EM connectomics reveals axonal target variation in a sequence-generating network

  1. Jörgen Kornfeld
  2. Sam E Benezra
  3. Rajeevan T Narayanan
  4. Fabian Svara
  5. Robert Egger
  6. Marcel Oberlaender
  7. Winfried Denk
  8. Michael A Long  Is a corresponding author
  1. Max Planck Institute of Neurobiology, Germany
  2. New York University Langone Medical Center, United States
  3. Max Planck Institute for Biological Cybernetics, Germany

Abstract

The sequential activation of neurons has been observed in various areas of the brain, but in no case is the underlying network structure well understood. Here we examined the circuit anatomy of zebra finch HVC, a cortical region that generates sequences underlying the temporal progression of the song. We combined serial block-face electron microscopy with light microscopy to determine the cell types targeted by HVC(RA) neurons, which control song timing. Close to their soma, axons almost exclusively targeted inhibitory interneurons, consistent with what had been found with electrical recordings from pairs of cells. Conversely, far from the soma the targets were mostly other excitatory neurons, about half of these being other HVC(RA) cells. Both observations are consistent with the notion that the neural sequences that pace the song are generated by global synaptic chains in HVC embedded within local inhibitory networks.

Article and author information

Author details

  1. Jörgen Kornfeld

    Max Planck Institute of Neurobiology, Martinsried, Germany
    Competing interests
    The authors declare that no competing interests exist.
  2. Sam E Benezra

    NYU Neuroscience Institute, New York University Langone Medical Center, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Rajeevan T Narayanan

    Computational Neuroanatomy Group, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  4. Fabian Svara

    Max Planck Institute of Neurobiology, Martinsried, Germany
    Competing interests
    The authors declare that no competing interests exist.
  5. Robert Egger

    NYU Neuroscience Institute, New York University Langone Medical Center, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Marcel Oberlaender

    Computational Neuroanatomy Group, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  7. Winfried Denk

    Max Planck Institute of Neurobiology, Martinsried, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0704-6998
  8. Michael A Long

    NYU Neuroscience Institute, New York University Langone Medical Center, New York, United States
    For correspondence
    mlong@nyumc.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9283-3741

Funding

National Institutes of Health (R01NS075044)

  • Michael A Long

New York Stem Cell Foundation (NYSCF-R-NI18)

  • Michael A Long

Rita Allen Foundation (Rita Allen)

  • Michael A Long

Max Planck Society (Max Planck)

  • Jörgen Kornfeld
  • Rajeevan T Narayanan
  • Fabian Svara
  • Marcel Oberlaender
  • Winfried Denk

Bernstein Center for Computational Neuroscience Tübingen

  • Rajeevan T Narayanan
  • Marcel Oberlaender

Boehringer Ingelheim Fonds

  • Jörgen Kornfeld
  • Fabian Svara

European Research Council (633428)

  • Rajeevan T Narayanan
  • Marcel Oberlaender

German Federal Ministry of Education and Research Grant

  • Rajeevan T Narayanan
  • Marcel Oberlaender

European Union's Horizon 2020

  • Rajeevan T Narayanan
  • Marcel Oberlaender

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

Reviewing Editor

  1. Karel Svoboda, Janelia Research Campus, Howard Hughes Medical Institute, United States

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols of the New York University Medical Center.Our songbird protocol, entitled 'Understanding birdsong circuitry', was recently renewed. The protocol number is 161102-01.

Version history

  1. Received: December 17, 2016
  2. Accepted: March 23, 2017
  3. Accepted Manuscript published: March 27, 2017 (version 1)
  4. Version of Record published: April 21, 2017 (version 2)

Copyright

© 2017, Kornfeld 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

  • 3,377
    views
  • 692
    downloads
  • 66
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

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. Jörgen Kornfeld
  2. Sam E Benezra
  3. Rajeevan T Narayanan
  4. Fabian Svara
  5. Robert Egger
  6. Marcel Oberlaender
  7. Winfried Denk
  8. Michael A Long
(2017)
EM connectomics reveals axonal target variation in a sequence-generating network
eLife 6:e24364.
https://doi.org/10.7554/eLife.24364

Share this article

https://doi.org/10.7554/eLife.24364

Further reading

    1. Cell Biology
    2. Neuroscience
    Marcos Moreno-Aguilera, Alba M Neher ... Carme Gallego
    Research Article Updated

    Alternative RNA splicing is an essential and dynamic process in neuronal differentiation and synapse maturation, and dysregulation of this process has been associated with neurodegenerative diseases. Recent studies have revealed the importance of RNA-binding proteins in the regulation of neuronal splicing programs. However, the molecular mechanisms involved in the control of these splicing regulators are still unclear. Here, we show that KIS, a kinase upregulated in the developmental brain, imposes a genome-wide alteration in exon usage during neuronal differentiation in mice. KIS contains a protein-recognition domain common to spliceosomal components and phosphorylates PTBP2, counteracting the role of this splicing factor in exon exclusion. At the molecular level, phosphorylation of unstructured domains within PTBP2 causes its dissociation from two co-regulators, Matrin3 and hnRNPM, and hinders the RNA-binding capability of the complex. Furthermore, KIS and PTBP2 display strong and opposing functional interactions in synaptic spine emergence and maturation. Taken together, our data uncover a post-translational control of splicing regulators that link transcriptional and alternative exon usage programs in neuronal development.

    1. Genetics and Genomics
    2. Neuroscience
    Kenneth Chiou, Noah Snyder-Mackler
    Insight

    Single-cell RNA sequencing reveals the extent to which marmosets carry genetically distinct cells from their siblings.