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

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

Egelhaaf M, Boeddeker N, Kern R, Kurtz R, Lindemann JP. Spatial vision in insects is facilitated by shaping the dynamics of visual input through behavioral action. Frontiers in Neural Circuits. 2012;6:108.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

Response latency of a motion-sensitive neuron in the fly visual system: dependence on stimulus parameters and physiological conditions

Warzecha A-K, Egelhaaf M. Response latency of a motion-sensitive neuron in the fly visual system: dependence on stimulus parameters and physiological conditions. Vision research. 2000;40(21):2973-2983

Inhibition by recurrent excitation: a mechanism for spike synchronization in a network of coupled neuronal oscillators

Egelhaaf M, Benjamin PR. Inhibition by recurrent excitation: a mechanism for spike synchronization in a network of coupled neuronal oscillators. Journal of Experimental Biology. 1982;96:447-451

Taking a goal-centred dynamic snapshot as a possibility for local homing in initially naïve bumblebees

Lobecke A, Kern R, Egelhaaf M. Taking a goal-centred dynamic snapshot as a possibility for local homing in initially naïve bumblebees. The Journal of Experimental Biology. 2018;221(2): jeb168674.It is essential for central place foragers, such as bumblebees, to return reliably to their nest. Bumblebees, leaving their inconspicuous nest hole for the first time need to gather and learn sufficient information about their surroundings to allow them to return to their nest at the end of their trip, instead of just flying away to forage. Therefore, we assume an intrinsic learning programme that manifests itself in the flight structure immediately after leaving the nest for the first time. In this study, we recorded and analysed the first outbound flight of individually marked naïve bumblebees in an indoor environment. We found characteristic loop-like features in the flight pattern that appear to be necessary for the bees to acquire environmental information and might be relevant for finding the nest hole after a foraging trip. Despite common features in their spatio- temporal organisation, first departure flights from the nest are characterised by a high level of variability in their loop-like flight structure across animals. Changes in turn direction of body orientation, for example, are distributed evenly across the entire area used for the flights without anysystematic relationship to the nest location. By considering the common flight motifs and this variability, we came to the hypothesis that a kind of dynamic snapshot is taken during the early phase of departure flights centred at the nest location. The quality of this snapshot is hypothesised to be ‘tested’ during the later phases of the departure flights concerning its usefulness for local homing

Neural processing of naturalistic optic flow

Kern R, Petereit C, Egelhaaf M. Neural processing of naturalistic optic flow. The Journal of Neuroscience. 2001;21(8):1-5.Stimuli traditionally used for analyzing visual information processing are much simpler than what an animal sees in normal life. When characterized with traditional stimuli, neuronal responses were found to depend on various parameters such as contrast, texture, or velocity of motion, and thus were highly ambiguous. In behavioral situations, all of these parameters change simultaneously and differently in different parts of the visual field. Thus it is hardly possible to predict from traditional analyses what information is encoded by neurons in behavioral situations. Therefore, we characterized an identified neuron in the optomotor system of the blowfly with image sequences as they were seen by animals walking in a structured environment. We conclude that during walking, the response of the neuron reflects the animal's turning direction nearly independently of the texture and spatial layout of the environment. Our findings stress the significance of analyzing the performance of neuronal circuits under their natural operating conditions

Chasing Behavior and Optomotor Following in Free-Flying Male Blowflies: Flight Performance and Interactions of the Underlying Control Systems

The chasing behavior of male blowflies after small targets belongs to the most rapid and virtuosic visually guided behaviors found in nature. Since in a structured environment any turn towards a target inevitably leads to a displacement of the entire retinal image in the opposite direction, it might evoke optomotor following responses counteracting the turn. To analyze potential interactions between the control systems underlying chasing behavior and optomotor following, respectively, we performed behavioral experiments on male blowflies and examined the characteristics of the two flight control systems in isolation and in combination. Three findings are particularly striking. (i) The characteristic saccadic flight and gaze style – a distinctive feature of blowfly cruising flights – is largely abandoned when the entire visual surroundings move around the fly; in this case flies tend to follow the moving pattern in a relatively continuous and smooth way. (ii) When male flies engage in following a small target, they also employ a smooth pursuit strategy. (iii) Although blowflies are reluctant to fly at high background velocities, the performance and dynamical characteristics of the chasing system are not much affected when the background moves in either the same or in the opposite direction as the target. Hence, the optomotor following response is largely suppressed by the chasing system and does not much impair chasing performance

