Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-11T07:41:12.487Z Has data issue: false hasContentIssue false
  • English
  • Français

Effects of light intensity and pattern contrast on the ability of the land crab, Cardisoma guanhumi, to separate optic flow-field components

Published online by Cambridge University Press:  25 February 2005

AARON P. JOHNSON ,
W. JON. P. BARNES  and
MARTIN W.S. MACAULEY
AARON P. JOHNSON
Affiliation:
Division of Environmental and Evolutionary Biology, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow, Scotland, UK Department of Electronics and Electrical Engineering, University of Glasgow, Glasgow, Scotland, UK
W. JON. P. BARNES
Affiliation:
Division of Environmental and Evolutionary Biology, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow, Scotland, UK
MARTIN W.S. MACAULEY
Affiliation:
Department of Electronics and Electrical Engineering, University of Glasgow, Glasgow, Scotland, UK
Get access Rights & Permissions [Opens in a new window]

Abstract

Using a novel suite of computer-generated visual stimuli that mimicked components of optic flow, the visual responses of the tropical land crab, Cardisoma guanhumi, were investigated. We show that crabs are normally successful in distinguishing the rotational and translational components of the optic flow field, showing strong optokinetic responses to the former but not the latter. This ability was not dependant on the orientation of the crab, occurring both in “forwards-walking” and “sideways-walking” configurations. However, under conditions of low overall light intensity and/or low object/background contrast, the separation mechanism shows partial failure causing the crab to generate compensatory eye movements to translation, particularly in response to low-frequency (low-velocity) stimuli. Using this discovery, we then tested the ability of crabs to separate rotational and translational components in a combined rotation/translation flow field under different conditions. We demonstrate that, while crabs can successfully separate such a combined flow field under normal circumstances, showing compensatory eye movements only to the rotational component, they are unable to make this separation under conditions of low overall light intensity and low object/background contrast. Here, the responses to both flow-field components show summation when they are in phase, but, surprisingly, there is little reduction in the amplitude of responses to rotation when the translational component is in antiphase. Our results demonstrate that the crab's visual system finds separation of flow-field components a harder task than detection of movement, since the former shows partial failure at light intensities and/or object/background contrasts at which movement of the world around the crab is still generating high-gain optokinetic responses.

