Excitatory and inhibitory synapse reorganization immediately after critical sensory experience in a vocal learner

  1. Ziqiang Huang
  2. Houda G Khaled
  3. Moritz Kirschmann
  4. Sharon MH Gobes
  5. Richard HR Hahnloser  Is a corresponding author
  1. University of Zurich/ETH Zurich, Switzerland
  2. Wellesley College, United States

Abstract

Excitatory and inhibitory synapses are the brain's most abundant synapse types. However, little is known about their formation during critical periods of motor skill learning, when sensory experience defines a motor target that animals strive to imitate. In songbirds, we find that exposure to tutor song leads to elimination of excitatory synapses in HVC (used here as a proper name), a key song generating brain area. A similar pruning is associated with song maturation, because juvenile birds have fewer excitatory synapses, the better their song imitations. In contrast, tutoring is associated with rapid insertion of inhibitory synapses, but the tutoring-induced structural imbalance between excitation and inhibition is eliminated during subsequent song maturation. Our work suggests that sensory exposure triggers the developmental onset of goal-specific motor circuits by increasing the relative strength of inhibition and it suggests a synapse-elimination model of song memorization.

Data availability

We provide all SSEM synaptic density data for Experiments I and II in the Matlab file ssSEM_exp1and2_groupSeperated.mat. We provide all FIBSEM data for Experiment I in the Matlab file FIBSEM_exp1.mat. HVC volume data for Experiment II is provided in the Matlab file HVCvolume_exp2.mat.To reproduce our linear mixed effects analyses, we provide the Matlab function getLME. For example, to reproduce the comparison between synaptic densities in LONG and LONG60 birds, one first needs to load the data: load ssSEM_exp1and2_groupSeperated, then one needs to concatenate the relevant variables: data=vertcat(data_ssSEM_exp1_LONG,data_ssSEM_exp2_TUT60), and finally, one needs to run the function: getLME(data), followed by typing 1 for running the analysis for asymmetric synapses for example. All Matlab files can be retrieved from https://www.research-collection.ethz.ch/handle/20.500.11850/285394, DOI 10.3929/ethz-b-000285394.

The following data sets were generated

Article and author information

Author details

  1. Ziqiang Huang

    Institute of Neuroinformatics, University of Zurich/ETH Zurich, Zurich, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
  2. Houda G Khaled

    Neuroscience Program, Wellesley College, Wellesley, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0759-0272
  3. Moritz Kirschmann

    Institute of Neuroinformatics, University of Zurich/ETH Zurich, Zurich, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
  4. Sharon MH Gobes

    Neuroscience Program, Wellesley College, Wellesley, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Richard HR Hahnloser

    Institute of Neuroinformatics, University of Zurich/ETH Zurich, Zurich, Switzerland
    For correspondence
    rich@ini.ethz.ch
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4039-7773

Funding

Swiss National Science Foundation (31003A_127024)

  • Richard HR Hahnloser

ETH Zürich Foundation (Project 2015-48 3)

  • Richard HR Hahnloser

Swiss National Science Foundation (31003A_156976)

  • Richard HR Hahnloser

Swiss National Science Foundation (ZKOZ3_160663)

  • Richard HR Hahnloser

European Research Council (FP7/2007-2013 / ERC Grant AdG 268911)

  • Richard HR Hahnloser

Susan Todd Horton Class of 1910 Trust

  • Houda G Khaled

Hubel Neuroscience Summer Research Fellowship

  • Houda G Khaled

Seven College Conference Junior Year Abroad Award

  • Houda G Khaled

Five Faculty Awards from Wellesley College

  • Sharon MH Gobes

National Institutes of Health (R15HD085143)

  • Sharon MH Gobes

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

Reviewing Editor

  1. Catherine Emily Carr, University of Maryland, United States

Ethics

Animal experimentation: All experimental procedures were in accordance with the Veterinary Office of the Canton of Zurich (207-2013).

Version history

  1. Received: April 18, 2018
  2. Accepted: October 24, 2018
  3. Accepted Manuscript published: October 25, 2018 (version 1)
  4. Version of Record published: November 26, 2018 (version 2)

Copyright

© 2018, Huang 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

  • 11,779
    views
  • 429
    downloads
  • 12
    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. Ziqiang Huang
  2. Houda G Khaled
  3. Moritz Kirschmann
  4. Sharon MH Gobes
  5. Richard HR Hahnloser
(2018)
Excitatory and inhibitory synapse reorganization immediately after critical sensory experience in a vocal learner
eLife 7:e37571.
https://doi.org/10.7554/eLife.37571

Share this article

https://doi.org/10.7554/eLife.37571

Further reading

    1. Neuroscience
    Daniel Hoops, Robert Kyne ... Cecilia Flores
    Short Report

    Dopamine axons are the only axons known to grow during adolescence. Here, using rodent models, we examined how two proteins, Netrin-1 and its receptor, UNC5C, guide dopamine axons toward the prefrontal cortex and shape behaviour. We demonstrate in mice (Mus musculus) that dopamine axons reach the cortex through a transient gradient of Netrin-1-expressing cells – disrupting this gradient reroutes axons away from their target. Using a seasonal model (Siberian hamsters; Phodopus sungorus) we find that mesocortical dopamine development can be regulated by a natural environmental cue (daylength) in a sexually dimorphic manner – delayed in males, but advanced in females. The timings of dopamine axon growth and UNC5C expression are always phase-locked. Adolescence is an ill-defined, transitional period; we pinpoint neurodevelopmental markers underlying this period.

    1. Neuroscience
    Baba Yogesh, Georg B Keller
    Research Article

    Acetylcholine is released in visual cortex by axonal projections from the basal forebrain. The signals conveyed by these projections and their computational significance are still unclear. Using two-photon calcium imaging in behaving mice, we show that basal forebrain cholinergic axons in the mouse visual cortex provide a binary locomotion state signal. In these axons, we found no evidence of responses to visual stimuli or visuomotor prediction errors. While optogenetic activation of cholinergic axons in visual cortex in isolation did not drive local neuronal activity, when paired with visuomotor stimuli, it resulted in layer-specific increases of neuronal activity. Responses in layer 5 neurons to both top-down and bottom-up inputs were increased in amplitude and decreased in latency, whereas those in layer 2/3 neurons remained unchanged. Using opto- and chemogenetic manipulations of cholinergic activity, we found acetylcholine to underlie the locomotion-associated decorrelation of activity between neurons in both layer 2/3 and layer 5. Our results suggest that acetylcholine augments the responsiveness of layer 5 neurons to inputs from outside of the local network, possibly enabling faster switching between internal representations during locomotion.