Looking and homing: how displaced ants decide where to go

Three spectrally distinct photoreceptors in diurnal and nocturnal Australian ants

Ants are thought to be special among Hymenopterans in having only dichromatic colour vision based on two spectrally distinct photoreceptors. Many ants are highly visual animals, however, and use vision extensively for navigation. We show here that two congeneric day- and night-active Australian ants have three spectrally distinct photoreceptor types, potentially supporting trichromatic colour vision. Electroretinogram recordings show the presence of three spectral sensitivities with peaks (λmax) at 370, 450 and 550 nm in the night-active Myrmecia vindex and peaks at 370, 470 and 510 nm in the day-active Myrmecia croslandi. Intracellular electrophysiology on individual photoreceptors confirmed that the night-active M. vindex has three spectral sensitivities with peaks (λmax) at 370, 430 and 550 nm. A large number of the intracellular recordings in the night-active M. vindex show unusually broad-band spectral sensitivities, suggesting that photoreceptors may be coupled. Spectral measurements at different temporal frequencies revealed that the ultraviolet receptors are comparatively slow. We discuss the adaptive significance and the probability of trichromacy in Myrmecia ants in the context of dim light vision and visual navigation.

Ant Homing Ability Is Not Diminished When Traveling Backwards

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.

Head roll stabilisation in the nocturnal bull ant Myrmecia pyriformis: implications for visual navigation

Ant foragers are known to memorise visual scenes that allow them to repeatedly travel along idiosyncratic routes and to return to specific places. Guidance is provided by a comparison between visual memories and current views, which critically depends on how well the attitude of the visual system is controlled. Here we show that nocturnal bull ants stabilise their head to varying degrees against locomotion-induced body roll movements, and this ability decreases as light levels fall. There are always un-compensated head roll oscillations that match the frequency of the stride cycle. Head roll stabilisation involves both visual and non-visual cues as ants compensate for body roll in complete darkness and also respond with head roll movements when confronted with visual pattern oscillations. We show that imperfect head roll control degrades navigation-relevant visual information and discuss ways in which navigating ants may deal with this problem.

Private information alone can trigger trapping of ant colonies in local feeding optima

Ant colonies are famous for using trail pheromones to make collective decisions. Trail pheromone systems are characterised by positive feedback, which results in rapid decision making. However, in an iconic experiment ants were shown to become ‘trapped’ in exploiting a poor food source, if it was discovered earlier. This has conventionally been explained by the established pheromone trail becoming too strong for new trails to compete. However, many social insects have a well-developed memory, and private information often overrules conflicting social information. Thus, route memory could also explain this collective ‘trapping’ effect. Here we disentangle the effects of social and private information in two ‘trapping’ experiments; one in which ants are presented a good and poor food source, and one in which ants are presented a long and short path to the same food source. We find that private information is sufficient to trigger trapping in selecting the poorer of two food sources, and may be sufficient to cause it altogether. Memories did not trigger trapping in the shortest path experiment, likely as sufficiently detailed memories did not form. The fact that collective decisions can be triggered by private information alone may require other collective patterns previously attributed solely to social information use to be reconsidered.

How do field of view and resolution affect the information content of panoramic scenes for visual navigation? A computational investigation

The visual systems of animals have to provide information to guide behaviour and the informational requirements of an animal's behavioural repertoire are often reflected in its sensory system. For insects, this is often evident in the optical array of the compound eye. One behaviour that insects share with many animals is the use of learnt visual information for navigation. As ants are expert visual navigators it may be that their vision is optimised for navigation. Here we take a computational approach in asking how the details of the optical array influence the informational content of scenes used in simple view matching strategies for orientation. We find that robust orientation is best achieved with low-resolution visual information and a large field of view, similar to the optical properties seen for many ant species. A lower resolution allows for a trade-off between specificity and generalisation for stored views. Additionally, our simulations show that orientation performance increases if different portions of the visual field are considered as discrete visual sensors, each giving an independent directional estimate. This suggests that ants might benefit by processing information from their two eyes independently.

A Bio-inspired Collision Avoidance Model Based on Spatial Information Derived from Motion Detectors Leads to Common Routes

Avoiding collisions is one of the most basic needs of any mobile agent, both biological and technical, when searching around or aiming toward a goal. We propose a model of collision avoidance inspired by behavioral experiments on insects and by properties of optic flow on a spherical eye experienced during translation, and test the interaction of this model with goal-driven behavior. Insects, such as flies and bees, actively separate the rotational and translational optic flow components via behavior, i.e. by employing a saccadic strategy of flight and gaze control. Optic flow experienced during translation, i.e. during intersaccadic phases, contains information on the depth-structure of the environment, but this information is entangled with that on self-motion. Here, we propose a simple model to extract the depth structure from translational optic flow by using local properties of a spherical eye. On this basis, a motion direction of the agent is computed that ensures collision avoidance. Flying insects are thought to measure optic flow by correlation-type elementary motion detectors. Their responses depend, in addition to velocity, on the texture and contrast of objects and, thus, do not measure the velocity of objects veridically. Therefore, we initially used geometrically determined optic flow as input to a collision avoidance algorithm to show that depth information inferred from optic flow is sufficient to account for collision avoidance under closed-loop conditions. Then, the collision avoidance algorithm was tested with bio-inspired correlation-type elementary motion detectors in its input. Even then, the algorithm led successfully to collision avoidance and, in addition, replicated the characteristics of collision avoidance behavior of insects. Finally, the collision avoidance algorithm was combined with a goal direction and tested in cluttered environments. The simulated agent then showed goal-directed behavior reminiscent of components of the navigation behavior of insects.

Visual scanning behaviours and their role in the navigation of the Australian desert ant Melophorus bagoti

Ants are excellent navigators, using a combination of innate strategies and learnt information to guide habitual routes. The mechanisms underlying this behaviour are little understood though one avenue of investigation is to explore how innate sensori-motor routines are used to accomplish route navigation. For instance, Australian desert ant foragers are occasionally observed to cease translation and rotate on the spot. Here, we investigate this behaviour using high-speed videography and computational analysis. We find that scanning behaviour is saccadic with pauses separated by fast rotations. Further, we have identified four situations where scanning is typically displayed: (1) by naïve ants on their first departure from the nest; (2) by experienced ants departing from the nest for their first foraging trip of the day; (3) by experienced ants when the familiar visual surround was experimentally modified, in which case frequency and duration of scans were proportional to the degree of modification; (4) when the information from visual cues is at odds with the direction indicated by the ant's path integration system. Taken together, we see a general relationship between scanning behaviours and periods of uncertainty.