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Published March 28, 2008 | Published
Journal Article Open

Contrast sensitivity of insect motion detectors to natural images

Abstract

How do animals regulate self-movement despite large variation in the luminance contrast of the environment? Insects are capable of regulating flight speed based on the velocity of image motion, but the mechanisms for this are unclear. The Hassenstein–Reichardt correlator model and elaborations can accurately predict responses of motion detecting neurons under many conditions but fail to explain the apparent lack of spatial pattern and contrast dependence observed in freely flying bees and flies. To investigate this apparent discrepancy, we recorded intracellularly from horizontal-sensitive (HS) motion detecting neurons in the hoverfly while displaying moving images of natural environments. Contrary to results obtained with grating patterns, we show these neurons encode the velocity of natural images largely independently of the particular image used despite a threefold range of contrast. This invariance in response to natural images is observed in both strongly and minimally motion-adapted neurons but is sensitive to artificial manipulations in contrast. Current models of these cells account for some, but not all, of the observed insensitivity to image contrast. We conclude that fly visual processing may be matched to commonalities between natural scenes, enabling accurate estimates of velocity largely independent of the particular scene.

Additional Information

© ARVO 2008. Received September 27, 2007; published March 28, 2008. This work was supported through a Predoctoral Fellowship from the Howard Hughes Medical Institute to A.D.S. and grants from the United States Air Force Office of Scientific Research/Asian Office for Aerospace Research and Development. We thank Rebekah Smith for some of the digital photography, Russell Brinkworth for helpful comments on the manuscript, and the Botanical Gardens of Adelaide for allowing us to collect Eristalis. Commercial relationships: none.

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