Not seeing the forest for the trees: combination of path integration and landmark cues in human virtual navigation.

Introduction: In order to successfully move from place to place, our brain often combines sensory inputs from various sources by dynamically weighting spatial cues according to their reliability and relevance for a given task. Two of the most important cues in navigation are the spatial arrangement of landmarks in the environment, and the continuous path integration of travelled distances and changes in direction. Several studies have shown that Bayesian integration of cues provides a good explanation for navigation in environments dominated by small numbers of easily identifiable landmarks.

The Virtual Navigation Toolbox: Providing tools for virtual navigation experiments.

Spatial navigation research in humans increasingly relies on experiments using virtual reality (VR) tools, which allow for the creation of highly flexible, and immersive study environments, that can react to participant interaction in real time. Despite the popularity of VR, tools simplifying the creation and data management of such experiments are rare and often restricted to a specific scope-limiting usability and comparability. To overcome those limitations, we introduce the Virtual Navigation Toolbox (VNT), a collection of interchangeable and independent tools for the development of spatial navigation VR experiments using the popular Unity game engine.

The effect of optic flow cues on honeybee flight control in wind.

To minimize the risk of colliding with the ground or other obstacles, flying animals need to control both their ground speed and ground height. This task is particularly challenging in wind, where head winds require an animal to increase its airspeed to maintain a constant ground speed and tail winds may generate negative airspeeds, rendering flight more difficult to control. In this study, we investigate how head and tail winds affect flight control in the honeybee , which is known to rely on the pattern of visual motion generated across the eye-known as optic flow-to maintain constant ground speeds and heights.

Neural basis of forward flight control and landing in honeybees.

The impressive repertoire of honeybee visually guided behaviors, and their ability to learn has made them an important tool for elucidating the visual basis of behavior. Like other insects, bees perform optomotor course correction to optic flow, a response that is dependent on the spatial structure of the visual environment. However, bees can also distinguish the speed of image motion during forward flight and landing, as well as estimate flight distances (odometry), irrespective of the visual scene.

Finding Home: Landmark Ambiguity in Human Navigation.

Memories of places often include landmark cues, i.e., information provided by the spatial arrangement of distinct objects with respect to the target location.

How Wasps Acquire and Use Views for Homing.

Nesting insects perform learning flights to establish a visual representation of the nest environment that allows them to subsequently return to the nest. It has remained unclear when insects learn what during these flights, what determines their overall structure, and, in particular, how what is learned is used to guide an insect's return. We analyzed learning flights in ground-nesting wasps (Sphecidae: Cerceris australis) using synchronized high-speed cameras to determine 3D head position and orientation.

Going round the bend: Persistent personal biases in walked angles.

For navigation through our environment, we can rely on information from various modalities, such as vision and audition. This information enables us for example to estimate our position relative to the starting position, or to integrate velocity and acceleration signals from the vestibular organ and proprioception to estimate the displacement due to self-motion. To better understand the mechanisms that underlie human navigation we analysed the performance of participants in an angle-walking task in the absence of visual and auditory signals.

Bumblebee Homing: The Fine Structure of Head Turning Movements.

Changes in flight direction in flying insects are largely due to roll, yaw and pitch rotations of their body. Head orientation is stabilized for most of the time by counter rotation. Here, we use high-speed video to analyse head- and body-movements of the bumblebee Bombus terrestris while approaching and departing from a food source located between three landmarks in an indoor flight-arena.

Visual motion-sensitive neurons in the bumblebee brain convey information about landmarks during a navigational task.

Bees use visual memories to find the spatial location of previously learnt food sites. Characteristic learning flights help acquiring these memories at newly discovered foraging locations where landmarks-salient objects in the vicinity of the goal location-can play an important role in guiding the animal's homing behavior. Although behavioral experiments have shown that bees can use a variety of visual cues to distinguish objects as landmarks, the question of how landmark features are encoded by the visual system is still open.

A universal strategy for visually guided landing.

Landing is a challenging aspect of flight because, to land safely, speed must be decreased to a value close to zero at touchdown. The mechanisms by which animals achieve this remain unclear. When landing on horizontal surfaces, honey bees control their speed by holding constant the rate of front-to-back image motion (optic flow) generated by the surface as they reduce altitude.

Spatial vision in insects is facilitated by shaping the dynamics of visual input through behavioral action.

Insects such as flies or bees, with their miniature brains, are able to control highly aerobatic flight maneuvres and to solve spatial vision tasks, such as avoiding collisions with obstacles, landing on objects, or even localizing a previously learnt inconspicuous goal on the basis of environmental cues. With regard to solving such spatial tasks, these insects still outperform man-made autonomous flying systems. To accomplish their extraordinary performance, flies and bees have been shown by their characteristic behavioral actions to actively shape the dynamics of the image flow on their eyes ("optic flow").

Blowfly flight characteristics are shaped by environmental features and controlled by optic flow information.

