1. Neuroscience
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Accelerating with FlyBrainLab the discovery of the functional logic of the Drosophila brain in the connectomic era

  1. Aurel A Lazar  Is a corresponding author
  2. Tingkai Liu
  3. Mehmet Kerem Turkcan
  4. Yiyin Zhou
  1. Columbia University, United States
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Cite this article as: eLife 2021;10:e62362 doi: 10.7554/eLife.62362

Abstract

In recent years, a wealth of Drosophila neuroscience data have become available including cell type, connectome/synaptome datasets for both the larva and adult fly. To facilitate integration across data modalities and to accelerate the understanding of the functional logic of the fly brain, we have developed FlyBrainLab, a unique open-source computing platform that integrates 3D exploration and visualization of diverse datasets with interactive exploration of the functional logic of modeled executable brain circuits. FlyBrainLab's User Interface, Utilities Libraries and Circuit Libraries bring together neuroanatomical, neurogenetic and electrophysiological datasets with computational models of different researchers for validation and comparison within the same platform. Seeking to transcend the limitations of the connectome/synaptome, FlyBrainLab also provides libraries for molecular transduction arising in sensory coding in vision/olfaction. Together with sensory neuron activity data, these libraries serve as entry points for the exploration, analysis, comparison and evaluation of circuit functions of the fruit fly brain.

Article and author information

Author details

  1. Aurel A Lazar

    Department of Electrical Engineering, Columbia University, New York, United States
    For correspondence
    aurel@ee.columbia.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4261-8709
  2. Tingkai Liu

    Department of Electrical Engineering, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3075-7648
  3. Mehmet Kerem Turkcan

    Department of Electrical Engineering, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9273-7293
  4. Yiyin Zhou

    Department of Electrical Engineering, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4618-4039

Funding

Air Force Office of Scientific Research (FA9550-16-1-0410)

  • Mehmet Kerem Turkcan

Defense Advanced Research Projects Agency (HR0011-19-9-0035)

  • Aurel A Lazar
  • Tingkai Liu
  • Mehmet Kerem Turkcan
  • Yiyin Zhou

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

Reviewing Editor

  1. Upinder Singh Bhalla, Tata Institute of Fundamental Research, India

Publication history

  1. Received: August 22, 2020
  2. Accepted: February 21, 2021
  3. Accepted Manuscript published: February 22, 2021 (version 1)

Copyright

© 2021, Lazar et al.

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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