Texture dependence of motion sensing and free flight behavior in blowflies

Lindemann JP, Egelhaaf M. Texture dependence of motion sensing and free flight behavior in blowflies. Frontiers in Behavioral Neuroscience. 2013;6:92.Many flying insects exhibit an active flight and gaze strategy: purely translational flight segments alternate with quick turns called saccades. To generate such a saccadic flight pattern, the animals decide the timing, direction, and amplitude of the next saccade during the previous translatory intersaccadic interval. The information underlying these decisions is assumed to be extracted from the retinal image displacements (optic flow), which scale with the distance to objects during the intersaccadic flight phases. In an earlier study we proposed a saccade-generation mechanism based on the responses of large-field motion-sensitive neurons. In closed-loop simulations we achieved collision avoidance behavior in a limited set of environments but observed collisions in others. Here we show by open-loop simulations that the cause of this observation is the known texture-dependence of elementary motion detection in flies, reflected also in the responses of large-field neurons as used in our model. We verified by electrophysiological experiments that this result is not an artifact of the sensory model. Already subtle changes in the texture may lead to qualitative differences in the responses of both our model cells and their biological counterparts in the fly's brain. Nonetheless, free flight behavior of blowflies is only moderately affected by such texture changes. This divergent texture dependence of motion-sensitive neurons and behavioral performance suggests either mechanisms that compensate for the texture dependence of the visual motion pathway at the level of the circuits generating the saccadic turn decisions or the involvement of a hypothetical parallel pathway in saccadic control that provides the information for collision avoidance independent of the textural properties of the environment

Neuronal processing of translational optic flow in the visual system of the shore crab Carcinus maenas

This paper describes a search for neurones sensitive to optic flow in the visual system of the shore crab Carcinus maenas using a procedure developed from that of Krapp and Hengstenberg. This involved determining local motion sensitivity and its directional selectivity at many points within the neurone's receptive field and plotting the results on a map. Our results showed that local preferred directions of motion are independent of velocity, stimulus shape and type of motion (circular or linear). Global response maps thus clearly represent real properties of the neurones' receptive fields. Using this method, we have discovered two families of interneurones sensitive to translational optic flow. The first family has its terminal arborisations in the lobula of the optic lobe, the second family in the medulla. The response maps of the lobula neurones (which appear to be monostratified lobular giant neurones) show a clear focus of expansion centred on or just above the horizon, but at significantly different azimuth angles. Response maps such as these, consisting of patterns of movement vectors radiating from a pole, would be expected of neurones responding to self-motion in a particular direction. They would be stimulated when the crab moves towards the pole of the neurone's receptive field. The response maps of the medulla neurones show a focus of contraction, approximately centred on the horizon, but at significantly different azimuth angles. Such neurones would be stimulated when the crab walked away from the pole of the neurone's receptive field. We hypothesise that both the lobula and the medulla interneurones are representatives of arrays of cells, each of which would be optimally activated by self-motion in a different direction. The lobula neurones would be stimulated by the approaching scene and the medulla neurones by the receding scene. Neurones tuned to translational optic flow provide information on the three-dimensional layout of the environment and are thought to play a role in the judgment of heading

The role of direction-selective visual interneurons T4 and T5 in Drosophila orientation behavior