Blowfly flight consists of two main components, saccadic turns and intervals of mostly straight gaze direction, although, as a consequence of inertia, flight trajectories usually change direction smoothly. We investigated how flight behavior changes depending on the surroundings and how saccadic turns and intersaccadic translational movements might be controlled in arenas of different width with and without obstacles. Blowflies do not fly in straight trajectories, even when traversing straight flight arenas; rather, they fly in meandering trajectories.

Prototypical components of honeybee homing flight behavior depend on the visual appearance of objects surrounding the goal.

Honeybees use visual cues to relocate profitable food sources and their hive. What bees see while navigating, depends on the appearance of the cues, the bee's current position, orientation, and movement relative to them. Here we analyze the detailed flight behavior during the localization of a goal surrounded by cylinders that are characterized either by a high contrast in luminance and texture or by mostly motion contrast relative to the background.

The behavioral relevance of landmark texture for honeybee homing.

Honeybees visually pinpoint the location of a food source using landmarks. Studies on the role of visual memories have suggested that bees approach the goal by finding a close match between their current view and a memorized view of the goal location. The most relevant landmark features for this matching process seem to be their retinal positions, the size as defined by their edges, and their color.

Goal seeking in honeybees: matching of optic flow snapshots?

Visual landmarks guide humans and animals including insects to a goal location. Insects, with their miniature brains, have evolved a simple strategy to find their nests or profitable food sources; they approach a goal by finding a close match between the current view and a memorised retinotopic representation of the landmark constellation around the goal. Recent implementations of such a matching scheme use raw panoramic images ('image matching') and show that it is well suited to work on robots and even in natural environments.

Mimicking honeybee eyes with a 280 degrees field of view catadioptric imaging system.

We present a small single camera imaging system that provides a continuous 280 degrees field of view (FOV) inspired by the large FOV of insect eyes. This is achieved by combining a curved reflective surface that is machined into acrylic glass with lenses covering the frontal field that otherwise would have been obstructed by the mirror. Based on the work of Seidl (1982 PhD Thesis Technische Hochschule Darmstadt), we describe an extension of the 'bee eye optics simulation' (BEOS) model by Giger (1996 PhD Thesis Australian National University) to the full FOV which enables us to remap camera images according to the spatial resolution of honeybee eyes.

The fine structure of honeybee head and body yaw movements in a homing task.

Honeybees turn their thorax and thus their flight motor to change direction or to fly sideways. If the bee's head were fixed to its thorax, such movements would have great impact on vision. Head movements independent of thorax orientation can stabilize gaze and thus play an important and active role in shaping the structure of the visual input the animal receives.

Visual gaze control during peering flight manoeuvres in honeybees.

As animals travel through the environment, powerful reflexes help stabilize their gaze by actively maintaining head and eyes in a level orientation. Gaze stabilization reduces motion blur and prevents image rotations. It also assists in depth perception based on translational optic flow.

Rugged, obstruction-free, mirror-lens combination for panoramic imaging.

We present a new combination of lenses and reflective surfaces for obstruction-free wide-angle imaging. The panoramic imaging system consists of a reflective surface machined into solid Perspex, which together with an embedded lens, can be attached to a video camera lens. Unlike vision sensors with a single mirror mounted in front of a camera, the view in the forward direction (i.

Lateralization of visual learning in the honeybee.

Lateralization is a well-described phenomenon in humans and other vertebrates and there are interesting parallels across a variety of different vertebrate species. However, there are only a few studies of lateralization in invertebrates. In a recent report, we showed lateralization of olfactory learning in the honeybee (Apis mellifera).

Characterisation of a blowfly male-specific neuron using behaviourally generated visual stimuli.

The pursuit system controlling chasing behaviour in male blowflies has to cope with extremely fast and dynamically changing visual input. An identified male-specific visual neuron called Male Lobula Giant 1 (MLG1) is presumably one major element of this pursuit system. Previous behavioural and modelling analyses have indicated that angular target size, retinal target position and target velocity are relevant input variables of the pursuit system.

Responses of blowfly motion-sensitive neurons to reconstructed optic flow along outdoor flight paths.

The retinal image flow a blowfly experiences in its daily life on the wing is determined by both the structure of the environment and the animal's own movements. To understand the design of visual processing mechanisms, there is thus a need to analyse the performance of neurons under natural operating conditions. To this end, we recorded flight paths of flies outdoors and reconstructed what they had seen, by moving a panoramic camera along exactly the same paths.

A single control system for smooth and saccade-like pursuit in blowflies.

During courtship, male blowflies perform aerobatic pursuits that rank among the fastest visual behaviours that can be observed in nature. The viewing strategies during pursuit behaviour of blowflies appear to be very similar to eye movements during pursuit in primates: a combination of smooth pursuit and catch-up saccades. Whereas in primates these two components of pursuit eye movements are thought to be controlled by distinct oculomotor subsystems, we present evidence that in blowflies both types of pursuit responses can be produced by a single control system.

Steering a virtual blowfly: simulation of visual pursuit.

The behavioural repertoire of male flies includes visually guided chasing after moving targets. The visuomotor control system for these pursuits belongs to the fastest found in the animal kingdom. We simulated a virtual fly, to test whether or not experimentally established hypotheses on the underlying control system are sufficient to explain chasing behaviour.