1. Neuroscience

The cellular architecture of memory modules in Drosophila supports stochastic input integration

  1. Omar A Hafez
  2. Benjamin Escribano
  3. Rouven L Ziegler
  4. Jan J Hirtz
  5. Ernst Niebur  Is a corresponding author
  6. Jan Pielage  Is a corresponding author
  1. Johns Hopkins University, United States
  2. University of Kaiserslautern, Germany
https://doi.org/10.7554/eLife.77578
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  1. Omar A Hafez
  2. Benjamin Escribano
  3. Rouven L Ziegler
  4. Jan J Hirtz
  5. Ernst Niebur
  6. Jan Pielage
(2023)
The cellular architecture of memory modules in Drosophila supports stochastic input integration
eLife 12:e77578.
https://doi.org/10.7554/eLife.77578
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Abstract

The ability to associate neutral stimuli with valence information and to store these associations as memories forms the basis for decision making. To determine the underlying computational principles, we build a realistic computational model of a central decision module within the Drosophila mushroom body (MB), the fly's center for learning and memory. Our model combines the electron microscopy-based architecture of one MB output neuron (MBON-α3), the synaptic connectivity of its 948 presynaptic Kenyon cells (KCs), and its membrane properties obtained from patch-clamp recordings. We show that this neuron is electrotonically compact and that synaptic input corresponding to simulated odor input robustly drives its spiking behavior. Therefore, sparse innervation by KCs can efficiently control and modulate MBON activity in response to learning with minimal requirements on the specificity of synaptic localization. This architecture allows efficient storage of large numbers of memories using the flexible stochastic connectivity of the circuit.

Data availability

All data generated or analysed in this study are included in the manuscript.All simulation files and the code and data files needed to replicate the simulations are available as a permanent and freely accessible data collection at the Johns Hopkins University Data Archive:https://doi.org/10.7281/T1/HRK27V.This includes the simulation code itself (python), the structural EM reconstruction of MBON-alpha3 (swc), the EM reconstruction of the related MBON used to model the axon and synaptic terminal structures (swc), the synapse locations as coordinate data (json), and the synapse locations by MBON section (json). Parameter values for model definition and individual simulations are specified within the code files and outlined in each figure legend where appropriate.

Article and author information

Author details

  1. Omar A Hafez

    Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.

  2. Benjamin Escribano

    Department of Biology, University of Kaiserslautern, Kaiserslautern, Germany
    Competing interests
    The authors declare that no competing interests exist.

  3. Rouven L Ziegler

    Department of Biology, University of Kaiserslautern, Kaiserslautern, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3050-7692

  4. Jan J Hirtz

    Department of Biology, University of Kaiserslautern, Kaiserslautern, Germany
    Competing interests
    The authors declare that no competing interests exist.

  5. Ernst Niebur

    Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, United States
    For correspondence
    niebur@jhu.edu
    Competing interests
    The authors declare that no competing interests exist.

  6. Jan Pielage

    Department of Biology, University of Kaiserslautern, Kaiserslautern, Germany
    For correspondence
    pielage@bio.uni-kl.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5115-5884

Funding

National Institutes of Health (R01DC020123)

  • Ernst Niebur

National Institutes of Health (R01DA040990)

  • Ernst Niebur

National Institutes of Health (R01EY027544)

  • Ernst Niebur

National Institutes of Health (Medical Scientist Training Program 708 Training Grant T32GM136651)

  • Ernst Niebur

National Science Foundation (1835202)

  • Ernst Niebur

Bundesministerium für Bildung und Forschung (FKZ 01GQ2105)

  • Jan Pielage

Deutsche Forschungsgemeinschaft (INST 248/293-1)

  • Jan Pielage

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

Reviewing Editor

  1. Albert Cardona, University of Cambridge, United Kingdom

Version history

  1. Preprint posted: December 7, 2020 (view preprint)
  2. Received: February 3, 2022
  3. Accepted: March 9, 2023
  4. Accepted Manuscript published: March 14, 2023 (version 1)
  5. Accepted Manuscript updated: March 14, 2023 (version 2)
  6. Accepted Manuscript updated: March 15, 2023 (version 3)
  7. Version of Record published: April 3, 2023 (version 4)

Copyright

© 2023, Hafez 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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  1. Omar A Hafez
  2. Benjamin Escribano
  3. Rouven L Ziegler
  4. Jan J Hirtz
  5. Ernst Niebur
  6. Jan Pielage
(2023)
The cellular architecture of memory modules in Drosophila supports stochastic input integration
eLife 12:e77578.
https://doi.org/10.7554/eLife.77578

Share this article

https://doi.org/10.7554/eLife.77578

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