ABSTRACT
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.
Footnotes
Author contributions
Conceptualization: L.C., S.S., A.W.; Methodology: L.C., S.S., B.M.-C., A.W.; Validation: A.W.; Formal analysis: L.C.; Investigation: L.C., S.S., B.M.-C., A.W.; Writing – original draft: L.C., A.W.; Writing – review & editing: L.C., S.S., B.M.-C., A.W.; Visualization: L.C.; Supervision: A.W.; Project administration: A.W.; Funding acquisition: A.W.
Funding
Funding was provided by European Research Council [EMERG-ANT 759817 to A.W.].
Data availability
Data are available at: https://github.com/ClementLe0/DATA_Is-this-scenery-worth-exploring-Insight-into-the-visual-encoding-of-navigating-ants_JEB.