May 2003
Volume 44, Issue 13
ARVO Annual Meeting Abstract  |   May 2003
Robust Velocity Estimates by Fly Motion Detectors Following Motion Adaptation
Author Affiliations & Notes
  • A.D. Straw
    Department of Physiology, University of Adelaide, Adelaide, Australia
  • D.C. O'Carroll
    Department of Physiology, University of Adelaide, Adelaide, Australia
  • Footnotes
    Commercial Relationships  A.D. Straw, None; D.C. O'Carroll, None.
  • Footnotes
    Support  HHMI Predoctoral Fellowship, US AFOSR International Research Initiative
Investigative Ophthalmology & Visual Science May 2003, Vol.44, 4131. doi:
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      A.D. Straw, D.C. O'Carroll; Robust Velocity Estimates by Fly Motion Detectors Following Motion Adaptation . Invest. Ophthalmol. Vis. Sci. 2003;44(13):4131.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract: : Purpose:Studies in a wide range of organisms reveal contrast gain control as a prominent feature of early visual processing. Contrast gain reduction was recently shown to be a component of motion adaptation in hoverfly wide-field movement detecting (HS) neurons (Harris et al. 2000, Neuron 28:595-606). Sensitivity to contrast is a fundamental ambiguity for velocity coding associated with both Reichardt correlators and motion energy detectors. We investigated the possibility that this ambiguity is resolved by gain reduction during extended periods of natural image motion. Methods:We recorded intracellularly from HS neurons in restrained hoverflies viewing a CRT subtending ~100 degrees. Panoramic scenes obtained from natural habitats were perspective-distorted and temporally anti-aliased (motion blurred) during animation to simulate rotational optic flow. After a prolonged (4s) initial adaptation period, 200ms bursts of test speeds were interleaved with further adapting periods. We generated velocity-response curves at various combinations of contrast, adapting velocity, initial phase and choice of image. Results:HS cells responded to moving scenes across 3 decades of stimulus velocity, peaking at 100 deg. per second. The shape and magnitude of motion-adapted velocity tuning curves are robust over a large range of adapting speeds, or if global image contrast is reduced to as little as 25% of the original image. Fluctuations in the response appear to be noise in individual trials, but repeated stimulation shows much of this variability to be image feature dependent. Conclusions:Our results suggest that motion adaptation allows HS cells to provide reliable estimates of velocity in natural conditions, despite variability in global image contrast. We propose that such ‘velocity constancy’ results from a non-linear gain control in motion detector inputs. The greatest remaining source of ‘noise’ in the response arises from the spatial structure of the stimulus. Since our display stimulates a subset of the large receptive fields of these cells, it is likely that such pattern-induced response variability is minimized during natural behavior.

Keywords: motion-3D • electrophysiology: non-clinical • optic flow 

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