A Conserved Network for Control of Arthropod Exteroceptive Optical Flow Reflexes during Locomotion

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6226)


We have developed an exteroceptive reflex network of sensory interneurons and command neurons that simulates arthropod optical reflexes based on current ethological and neurophysiological models. The simple neural network was instantiated in software with discrete-time map-based neurons and synapses and can mediate four forms of optomotor reflexes in arthropods: (1) translational responses to pure translational optic flow; (2) rotational responses to pure angular rotation and (3) combinations of translation and rotation that occur during obstacle avoidance and (4) yaw. Simple neural networks are well suited for controlling robots and can be used to test neurophysiological hypotheses, particularly related to sensory fusion in arthropods.


Sensory Neuron Obstacle Avoidance Command Neuron Wing Beat Underwater Robot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Loeb, J.: Forced Movements, Tropisms, and Animal Conduct. J.B. Lippincott, Philadelphia (1918)Google Scholar
  2. 2.
    Braitenberg, V.: Taxis, Kinesis and Decussation. Prog. Brain Res. 17, 210–222 (1978)CrossRefGoogle Scholar
  3. 3.
    Braitenberg, V.: Vehicles: experiments in synthetic psychology. MIT Press, Cambridge (1986)Google Scholar
  4. 4.
    Bethe, A.: A comparative study of the functions of the central nervous system of arthropods. J. Comp. Neurol. 8, 232–238 (1898)CrossRefGoogle Scholar
  5. 5.
    Davis, W.J., Ayers, J.A.: Locomotion: Control by positive-feedback optokinetic responses. Science 177, 183–185 (1972)CrossRefGoogle Scholar
  6. 6.
    Ayers, J., Rulkov, N.F.: Controlling Biomimetic Underwater Robots with Electronic Nervous Systems. In: Kato, N., Kamimura, S. (eds.) Bio-mechanisms of Animals in Swimming and Flying, pp. 295–306. Springer, Tokyo (2007)Google Scholar
  7. 7.
    Götz, K.: Flight control in Drosophila by visual perception of motion. Biol. Cybernetics 4, 199–208 (1968)Google Scholar
  8. 8.
    Blondeau, J., Heisenberg, M.: The 3-dimensional optomotor torque system of Drosophila melanogaster. J. Comp. Physiol. 145, 321–329 (1982)CrossRefGoogle Scholar
  9. 9.
    Srinivasan, M.W., Zhang, S.W.: Visual motor computations in insects. Annu. Rev. Neurosci. 27, 679–696 (2004)CrossRefGoogle Scholar
  10. 10.
    Frye, M., Dickinson, M.: Closing the loop between neurobiology and flight behavior in Drosophila. Curr. Opin. Neurobiol. 14, 729–736 (2004)CrossRefGoogle Scholar
  11. 11.
    Rowell, C.: Mechanisms of flight steering in locusts. Experientia 44, 389–395 (1988)CrossRefGoogle Scholar
  12. 12.
    Srinivasan, M.V., Zhang, S.W., Lehrer, M., Collett, T.S.: Honeybee navigation en route to the goal: visual flight control and odometry. J. Exp. Biol. 199, 237–244 (1996)Google Scholar
  13. 13.
    Dickinson, M.: The initiation and control of rapid flight maneuvers in fruit flies. Integr. Comp. Biol. 45, 274–281 (2005)CrossRefGoogle Scholar
  14. 14.
    Rind, F., Bramwell, D.: Neural network based on the input organization of an identified neuron signaling impending collision. J. Neurophysiol. 75, 967–985 (1996)Google Scholar
  15. 15.
    O’Shea, M., Rowell, C., Williams, J.: The anatomy of a locust visual interneurone; the descending contralateral movement detector. J. Exp. Biol. 60, 1–12 (1974)Google Scholar
  16. 16.
    Baader, A., Schäfer, M., Rowell, C.: The perception of the visual flow field by flying locusts: a behavioural and neuronal analysis. J. Exp. Biol. 165, 137–160 (1992)Google Scholar
  17. 17.
    Baird, E., Srinivasan, M., Zhang, S., Cowling, A.: Visual control of flight speed in honeybees. J. Exp. Biol. 208, 3895–3905 (2005)CrossRefGoogle Scholar
  18. 18.
    Wendler, G.: The organization of insect locomotion systems and computer-based flight control in the tobacco hawkmoth Manduca sexta. In: Ayers, J., Davis, J., Rudolph, A. (eds.) Neurotechnology for Biomimetic Robots, pp. 451–468. MIT Press, Cambridge (2002)Google Scholar
