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.

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.

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

  • 3,523
    views
  • 713
    downloads
  • 70
    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. Neuroscience
    Friedrich Schuessler, Francesca Mastrogiuseppe ... Omri Barak
    Research Article

    The relation between neural activity and behaviorally relevant variables is at the heart of neuroscience research. When strong, this relation is termed a neural representation. There is increasing evidence, however, for partial dissociations between activity in an area and relevant external variables. While many explanations have been proposed, a theoretical framework for the relationship between external and internal variables is lacking. Here, we utilize recurrent neural networks (RNNs) to explore the question of when and how neural dynamics and the network’s output are related from a geometrical point of view. We find that training RNNs can lead to two dynamical regimes: dynamics can either be aligned with the directions that generate output variables, or oblique to them. We show that the choice of readout weight magnitude before training can serve as a control knob between the regimes, similar to recent findings in feedforward networks. These regimes are functionally distinct. Oblique networks are more heterogeneous and suppress noise in their output directions. They are furthermore more robust to perturbations along the output directions. Crucially, the oblique regime is specific to recurrent (but not feedforward) networks, arising from dynamical stability considerations. Finally, we show that tendencies toward the aligned or the oblique regime can be dissociated in neural recordings. Altogether, our results open a new perspective for interpreting neural activity by relating network dynamics and their output.

    1. Neuroscience
    Ji Eun Ryu, Kyu-Won Shim ... Eun Young Kim
    Research Article

    The circadian clock, an internal time-keeping system orchestrates 24 hr rhythms in physiology and behavior by regulating rhythmic transcription in cells. Astrocytes, the most abundant glial cells, play crucial roles in CNS functions, but the impact of the circadian clock on astrocyte functions remains largely unexplored. In this study, we identified 412 circadian rhythmic transcripts in cultured mouse cortical astrocytes through RNA sequencing. Gene Ontology analysis indicated that genes involved in Ca2+ homeostasis are under circadian control. Notably, Herpud1 (Herp) exhibited robust circadian rhythmicity at both mRNA and protein levels, a rhythm disrupted in astrocytes lacking the circadian transcription factor, BMAL1. HERP regulated endoplasmic reticulum (ER) Ca2+ release by modulating the degradation of inositol 1,4,5-trisphosphate receptors (ITPRs). ATP-stimulated ER Ca2+ release varied with the circadian phase, being more pronounced at subjective night phase, likely due to the rhythmic expression of ITPR2. Correspondingly, ATP-stimulated cytosolic Ca2+ increases were heightened at the subjective night phase. This rhythmic ER Ca2+ response led to circadian phase-dependent variations in the phosphorylation of Connexin 43 (Ser368) and gap junctional communication. Given the role of gap junction channel (GJC) in propagating Ca2+ signals, we suggest that this circadian regulation of ER Ca2+ responses could affect astrocytic modulation of synaptic activity according to the time of day. Overall, our study enhances the understanding of how the circadian clock influences astrocyte function in the CNS, shedding light on their potential role in daily variations of brain activity and health.