Insect Vision: Controlling Actions through Optic Flow

Event Abstract Back to Event Spatial vision in insects: How visual information processing is facilitated by an active flight and gaze strategy Martin Egelhaaf1*, Roland Kern1 and Jens P. Lindemann1 1 Bielefeld University, Neurobiology & CITEC, Germany Flying insects, such as blowflies and bees rely on the image flow on their eyes (“optic flow”) solving spatial tasks as diverse as collision avoidance and local navigation, i.e. localizing a previously learnt inconspicuous goal on the basis of landmark cues. In free flight flies and bees exhibit characteristic behavioural actions to shape the dynamics of the optic flow. By employing a saccadic flight and gaze strategy they squeeze rotations into brief and rapid turns leaving most of the flight time for various types of translational prototypical movements. Separation of rotational and translational optic flow components by a behavioural strategy is reasonable , since only the optic flow component induced by translations contains information about the relative distance of environmental structures from the animal. By combined electrophysiological analysis and model simulations we analyzed how during rotational and translational self-motion information about the spatial layout and the textural properties of both experimenter-designed and natural environments are represented at the different processing stages of the visual motion pathway. Only two major conclusions shall be mentioned here: (1) during intersaccadic translational flight, the mechanisms of local motion detection segregate in a computationally cheap way natural sceneries into their depth structure: nearby objects pop out in the activity profile of retinotopic arrays of local motion detectors, whereas more distant structures evoke only negligible responses. (2) Even after spatial pooling of local motion signals by the dendritic trees of the wide-field cells in the lobula complex of flies and bees, these distance dependent response modulations persist. Hence, these neurons, which are traditionally conceived as rotation sensors being involved in mediating compensatory optomotor responses, provide information about the spatial properties of the environment. In conclusion, the neural processing of spatial information in flies and bees is greatly facilitated by their saccadic flight and gaze strategy. This active vision strategy enables the nervous system to solve apparently complex spatial vision tasks in a computationally parsimonious way. Thus, by making use of the closed action–perception loop in a smart way, insects with their tiny brains are capable of performing extraordinarily well even on extremely fast timescales of some ten milliseconds. Acknowledgements The work in our lab is supported by the Deutsche Forschungsgemeinschaft (DFG) Keywords: motion vision, Spatial Vision, Optic Flow, collision avoidance, navigation, fly, Honeybee, Bumblebee, Flight control Conference: International Conference on Invertebrate Vision, Fjälkinge, Sweden, 1 Aug - 8 Aug, 2013. Presentation Type: Oral presentation preferred Topic: Motion vision Citation: Egelhaaf M, Kern R and Lindemann JP (2019). Spatial vision in insects: How visual information processing is facilitated by an active flight and gaze strategy. Front. Physiol. Conference Abstract: International Conference on Invertebrate Vision. doi: 10.3389/conf.fphys.2013.25.00044 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 25 Feb 2013; Published Online: 09 Dec 2019. * Correspondence: Prof. Martin Egelhaaf, Bielefeld University, Neurobiology & CITEC, Bielefeld, D-33501, Germany, martin.egelhaaf@uni-bielefeld.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Martin Egelhaaf Roland Kern Jens P Lindemann Google Martin Egelhaaf Roland Kern Jens P Lindemann Google Scholar Martin Egelhaaf Roland Kern Jens P Lindemann PubMed Martin Egelhaaf Roland Kern Jens P Lindemann Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

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”). The neural processing of information about the spatial layout of the environment is greatly facilitated by segregating the rotational from the translational optic flow component through a saccadic flight and gaze strategy. This active vision strategy thus enables the nervous system to solve apparently complex spatial vision tasks in a particularly efficient and parsimonious way. The key idea of this review is that biological agents, such as flies or bees, acquire at least part of their strength as autonomous systems through active interactions with their environment and not by simply processing passively gained information about the world. These agent-environment interactions lead to adaptive behavior in surroundings of a wide range of complexity. Animals with even tiny brains, such as insects, are capable of performing extraordinarily well in their behavioral contexts by making optimal use of the closed action–perception loop. Model simulations and robotic implementations show that the smart biological mechanisms of motion computation and visually-guided flight control might be helpful to find technical solutions, for example, when designing micro air vehicles carrying a miniaturized, low-weight on-board processor.

Mechanics of animal locomotion, vol. 11: Edited by R. McN. Alexander. Advances in Comparative Physiology, 304pp. 1992. Springer Verlag, Berlin. DM 168

The optic flow generated when a person moves through the environment can be locally decomposed into several basic components, including radial, circular, translational and spiral motion. Since their analysis plays an important part in the visual perception and control of locomotion and posture it is likely that some brain regions in the primate dorsal visual pathway are specialized to distinguish among them. The aim of this study is to explore the sensitivity to different types of egomotion-compatible visual stimulations in the human motion-sensitive regions of the brain. Event-related fMRI experiments, 3D motion and wide-field stimulation, functional localizers and brain mapping methods were used to study the sensitivity of six distinct motion areas (V6, MT, MST+, V3A, CSv and an Intra-Parietal Sulcus motion [IPSmot] region) to different types of optic flow stimuli. Results show that only areas V6, MST+ and IPSmot are specialized in distinguishing among the various types of flow patterns, with a high response for the translational flow which was maximum in V6 and IPSmot and less marked in MST+. Given that during egomotion the translational optic flow conveys differential information about the near and far external objects, areas V6 and IPSmot likely process visual egomotion signals to extract information about the relative distance of objects with respect to the observer. Since area V6 is also involved in distinguishing object-motion from self-motion, it could provide information about location in space of moving and static objects during self-motion, particularly in a dynamically unstable environment.

