1. Neuroscience
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Nonlinear circuits for naturalistic visual motion estimation

  1. James E Fitzgerald
  2. Damon A Clark  Is a corresponding author
  1. Harvard University, United States
  2. Yale University, United States
Research Article
  • Cited 18
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Cite this article as: eLife 2015;4:e09123 doi: 10.7554/eLife.09123


Many animals use visual signals to estimate motion. Canonical models suppose that animals estimate motion by cross-correlating pairs of spatiotemporally separated visual signals, but recent experiments indicate that humans and flies perceive motion from higher-order correlations that signify motion in natural environments. Here we show how biologically plausible processing motifs in neural circuits could be tuned to extract this information. We emphasize how known aspects of Drosophila's visual circuitry could embody this tuning and predict fly behavior. We find that segregating motion signals into ON/OFF channels can enhance estimation accuracy by accounting for natural light/dark asymmetries. Furthermore, a diversity of inputs to motion detecting neurons can provide access to more complex higher-order correlations. Collectively, these results illustrate how non-canonical computations improve motion estimation with naturalistic inputs. This argues that the complexity of the fly's motion computations, implemented in its elaborate circuits, represents a valuable feature of its visual motion estimator.

Article and author information

Author details

  1. James E Fitzgerald

    Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Damon A Clark

    MCDB, Yale University, New Haven, United States
    For correspondence
    Competing interests
    The authors declare that no competing interests exist.

Reviewing Editor

  1. Matteo Carandini, University College London, United Kingdom

Publication history

  1. Received: June 1, 2015
  2. Accepted: October 23, 2015
  3. Accepted Manuscript published: October 24, 2015 (version 1)
  4. Version of Record published: November 27, 2015 (version 2)


© 2015, Fitzgerald & Clark

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.


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