenging trip. To solve this problem, desert ants spend several days performing Learning walks (LWs) to learn the visual landmarks around their nest before they begin searching for food. LWs are structured active learning procedures and clear patterns can be identified across ant species. LWs take the form of nest-centred spirals, interspersed with frequent visual scans. Over two to four days, LWs become longer, straighter and walking speed increases, before the ant finally transitions to foraging. LWs may reoccur even in experienced foragers, when a new landmark is introduced near the nest.
No previous model has provided a mechanism for how LWs are controlled. Here, we propose that the transition from LWs to foraging is driven by visual familiarity. In our model, unfamiliar surroundings promote learning and exploration; as the visual panorama becomes familiar, behaviour shifts to foraging. Using 3D simulations of experimental layouts, we demonstrate that LWs can emerge from simple rules, and that our simulated agents reproduce the main features of LWs observed in desert ants.