  19. 19.
    Ellington, C.: The novel aerodynamics of insect flight: applications to micro-air vehicles. J. Exp. Biol. 202, 3439–3448 (1999)Google Scholar
  20. 20.
    Sherman, A., Dickinson, M.: A comparison of visual and haltere-mediated equilibrium reflexes in the fruit fly Drosophila melanogaster. J. Exp. Biol. 206, 295–302 (2003)CrossRefGoogle Scholar
  21. 21.
    Ristroph, L., Bergou, A., Ristroph, G., Coumes, K., Berman, G., Guckenheimer, J., Wang, Z., Cohen, I.: Discovering the flight autostabilizer of fruit flies by inducing aerial stumbles. Proc. Natl. Acad. Sci. USA 107, 4820–4824 (2010)CrossRefGoogle Scholar
  22. 22.
    Wiersma, C., Yamaguchi, T.: Integration of visual stimuli by the crayfish central nervous system. J. Exp. Biol. 47, 409–431 (1967)Google Scholar
  23. 23.
    Rind, F.: Identification of directionally selective motion-detecting neurones in the locust lobula and their synaptic connections with an identified descending neurone. J. Exp. Biol. 149, 21–43 (1990)Google Scholar
  24. 24.
    Ibbotson, M.: Wide-field motion-sensitive neurons tuned to horizontal movement in the honeybee, Apis mellifera. J. Comp. Physiol. 168, 91–102 (1991)CrossRefGoogle Scholar
  25. 25.
    Ibbotson, M., Maddess, T., DuBois, R.: A system of insect neurons sensitive to horizontal and vertical image motion connects the medula and midbrain. J. Comp. Physiol. 169, 355–367 (1991)CrossRefGoogle Scholar
  26. 26.
    Kern, R.: Visual position stabilization in the hummingbird hawk moth, Macroglossum stellatarum L. II. Electrophysiological analysis of neurons sensitive to wide-field image motion. J. Comp. Physiol. 182, 239–249 (1998)Google Scholar
  27. 27.
    Joesch, M., Plett, J., Borst, A., Reiff, D.F.: Response properties of motion-sensitive visual interneurons in the lobula plate of Drosophila melanogaster. Curr. Biol. 18, 368–374 (2008)CrossRefGoogle Scholar
  28. 28.
    Bowerman, R., Larimer, J.: Command fibres in the circumesophageal connectives of crayfish, II. Phasic fibres. J. Exp. Biol. 60, 119–134 (1974)Google Scholar
  29. 29.
    Rulkov, N.F.: Modeling of spiking-bursting neural behavior using two-dimensional map. Phys. Rev. E 65, 041922 (2002)CrossRefMathSciNetGoogle Scholar
  30. 30.
    Ayers, J., Rulkov, N.F., Knudsen, D., Kim, Y.B., Volkovskii, A., Selverston, A.: Controlling underwater robots with electronic nervous systems. Appl. Bionics Biomech. 7, 57–67 (2010)CrossRefGoogle Scholar
  31. 31.
    Preiss, R., Spork, P.: How locusts separate pattern flow into its rotatory and translatory components (Orthoptera: Acrididae). J. Insect Behavior 8, 763–779 (1995)CrossRefGoogle Scholar
  32. 32.
    Layne, J., Barnes, W.J., Duncan, L.: Mechanisms of homing in the fiddler crab Uca rapax: 2. Information sources and frame of reference for a path integration system. J. Exp. Biol. 206, 4425–4442 (2003)Google Scholar
  33. 33.
    Coombs, D., Roberts, K.: “Bee-bot”: using peripheral optical flow to avoid obstacles. In: Proc. of the SPIE, vol. 1825, pp. 714–721 (1992)Google Scholar
  34. 34.
    Green, W., Oh, P., Barrows, G.: Flying insect inspired vision for autonomous aerial robot maneuvers in near-Earth environments. In: Proceedings of IEEE International Conference of Robotics and Automation, pp. 2347–2352. IEEE Press, New Orleans (2004)Google Scholar
  35. 35.
    Budick, S., Reiser, M., Dickinson, M.: The role of visual and mechanosensory cues in structuring forward flight in Drosophila melanogaster. J. Exp. Biol. 210, 4092–4103 (2007)CrossRefGoogle Scholar
  36. 36.
    Wiersma, C., Fiore, L.: Unidirectional rotation neurones in the optomotor system of the crab, Carcinus. J. Exp. Biol. 54, 507–513 (1971)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Marine Science CenterNortheastern UniversityNahantUSA

Personalised recommendations