Computational modeling of brainstem circuits controlling locomotor frequency and gait

  1. Jessica Ausborn  Is a corresponding author
  2. Natalia A Shevtsova
  3. Vittorio Caggiano
  4. Simon M Danner
  5. Ilya A Rybak
  1. Drexel University College of Medicine, United States
  2. IBM, United States

Abstract

A series of recent studies identified key structures in the mesencephalic locomotor region and the caudal brainstem of mice involved in the initiation and control of slow (exploratory) and fast (escape-type) locomotion and gait. Yet, how these brainstem centers interact with each other and with the spinal locomotor circuits is poorly understood. In a previous model (Danner et al., 2017), we suggested that commissural and long propriospinal interneurons are the main targets for brainstem inputs adjusting gait. Here, by extending our previous model, we propose a connectome of the brainstem-spinal circuitry and suggest a mechanistic explanation of the operation of brainstem structures and their roles in controlling speed and gait. We suggest that brainstem control of locomotion is mediated by two pathways, one controlling locomotor speed via connections to rhythm generating circuits in the spinal cord and the other providing gait control by targeting commissural and long propriospinal interneurons.

Data availability

Source code and python scripts to create all simulations presented here are available on GitHub at https://github.com/SimonDanner/CPGNetworkSimulator

Article and author information

Author details

  1. Jessica Ausborn

    Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, United States
    For correspondence
    jessica.ausborn@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4500-5131
  2. Natalia A Shevtsova

    Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Vittorio Caggiano

    T J Watson Research Center, IBM, Yorktown Heights, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Simon M Danner

    Department for Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4642-7064
  5. Ilya A Rybak

    Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3461-349X

Funding

National Institutes of Health (R01NS095366)

  • Natalia A Shevtsova

National Institutes of Health (R01NS090919)

  • Ilya A Rybak

Edward Jekkal Muscular Dystrophy Association Fellowship

  • Jessica Ausborn

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

Reviewing Editor

  1. Ronald L Calabrese, Emory University, United States

Publication history

  1. Received: November 15, 2018
  2. Accepted: January 19, 2019
  3. Accepted Manuscript published: January 21, 2019 (version 1)
  4. Version of Record published: January 31, 2019 (version 2)

Copyright

© 2019, Ausborn 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.

Metrics

  • 2,153
    Page views
  • 374
    Downloads
  • 24
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Jessica Ausborn
  2. Natalia A Shevtsova
  3. Vittorio Caggiano
  4. Simon M Danner
  5. Ilya A Rybak
(2019)
Computational modeling of brainstem circuits controlling locomotor frequency and gait
eLife 8:e43587.
https://doi.org/10.7554/eLife.43587

Further reading

    1. Developmental Biology
    2. Neuroscience
    Ashtyn T Wiltbank et al.
    Research Article

    Efficient neurotransmission is essential for organism survival and is enhanced by myelination. However, the genes that regulate myelin and myelinating glial cell development have not been fully characterized. Data from our lab and others demonstrates that cd59, which encodes for a small GPI-anchored glycoprotein, is highly expressed in developing zebrafish, rodent, and human oligodendrocytes (OLs) and Schwann cells (SCs), and that patients with CD59 dysfunction develop neurological dysfunction during early childhood. Yet, the function of Cd59 in the developing nervous system is currently undefined. In this study, we demonstrate that cd59 is expressed in a subset of developing SCs. Using cd59 mutant zebrafish, we show that developing SCs proliferate excessively and nerves may have reduced myelin volume, altered myelin ultrastructure, and perturbed node of Ranvier assembly. Finally, we demonstrate that complement activity is elevated in cd59 mutants and that inhibiting inflammation restores SC proliferation, myelin volume, and nodes of Ranvier to wildtype levels. Together, this work identifies Cd59 and developmental inflammation as key players in myelinating glial cell development, highlighting the collaboration between glia and the innate immune system to ensure normal neural development.

    1. Neuroscience
    Arefeh Sherafati et al.
    Research Article Updated

    Cochlear implants are neuroprosthetic devices that can restore hearing in people with severe to profound hearing loss by electrically stimulating the auditory nerve. Because of physical limitations on the precision of this stimulation, the acoustic information delivered by a cochlear implant does not convey the same level of acoustic detail as that conveyed by normal hearing. As a result, speech understanding in listeners with cochlear implants is typically poorer and more effortful than in listeners with normal hearing. The brain networks supporting speech understanding in listeners with cochlear implants are not well understood, partly due to difficulties obtaining functional neuroimaging data in this population. In the current study, we assessed the brain regions supporting spoken word understanding in adult listeners with right unilateral cochlear implants (n=20) and matched controls (n=18) using high-density diffuse optical tomography (HD-DOT), a quiet and non-invasive imaging modality with spatial resolution comparable to that of functional MRI. We found that while listening to spoken words in quiet, listeners with cochlear implants showed greater activity in the left prefrontal cortex than listeners with normal hearing, specifically in a region engaged in a separate spatial working memory task. These results suggest that listeners with cochlear implants require greater cognitive processing during speech understanding than listeners with normal hearing, supported by compensatory recruitment of the left prefrontal cortex.