How variation in head pitch could affect image matching algorithms for ant navigation

Desert ants are a model system for animal navigation, using visual memory to follow long routes across both sparse and cluttered environments. Most accounts of this behaviour assume retinotopic image matching, e.g. recovering heading direction by finding a minimum in the image difference function as the viewpoint rotates. But most models neglect the potential image distortion that could result from unstable head motion. We report that for ants running across a short section of natural substrate, the head pitch varies substantially: by over 20 degrees with no load; and 60 degrees when carrying a large food item. There is no evidence of head stabilisation. Using a realistic simulation of the ant’s visual world, we demonstrate that this range of head pitch significantly degrades image matching. The effect of pitch variation can be ameliorated by a memory bank of densely sampled along a route so that an image sufficiently similar in pitch and location is available for comparison. However, with large pitch disturbance, inappropriate memories sampled at distant locations are often recalled and navigation along a route can be adversely affected. Ignoring images obtained at extreme pitches, or averaging images over several pitches, does not significantly improve performance

Using an insect mushroom body circuit to encode route memory in complex natural environments

Ants, like many other animals, use visual memory to follow extended routes through complex environments, but it is unknown how their small brains implement this capability. The mushroom body neuropils have been identified as a crucial memory circuit in the insect brain, but their function has mostly been explored for simple olfactory association tasks. We show that a spiking neural model of this circuit originally developed to describe fruitfly (Drosophila melanogaster) olfactory association, can also account for the ability of desert ants (Cataglyphis velox) to rapidly learn visual routes through complex natural environments. We further demonstrate that abstracting the key computational principles of this circuit, which include one-shot learning of sparse codes, enables the theoretical storage capacity of the ant mushroom body to be estimated at hundreds of independent images

Radio tagging reveals the roles of corpulence, experience and social information in ant decision making

Ant colonies are factories within fortresses (Oster and Wilson 1978). They run on resources foraged from an outside world fraught with danger. On what basis do individual ants decide to leave the safety of the nest? We investigated the relative roles of social information (returning nestmates), individual experience and physiology (lipid stores/corpulence) in predicting which ants leave the nest and when. We monitored Temnothorax albipennis workers individually using passive radio-frequency identification technology, a novel procedure as applied to ants. This method allowed the matching of individual corpulence measurements to activity patterns of large numbers of individuals over several days. Social information and physiology are both good predictors of when an ant leaves the nest. Positive feedback from social information causes bouts of activity at the colony level. When certain social information is removed from the system by preventing ants returning, physiology best predicts which ants leave the nest and when. Individual experience is strongly related to physiology. A small number of lean individuals are responsible for most external trips. An individual's nutrient status could be a useful cue in division of labour, especially when public information from other ants is unavailable. © 2008 Springer-Verlag