1. Neuroscience

Cell type-specific connectome predicts distributed working memory activity in the mouse brain

  1. Xingyu Ding
  2. Sean Froudist-Walsh
  3. Jorge Jaramillo
  4. Junjie Jiang
  5. Xiao-Jing Wang  Is a corresponding author
  1. New York University, United States
  2. University of Bristol, United Kingdom
  3. University of Göttingen, Germany
  4. Xi'an Jiaotong University, China
https://doi.org/10.7554/eLife.85442
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Cite this article
  1. Xingyu Ding
  2. Sean Froudist-Walsh
  3. Jorge Jaramillo
  4. Junjie Jiang
  5. Xiao-Jing Wang
(2024)
Cell type-specific connectome predicts distributed working memory activity in the mouse brain
eLife 13:e85442.
https://doi.org/10.7554/eLife.85442
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Abstract

Recent advances in connectome and neurophysiology make it possible to probe whole-brain mechanisms of cognition and behavior. We developed a large-scale model of the mouse multiregional brain for a cardinal cognitive function called working memory, the brain's ability to internally hold and process information without sensory input. The model is built on mesoscopic connectome data for inter-areal cortical connections and endowed with a macroscopic gradient of measured parvalbumin-expressing interneuron density. We found that working memory coding is distributed yet exhibits modularity; the spatial pattern of mnemonic representation is determined by long-range cell type-specific targeting and density of cell classes. Cell type-specific graph measures predict the activity patterns and a core subnetwork for memory maintenance. The model shows numerous self-sustained internal states (each engaging a distinct subset of areas). This work provides a framework to interpret large-scale recordings of brain activity during cognition, while highlighting the need for cell type-specific connectomics.

Data availability

The current manuscript is predominantly a computational study. Consequently, no new data was generated. However, the modeling code that underpins our findings has been made publicly available on GitHub, accessible via https://github.com/XY-DIng/mouse_dist_wm

The following previously published data sets were used

Article and author information

Author details

  1. Xingyu Ding

    Center for Neural Science, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  2. Sean Froudist-Walsh

    Bristol Computational Neuroscience Unit, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

  3. Jorge Jaramillo

    Campus Institute for Dynamics of Biological Networks, University of Göttingen, Göttingen, Germany
    Competing interests
    The authors declare that no competing interests exist.

  4. Junjie Jiang

    Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2930-7770

  5. Xiao-Jing Wang

    Center for Neural Science, New York University, New York, United States
    For correspondence
    xjwang@nyu.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3124-8474

Funding

National Institutes of Health (R01MH062349)

  • Xiao-Jing Wang

Office of Naval Research (N00014)

  • Xiao-Jing Wang

National Science Foundation (NeuroNex grant,2015276)

  • Xiao-Jing Wang

Simons Foundation (543057SPI)

  • Xiao-Jing Wang

National Institutes of Health (U19NS123714)

  • Xiao-Jing Wang

Biotechnology and Biological Sciences Research Council (BB/X013243/1)

  • Sean Froudist-Walsh

University of Bristol (Neuroscience of Mental Health Award)

  • Sean Froudist-Walsh

National Institutes of Health (U19NS123714)

  • Jorge Jaramillo

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

Reviewing Editor

  1. Carlos D Brody, Princeton University, United States

Version history

  1. Preprint posted: December 5, 2022 (view preprint)
  2. Received: December 8, 2022
  3. Accepted: December 14, 2023
  4. Accepted Manuscript published: January 4, 2024 (version 1)
  5. Version of Record published: January 24, 2024 (version 2)

Copyright

© 2024, Ding 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. Xingyu Ding
  2. Sean Froudist-Walsh
  3. Jorge Jaramillo
  4. Junjie Jiang
  5. Xiao-Jing Wang
(2024)
Cell type-specific connectome predicts distributed working memory activity in the mouse brain
eLife 13:e85442.
https://doi.org/10.7554/eLife.85442

Share this article

https://doi.org/10.7554/eLife.85442

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