Keywords

CrabOptic flowVisual flow fieldOptokinetic responsesComputer-generated visual images
Type
Research Article
Information
Visual Neuroscience , Volume 21 , Issue 6 , November 2004 , pp. 895 - 904
Copyright
© 2004 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Barnes, W.J.P. (1990). Sensory basis and functional role of eye movements elicited during locomotion in the land crab, Cardisoma guanhumi. Journal of Experimental Biology 154, 99–119.Google Scholar
Barnes, W.J.P. & Horridge, G.A (1969). Interaction of the movements of the two eyecups in the crab Carcinus. Journal of Experimental Biology 50, 651–671.Google Scholar
Barnes, W.J.P., Horseman, B.G., & Macauley, M.W.S. (2001). The detection and analysis of optic flow by crabs: from eye movements to electrophysiology. In The Crustacean Nervous System, ed. Wiese, K., pp. 468–485. Berlin, Heidelberg, New York: Springer Verlag.
Barnes, W.J.P., Johnson, A.P., Horseman, B.G., & Macauley, M.W.S. (2002). Computer-aided studies of vision in crabs. Marine and Freshwater Behaviour and Physiology 35, 37–56.Google Scholar
Barnes, W.J.P. & Nalbach, H.-O. (1993). Eye movements in freely moving crabs; their sensory basis and possible role in flow-field analysis. Comparative Biochemistry and Physiology 104A, 675–693.Google Scholar
Blanke, H., Nalbach, H.-O., & Varjú, D. (1997). Whole-field integration, not detailed analysis, is used by the crab optokinetic system to separate rotation and translation in optic flow. Journal of Comparative Physiology A 181, 383–392.Google Scholar
Collewijn, H. (1970). Oculomotor reactions of cuttlefish, Sepia officinalis. Journal of Experimental Biology 52, 369–384.Google Scholar
Cornilleau-Pérès, V. & Gielen, C.C.A.M. (1996). Interactions between self-motion and depth perception in the processing of optic flow. Trends in Neuroscience 19, 196–202.Google Scholar
Domenici, P., Jamon, M., & Clarac, F. (1998). Curve walking in freely walking crayfish (Procambarus clarkii). Journal of Experimental Biology 201, 1315–1329.Google Scholar
Easter, S.S., Johns, P.R., & Heckenlively, D. (1974). Horizontal compensatory eye movements in goldfish (Carrassius auratus). I. The normal animal. Journal of Comparative Physiology 92, 23–35.Google Scholar
Esch, H.E. & Burns, J.E. (1996). Distance estimation by foraging honeybees. Journal of Experimental Biology 199, 155–162.Google Scholar
Esch, H.E., Zhang, S., Srinivasan, M.V., & Tautz, J. (2001). Honeybee dances communicate distances measured by optic flow. Nature 411, 581–583.Google Scholar
Forman, R. & Brumbley, D. (1980). An improved capacitative position transducer for biological systems. Journal of Experimental Biology 88, 399–402.Google Scholar
Gibson, J.J. (1966). The Senses Considered as Perceptual Systems. Boston, Massachusetts: Houghton Mifflen.
Johnson, A.P. & Macauley, M.W.S. (2001). High precision timing within Microsoft Windows: threads, scheduling and system interrupts. Microprocessors and Microsystems 25, 297–307.Google Scholar
Johnson, A.P., Horseman, B.G., Barnes, W.J.P., & Macauley, M.W.S. (2002). A PC-based visual stimulus generator for behavioural and electrophysiological studies of optic flow detection. Journal of Neuroscience Methods 114, 51–61.Google Scholar
Johnson, A.P., Barnes, W.J.P., & Macauley, M.W.S. (2004). Local mechanisms for the separation of optic flow fields: A role for motion parallax? Visual Neuroscience 21, 905–911.Google Scholar
Kern, R., Nalbach, H.-O., & Varjú, D. (1993). Interactions of local movement detectors enhance the detection of rotation. Optokinetic experiments with the rock crab, Pachygrapsus marmoratus. Visual Neuroscience 10, 643–652.Google Scholar
Krapp, H.G. & Hengstenberg, R. (1996). Estimation of self-motion by optic flow processing in single visual interneurons. Nature 384, 463–466.Google Scholar
Land, M.F. (1999). Motion and vision: Why animals move their eyes. Journal of Comparative Physiology A 185, 341–352.Google Scholar
Lappe, M., ed. (2000). In Neuronal Processing of Optic Flow, p. 321. San Diego, London: Academic Press.
Layne, J.E., Barnes, W.J.P., & Duncan, L.M.J. (2003). Mechanisms of homing in the fiddler crab Uca rapax. 2. Information sources and frame of reference for a path integration system. Journal of Experimental Biology 206, 4425–4442.Google Scholar
Layne, J.E., Wicklein, M., Dodge, F.A., & Barlow, R.B. (1997). Prediction of maximal allowable retinal slip speed in the fiddler crab, Uca pugilator. Biological Bulletin 193, 202–203.Google Scholar
Nalbach, H.-O. (1990). Multisensory control of eye stalk orientation in decapod crustaceans: An ecological approach. Journal of Crustacean Biology 10, 382–399.Google Scholar
Nalbach, H.-O. & Nalbach, G. (1987). Distribution of optokinetic sensitivity over they eye of crabs: Its relation to habitat and possible role in flow-field analysis. Journal of Comparative Physiology 160, 127–135.Google Scholar
Nalbach, H.-O., Thier, P., & Varjú, D. (1985). Light-dependent eye-coupling during the optokinetic response of the crab, Carcinus maenas (L.). Journal of Experimental Biology 119, 103–114.Google Scholar
Nalbach, H.-O., Thier, P., & Varjú, D. (1993). Binocular interaction in the optokinetic system of the crab Carcinus maenas (L.): Optokinetic gain modified by bilateral image flow. Visual Neuroscience 10, 873–885.Google Scholar
Paul, H., Barnes, W.J.P., & Varjú, D. (1998). Roles of eyes, leg proprioceptors and statocysts in the compensatory eye movements of freely moving land crabs (Cardisoma guanhumi). Journal of Experimental Biology 201, 3395–3409.Google Scholar
Paul, H., Nalbach, H.-O., & Varjú, D. (1990). Eye movements in the rock crab Pachygrapsus marmoratus walking along straight and curved paths. Journal of Experimental Biology 154, 81–97.Google Scholar
Sandeman, D.C. (1978). Regionalization of the eye of the crab, Leptograpsus variegatus: Eye movements evoked by a target in different parts of the visual field. Journal of Comparative Physiology 123, 299–306.Google Scholar
Srinivasan, M.V., (1992). How bees exploit optic flow—behavioural experiments and neural models. Philosophical Transactions of the Royal Society 337, 253–259.Google Scholar
Srinivasan, M.V. (1993). How insects infer range from visual motion. In Visual Motion and Its Roles in the Stabilization of Gaze, ed. Miles, F.A. & Wallman, J., pp. 139–156. Amsterdam: Elsevier.
Tovée, M.J. (1996). An Introduction to the Visual System. Cambridge: Cambridge University Press.
Treue, S., Andersen, R.A., Ando, H., & Hildreth, E.C. (1995). Structure-from-motion: Perceptual evidence for surface interpolation. Vision Research 35, 139–148.Google Scholar
van den Berg, A.V. (1996). Optic flow and the kinematics of eye movements. Proceedings of the Royal Society B (London) 263, 957–981.Google Scholar
Warren, W.H., Jr. (1998). The state of flow. In High-Level Motion Processing: Computational, Neurobiological and Psychophysical Perspectives, ed. Watanabe, T., pp. 315–358. London, UK: MIT Press.
Warren, W.H., Jr. & Kurtz, K.J. (1992). The role of central and peripheral vision in perceiving the direction of self-motion. Perception and Psychophysics 5, 443–454.Google Scholar
Zanker, J.M. & Zeil, J., eds. (2001). In Motion Vision—Computational, Neural and Ecological Constraints, pp. 1–12. Berlin, Heidelberg, New York: Springer Verlag.