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.
Abstract-Inspired by ant navigation, we explore a method for sky segmentation using ultraviolet (UV) light. A standard camera is adapted to allow collection of outdoor images containing light in the visible range, in UV only and in green only. Automatic segmentation of the sky region using UV only is significantly more accurate and far more consistent than visible wavelengths over a wide range of locations, times and weather conditions, and can be accomplished with a very low complexity algorithm. We apply this method to obtain compact binary (sky vs non-sky) images from panoramic UV images taken along a 2km route in an urban environment. Using either sequence SLAM or a visual compass on these images produces reliable localisation and orientation on a subsequent traversal of the route under different weather conditions.
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.Electronic supplementary materialThe online version of this article (doi:10.1007/s00359-015-1005-8) contains supplementary material, which is available to authorized users.
Ants are known to be capable of homing to their nest after displacement to a novel location. This is widely assumed to involve some form of retinotopic matching between their current view and previously experienced views. One simple algorithm proposed to explain this behavior is continuous retinotopic alignment, in which the ant constantly adjusts its heading by rotating to minimize the pixel-wise difference of its current view from all views stored while facing the nest. However, ants with large prey items will often drag them home while facing backwards. We tested whether displaced ants (Myrmecia croslandi) dragging prey could still home despite experiencing an inverted view of their surroundings under these conditions. Ants moving backwards with food took similarly direct paths to the nest as ants moving forward without food, demonstrating that continuous retinotopic alignment is not a critical component of homing. It is possible that ants use initial or intermittent retinotopic alignment, coupled with some other direction stabilizing cue that they can utilize when moving backward. However, though most ants dragging prey would occasionally look toward the nest, we observed that their heading direction was not noticeably improved afterwards. We assume ants must use comparison of current and stored images for corrections of their path, but suggest they are either able to chose the appropriate visual memory for comparison using an additional mechanism; or can make such comparisons without retinotopic alignment.
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