In order to safely move through the environment, visually-guided animals use several types of visual cues for orientation. Optic flow provides faithful information about ego-motion and can thus be used to maintain a straight course. Additionally, local motion cues or landmarks indicate potentially interesting targets or signal danger, triggering approach or avoidance, respectively. The visual system must reliably and quickly evaluate these cues and integrate this information in order to orchestrate behavior. The underlying neuronal computations for this remain largely inaccessible in higher organisms, such as in humans, but can be studied experimentally in more simple model species. The fly Drosophila, for example, heavily relies on such visual cues during its impressive flight maneuvers. Additionally, it is genetically and physiologically accessible. Hence, it can be regarded as an ideal model organism for exploring neuronal computations during visual processing. In my PhD studies, I have designed and built several autonomous virtual reality setups to precisely measure visual behavior of walking flies. The setups run in open-loop and in closed-loop configuration. In an open-loop experiment, the visual stimulus is clearly defined and does not depend on the behavioral response. Hence, it allows mapping of how specific features of simple visual stimuli are translated into behavioral output, which can guide the creation of computational models of visual processing. In closedloop experiments, the behavioral response is fed back onto the visual stimulus, which permits characterization of the behavior under more realistic conditions and, thus, allows for testing of the predictive power of the computational models. In addition, Drosophila’s genetic toolbox provides various strategies for targeting and silencing specific neuron types, which helps identify which cells are needed for a specific behavior. We have focused on visual interneuron types T4 and T5 and assessed their role in visual orientation behavior. These neurons build up a retinotopic array and cover the whole visual field of the fly. They constitute major output elements from the medulla and have long been speculated to be involved in motion processing. This cumulative thesis consists of three published studies: In the first study, we silenced both T4 and T5 neurons together and found that such flies were completely blind to any kind of motion. In particular, these flies could not perform an optomotor response anymore, which means that they lost their normally innate following responses to motion of large-field moving patterns. This was an important finding as it ruled out the contribution of another system for motion vision-based behaviors. However, these flies were still able to fixate a black bar. We could show that this behavior is mediated by a T4/T5-independent flicker detection circuitry which exists in parallel to the motion system. In the second study, T4 and T5 neurons were characterized via twophoton imaging, revealing that these cells are directionally selective and have very similar temporal and orientation tuning properties to directionselective neurons in the lobula plate. T4 and T5 cells responded in a contrast polarity-specific manner: T4 neurons responded selectively to ON edge motion while T5 neurons responded only to OFF edge motion. When we blocked T4 neurons, behavioral responses to moving ON edges were more impaired than those to moving OFF edges and the opposite was true for the T5 block. Hence, these findings confirmed that the contrast polarityspecific visual motion pathways, which start at the level of L1 (ON) and L2 (OFF), are maintained within the medulla and that motion information is computed twice independently within each of these pathways. Finally, in the third study, we used the virtual reality setups to probe the performance of an artificial microcircuit. The system was equipped with a camera and spherical fisheye lens. Images were processed by an array of Reichardt detectors whose outputs were integrated in a similar way to what is found in the lobula plate of flies. We provided the system with several rotating natural environments and found that the fly-inspired artificial system could accurately predict the axes of rotation

Mobile Robots

The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review

Motion perception is a critical capability determining a variety of aspects of insects' life, including avoiding predators, foraging and so forth. A good number of motion detectors have been identified in the insects' visual pathways. Computational modelling of these motion detectors has not only been providing effective solutions to artificial intelligence, but also benefiting the understanding of complicated biological visual systems. These biological mechanisms through millions of years of evolutionary development will have formed solid modules for constructing dynamic vision systems for future intelligent machines. This article reviews the computational motion perception models originating from biological research of insects' visual systems in the literature. These motion perception models or neural networks comprise the looming sensitive neuronal models of lobula giant movement detectors (LGMDs) in locusts, the translation sensitive neural systems of direction selective neurons (DSNs) in fruit flies, bees and locusts, as well as the small target motion detectors (STMDs) in dragonflies and hover flies. We also review the applications of these models to robots and vehicles. Through these modelling studies, we summarise the methodologies that generate different direction and size selectivity in motion perception. At last, we discuss about multiple systems integration and hardware realisation of these bio-inspired motion perception models

Finding the Gap:Neuromorphic Motion Vision in Cluttered Environments

Many animals meander in environments and avoid collisions. How the underlying neuronal machinery can yield robust behaviour in a variety of environments remains unclear. In the fly brain, motion-sensitive neurons indicate the presence of nearby objects and directional cues are integrated within an area known as the central complex. Such neuronal machinery, in contrast with the traditional stream-based approach to signal processing, uses an event-based approach, with events occurring when changes are sensed by the animal. Contrary to von Neumann computing architectures, event-based neuromorphic hardware is designed to process information in an asynchronous and distributed manner. Inspired by the fly brain, we model, for the first time, a neuromorphic closed-loop system mimicking essential behaviours observed in flying insects, such as meandering in clutter and gap crossing, which are highly relevant for autonomous vehicles. We implemented our system both in software and on neuromorphic hardware. While moving through an environment, our agent perceives changes in its surroundings and uses this information for collision avoidance. The agent's manoeuvres result from a closed action-perception loop implementing probabilistic decision-making processes. This loop-closure is thought to have driven the development of neural circuitry in biological agents since the Cambrian explosion. In the fundamental quest to understand neural computation in artificial agents, we come closer to understanding and modelling biological intelligence by closing the loop also in neuromorphic systems. As a closed-loop system, our system deepens our understanding of processing in neural networks and computations in biological and artificial systems. With these investigations, we aim to set the foundations for neuromorphic intelligence in the future, moving towards leveraging the full potential of neuromorphic systems.Comment: 7 main pages with two figures, including appendix 26 pages with 14 figure

Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care