1. Neuroscience
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Biophysics of object segmentation in a collision-detecting neuron

  1. Richard Burkett Dewell
  2. Fabrizio Gabbiani  Is a corresponding author
  1. Baylor College of Medicine, United States
Research Article
  • Cited 6
  • Views 1,419
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Cite this article as: eLife 2018;7:e34238 doi: 10.7554/eLife.34238

Abstract

Collision avoidance is critical for survival, including in humans, and many species possess visual neurons exquisitely sensitive to objects approaching on a collision course. Here, we demonstrate that a collision-detecting neuron can detect the spatial coherence of a simulated impending object, thereby carrying out a computation akin to object segmentation critical for proper escape behavior. At the cellular level, object segmentation relies on a precise selection of the spatiotemporal pattern of synaptic inputs by dendritic membrane potential-activated channels. One channel type linked to dendritic computations in many neural systems, the hyperpolarization-activated cation channel, HCN, plays a central role in this computation. Pharmacological block of HCN channels abolishes the neuron's spatial selectivity and impairs the generation of visually guided escape behaviors, making it directly relevant to survival. Additionally, our results suggest that the interaction of HCN and inactivating K+ channels within active dendrites produces neuronal and behavioral object specificity by discriminating between complex spatiotemporal synaptic activation patterns.

Article and author information

Author details

  1. Richard Burkett Dewell

    Department of Neuroscience, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2430-8184
  2. Fabrizio Gabbiani

    Department of Neuroscience, Baylor College of Medicine, Houston, United States
    For correspondence
    gabbiani@bcm.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4966-3027

Funding

National Institutes of Health (MH065339)

  • Fabrizio Gabbiani

National Science Foundation (DMS-1120952)

  • Fabrizio Gabbiani

National Science Foundation (IIS-1607518)

  • Fabrizio Gabbiani

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Fred Rieke, Howard Hughes Medical Institute, University of Washington, United States

Publication history

  1. Received: December 11, 2017
  2. Accepted: April 4, 2018
  3. Accepted Manuscript published: April 18, 2018 (version 1)
  4. Version of Record published: May 11, 2018 (version 2)
  5. Version of Record updated: November 9, 2018 (version 3)

Copyright

© 2018, Dewell & Gabbiani

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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