Depth information in natural environments derived from optic flow by insect motion detection system: a model analysis

Knowing the depth structure of the environment is crucial for moving animals in many behavioral contexts, such as collision avoidance, targeting objects, or spatial navigation. An important source of depth information is motion parallax. This powerful cue is generated on the eyes during translatory self-motion with the retinal images of nearby objects moving faster than those of distant ones. To investigate how the visual motion pathway represents motion-based depth information we analyzed its responses to image sequences recorded in natural cluttered environments with a wide range of depth structures. The analysis was done on the basis of an experimentally validated model of the visual motion pathway of insects, with its core elements being correlation-type elementary motion detectors (EMDs). It is the key result of our analysis that the absolute EMD responses, i.e. the motion energy profile, represent the contrast-weighted nearness of environmental structures during translatory self-motion at a roughly constant velocity. In other words, the output of the EMD array highlights contours of nearby objects. This conclusion is largely independent of the scale over which EMDs are spatially pooled and was corroborated by scrutinizing the motion energy profile after eliminating the depth structure from the natural image sequences. Hence, the well-established dependence of correlation-type EMDs on both velocity and textural properties of motion stimuli appears to be advantageous for representing behaviorally relevant information about the environment in a computationally parsimonious way

Neural coding with graded membrane potential changes and spikes

Kretzberg J, Warzecha A-K, Egelhaaf M. Neural coding with graded membrane potential changes and spikes. Journal of computational neuroscience. 2001;11(2):153-164.The neural encoding of sensory stimuli is usually investigated for spike responses, although many neurons are known to convey information by graded membrane potential changes. We compare by model simulations how well different dynamical stimuli can be discriminated on the basis of spiking or graded responses. Although a continuously varying membrane potential contains more information than binary spike trains, we find situations where different stimuli can be better discriminated on the basis of spike responses than on the basis of graded responses. Spikes can be superior to graded membrane potential fluctuations if spikes sharpen the temporal structure of neuronal responses by amplifying fast transients of the membrane potential. Such fast membrane potential changes can be induced deterministically by the stimulus or can be due to membrane potential noise that is influenced in its statistical properties by the stimulus. The graded response mode is superior for discrimination between stimuli on a fine time scale

Temporal precision of the encoding of motion information by visual interneurons

Warzecha A-K, Kretzberg J, Egelhaaf M. Temporal precision of the encoding of motion information by visual interneurons. Current Biology. 1998;8(7):359-368.BACKGROUND: There is much controversy about the timescale on which neurons process and transmit information. On the one hand, a vast amount of information can be processed by the nervous system if the precise timing of individual spikes on a millisecond timescale is important. On the other hand, neuronal responses to identical stimuli often vary considerably and stochastic response fluctuations can exceed the mean response amplitude. Here, we examined the timescale on which neural responses could be locked to visual motion stimuli. RESULTS: Spikes of motion-sensitive neurons in the visual system of the blowfly are time-locked to visual motion with a precision in the range of several tens of milliseconds. Nevertheless, different motion-sensitive neurons with largely overlapping receptive fields generate a large proportion of spikes almost synchronously. This precision is brought about by stochastic rather than by motion-induced membrane-potential fluctuations elicited by the common peripheral input. The stochastic membrane-potential fluctuations contain more power at frequencies above 30-40 Hz than the motion-induced potential changes. A model of spike generation indicates that such fast membrane-potential changes are a major determinant of the precise timing of spikes. CONCLUSIONS: The timing of spikes in neurons of the motion pathway of the blowfly is controlled on a millisecond timescale by fast membrane-potential fluctuations. Despite this precision, spikes do not lock to motion stimuli on this timescale because visual motion does not induce sufficiently rapid changes in the membrane potential