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  Processing of figure and background motion in the visual system of the fly

Reichardt, W., Egelhaaf, M., & Guo, A.-K. (1989). Processing of figure and background motion in the visual system of the fly. Biological Cybernetics, 61(5), 327-345. doi:10.1007/BF00200799.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-EEE1-C Version Permalink: http://hdl.handle.net/21.11116/0000-0006-44CD-7
Genre: Journal Article


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Reichardt, W1, 2, Author              
Egelhaaf, M1, 2, Author              
Guo , A-K, Author
1Former Department Information Processing in Insects, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497801              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              


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 Abstract: The visual system of the fly is able to extract different types of global retinal motion patterns as may be induced on the eyes during different flight maneuvers and to use this information to control visual orientation. The mechanisms underlying these tasks were analyzed by a combination of quantitative behavioral experiments on tethered flying flies (Musca domestica) and model simulations using different conditions of oscillatory large-field motion and relative motion of different segments of the stimulus pattern. Only torque responses about the vertical axis of the animal were determined. The stimulus patterns consisted of random dot textures (“Julesz patterns”) which could be moved either horizontally or vertically. Horizontal rotatory large-field motion leads to compensatory optomotor turning responses, which under natural conditions would tend to stabilize the retinal image. The response amplitude depends on the oscillation frequency: It is much larger at low oscillation frequencies than at high ones. When an object and its background move relative to each other, the object may, in principle, be discriminated and then induce turning responses of the fly towards the object. However, whether the object is distinguished by the fly depends not only on the phase relationship between object and background motion but also on the oscillation frequency. At all phase relations tested, the object is detected only at high oscillation frequencies. For the patterns used here, the turning responses are only affected by motion along the horizontal axis of the eye. No influences caused by vertical motion could be detected. The experimental data can be explained best by assuming two parallel control systems with different temporal and spatial integration properties: TheLF-system which is most sensitive to coherent rotatory large-field motion and mediates compensatory optomotor responses mainly at low oscillation frequencies. In contrast, theSF-system is tuned to small-field and relative motion and thus specialized to discriminate a moving object from its background; it mediates turning responses towards objects mainly at high oscillation frequencies. The principal organization of the neural networks underlying these control systems could be derived from the characteristic features of the responses to the different stimulus conditions. The input to the model circuits responsible for the characteristic sensitivity of the SF-system to small-field and relative motion is provided by retinotopic arrays of local movement detectors. The movement detectors are integrated by a large-field element, the output cell of the network. The synapses between the detectors and the output cells have nonlinear transmission characteristics. Another type of large-field elements (“pool cells”) which respond to motion in front of both eyes and have characteristic direction selectivities are assumed to interact with the local movement detector channels by inhibitory synapses of the shunting type, before the movement detectors are integrated by the output cells. The properties of the LF-system can be accounted for by similar model circuits which, however, differ with respect to the transmission characteristic of the synapses between the movement detectors and the output cell; moreover, their pool cells are only monocular. This type of network, however, is not necessary to account for the functional properties of the LF-system. Instead, intrinsic properties of single neurons may be sufficient. Computer simulations of the postulated mechanisms of the SF-and LF-system reveal that these can account for the specific features of the behavioral responses under quite different conditions of coherent large-field motion and relative motion of different pattern segments.


 Dates: 1989-09
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1007/BF00200799
BibTex Citekey: 1649
 Degree: -



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Title: Biological Cybernetics
  Other : Biol. Cybern.
Source Genre: Journal
Publ. Info: Berlin : Springer
Pages: - Volume / Issue: 61 (5) Sequence Number: - Start / End Page: 327 - 345 Identifier: ISSN: 0340-1200
CoNE: https://pure.mpg.de/cone/journals/resource/954927549307