The continuously changing optic flow on the retina provides information about direction of heading and about the three-dimensional structure of the environment. Here we use functional magnetic resonance imaging (fMRI) to demonstrate that an area in human cortex responds selectively to components of optic flow, such as circular and radial motion. This area is within the region commonly referrred to as V5/MT complex, but is distinct from the part of this region that responds to translation. The functional properties of these two areas of the V5/MT complex are also different; the response to optic flow was obtained only with changing flow stimuli, whereas response to translation occurred during exposure to continuous motion.

The focus of expansion (FoE) specifies the heading direction of an observer during self-motion, and experiments show that humans can accurately perceive their heading from optic flow. However, when the environment contains an independently moving object, heading judgments may be biased. When objects approach the observer in depth, the heading bias may be due to discrepant optic flow within the contours of the object that radiates from a secondary FoE (object-based discrepancy) or by motion contrast at the borders of the object (border-based discrepancy). In Experiments 1 and 2, we manipulated the object's path angle and distance from the observer to test whether the heading bias induced by moving objects is entirely due to object-based discrepancies. The results showed consistent bias even at large path angles and when the object moved far in depth, which is difficult to reconcile with the influence of discrepant optic flow within the object. In Experiment 3, we found strong evidence that the misperception of heading can also result from a specific border-based discrepancy ("pseudo FoE") that emerges from the relative motion between the object and background at the trailing edge of the object. Taken together, the results from the present study support the idea that when moving objects are present, heading perception is biased in some conditions by discrepant optic flow within the contours of the object and in other conditions by motion contrast at the border (the pseudo FoE). Center-weighted spatial pooling mechanisms in MSTd may account for both effects.

Spike Burst Coding of Translatory Optic Flow and Depth from Motion in the Fly Visual System

Perception of three-dimensional structure from visual motion requires the visual motion to be integrated spatially as well as to be recognized as a 3-D object. Psychophysical studies have been made to investigate how the visual system extracts the three-dimensional structure of objects from the two-dimensional motion of random dots (3-D structure-from-motion: 3D-SFM), though the neural dynamics underlying the reconstruction of a 3-D structure from optic flow is not fully understood. We used neuromagnetic measurements to detect the dynamic brain responses to 3-D structure perception from visual motion in human. Three different visual stimuli were used; (A) 3-D structure-from-motion (SFM): dots moved as if they belonged to a spherical surface rotating horizontally, (B) In-plane rotation (IPR): dots moved as if they belonged to a circle rotating in-plane, or (C) Random motion (RM): dots moved with random direction and random displacement. The results of event-related time-frequency analysis showed significant suppression of alpha band (7–13 Hz) activity in the right occipito-temporal region, and the suppression of beta band (15–25 Hz) activity in the bilateral superior occipital region in the’ sFM’ condition compared to the ‘IPR’ condition. Spatio-temporal imaging of the brain activity using adaptive beamformer method showed that these areas were also involved in the generation of the event-related MEG components observed during the perception of 3-D objects between the latencies of 140 and 220 ms after the onset of random-dot motion. These results suggest that the perception of moving 3-D object from 2-D random-dot motion is accomplished by the activation both in the ventral and dorsal visual pathways.

Summary form only given, as follows. Anyone who has watched a fly make a flawless landing on the rim of a teacup, or marvelled at a honeybee speeding home after collecting nectar fiom a flower patch several kilometres away, would know that insects possess visual systems that are fast, reliable and accurate. Insects cope remarkably well with their world, despite possessing a brain that carries fewer than 0.01% as many neurons as ours does. Although most insects lack stereo vision, they use a number of ingenious strategies for perceiving their world in three dimensions and navigating successfully in it. For example, distances to objects are gauged in terms of the apparent speeds of motion of the objects' images, rather than by using complex stereo mechanisms. Grasshoppers estimate the distance to targets by moving their heads from side to side, and measuring range in terms of the speed of the target's image on the retina. Bees distinguish objects from backgrounds by sensing the apparent relative motion at the boundary between object and background. Narrow gaps are negotiated by balancing the apparent speeds of the images in the two eyes. Flight speed is regulated by holding constant the global image velocity as seen by the two eyes. Bees landing on a horizontal surface hold constant the image velocity of the surface as they approach it, thus automatically ensuring that flight speed is close to zero at touchdown. Foraging bees gauge distance flown by integrating optic flow: they possess a visually-driven odometer that is robust to variations in wind, body weight and energy expenditure. This presentation reviews some of this work, and outlines applications of some of these strategies to the design of autonomous, visually-guided robots.

The effect of monocular depth cues on the detection of moving objects by moving observers

As an animal moves through the environment, it experiences flow of sensory information from stationary objects. Animals that relylargely on visual information to guide their movement experience optic flow patterns as they navigate, which can be used to measure the relative distance of objects in the environment (Gibson, 1958, Besl, 1988). For example, honeybees use optic flow patterns to center themselves in a flight corridor, and experimental manipulations of the visual patterns on the walls directly influence the animal’s navigation path (Srinivasan et al., 1996). Other animals instead show wall-following behavior, choosing to navigate close to visual obstacles (Scholtyssek et al., 2014). Here, we report on the navigation paths of animals that rely on acoustic signals to guide their movement. Echolocating bats emit ultrasonic signals that reflect from objects in the path of their sound beam, and we are studying how these animals use echo flow to guide their flight path through a corridor. In this study, we flew echolocating big brown bats through tunnels of horizontally and vertically hung PVC pipes to investigate how acoustic patterns influence the bat’s flight and echolocation behavior.