| Abstract |
Some ants follow long, visually guided foraging routes. Study of their route following shows that they acquire multiple visual memories, retrieve them appropriately during the route and guide their paths with this stored visual information. We will improve our understanding of these processes by analysing landmark guidance on a moment-by-moment basis. For this purpose, we have developed a route along which ants guide themselves by means of a single visual feature that we can perturb at defined points during their path. A video-tracking camera gives a precise record of the ant's path and its body orientation, and lets us infer the landmark's position on the ant's retina. This methodology also opens to experiment a neglected but significant aspect of landmark guidance. Ants are so close to the ground that small bumps will frequently obscure their view of guiding landmarks so that they must be able to maintain a path with only intermittent access to visual input. How do ants navigate over uneven terrain? The information that we will obtain by recording the ant's behavioural responses to landmark perturbations will bring us closer to the underlying mechanisms of visual guidance, and so will be of use to neuroscientists and to computer scientists working on the navigation of autonomous robots. We have found that ants will learn a straight route to food placed at the base of a black-white vertical edge, where the black side fades slowly into the white of the walls of the surrounding experimental arena. In this case, the ant's visual task is simply to keep the edge at the front of the eye throughout its approach. Ants will also learn a straight route to food placed at a short distance to the side of the edge. This task is more taxing as the desired retinal position of the edge shifts from the front towards the periphery of the eye during the ant's approach. Our data suggest that the ant stores a sequence of visual memories (the desired positions of the edge on its retina), and that during its route it retrieves the appropriate memory and guides itself by moving to place the edge at the currently desired retinal position. The retrieval of particular desired edge positions seems to be cued by the gradient's apparent width, a visual parameter that increases reliably during the ant's approach and so can provide a robust retrieval signal. Perturbation studies with gradient edges displayed on an LCD screen will give us data to test and improve these hypotheses. The ant's reaction to abrupt changes in the position of the edge should reveal the current desired retinal position as the null point, where there is a switch in the direction of the ant's corrective response to perturbations of different magnitudes and directions. We will map how the desired edge position changes along the route. Does it change continuously or in a step-wise manner, as predicted by a sequence of discrete memories? By altering the width of the gradient, but keeping edge position constant, we can see whether the ant's desired edge position shifts as predicted by the notion that the width of the gradient determines the ant's currently active memory. Similar experiments can tell us how ants cope with intermittent visual input and the role of motor learning in this process. Thus, we expect ants to show 'inertia' and continue towards the goal for a while after the edge is made to disappear. The learning of a motor trajectory should show itself as inertial effects that increase with experience and an increased sluggishness when the ant tracks oscillating edges. Stronger evidence for trajectory learning will be sought by training ants to perform curved trajectories to an edge that always moves during their approach and examining the curvature of the path when the edge vanishes. To explore how ants behave in more natural conditions, we will analyse landmark guidance when ants walk over bumpy ground. |
