1. Neuroscience

Shared mechanisms of auditory and non-auditory vocal learning in the songbird brain

  1. James N McGregor  Is a corresponding author
  2. Abigail L Grassler
  3. Paul I Jaffe
  4. Amanda Louise Jacob
  5. Michael S Brainard
  6. Samuel J Sober
  1. Emory University, United States
  2. University of California, San Francisco, United States
https://doi.org/10.7554/eLife.75691
Share this article
Cite this article
  1. James N McGregor
  2. Abigail L Grassler
  3. Paul I Jaffe
  4. Amanda Louise Jacob
  5. Michael S Brainard
  6. Samuel J Sober
(2022)
Shared mechanisms of auditory and non-auditory vocal learning in the songbird brain
eLife 11:e75691.
https://doi.org/10.7554/eLife.75691
  2. Download BibTeX
  3. Download .RIS

Abstract

Songbirds and humans share the ability to adaptively modify their vocalizations based on sensory feedback. Prior studies have focused primarily on the role that auditory feedback plays in shaping vocal output throughout life. In contrast, it is unclear how non-auditory information drives vocal plasticity. Here, we first used a reinforcement learning paradigm to establish that somatosensory feedback (cutaneous electrical stimulation) can drive vocal learning in adult songbirds. We then assessed the role of a songbird basal ganglia thalamocortical pathway critical to auditory vocal learning in this novel form of vocal plasticity. We found that both this circuit and its dopaminergic inputs are necessary for non-auditory vocal learning, demonstrating that this pathway is critical for guiding adaptive vocal changes based on both auditory and somatosensory signals. The ability of this circuit to use both auditory and somatosensory information to guide vocal learning may reflect a general principle for the neural systems that support vocal plasticity across species.

Data availability

Source data are provided for all main figures and relevant figure supplements (Figure 2b-f, Figure 2 - Figure Supplements 1-7, Figure 3b-e, Figure 3 - Figure Supplement 1, and Figure 4b-d). MATLAB code for generating these figures is also provided in the associated source code files. Data and source code have also been uploaded to a public data repository on figshare, in a project titled 'Shared mechanisms of auditory and non-auditory vocal learning in the songbird brain.'

The following data sets were generated

Article and author information

Author details

  1. James N McGregor

    Neuroscience Graduate Program, Emory University, Atlanta, United States
    For correspondence
    jmcgregor2292@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5187-0984

  2. Abigail L Grassler

    Neuroscience Graduate Program, Emory University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Paul I Jaffe

    Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0680-3923

  4. Amanda Louise Jacob

    Department of Biology, Emory University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.

  5. Michael S Brainard

    Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9425-9907

  6. Samuel J Sober

    Department of Biology, Emory University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1140-7469

Funding

National Institutes of Health (R01- EB022872)

  • James N McGregor
  • Abigail L Grassler
  • Amanda Louise Jacob
  • Samuel J Sober

National Institutes of Health (R01- NS084844)

  • James N McGregor
  • Abigail L Grassler
  • Amanda Louise Jacob
  • Samuel J Sober

National Institutes of Health (R01- NS099375)

  • James N McGregor
  • Abigail L Grassler
  • Amanda Louise Jacob
  • Samuel J Sober

Simons Foundation (Emory International Consortium on Motor Control)

  • Samuel J Sober

Howard Hughes Medical Institute

  • Paul I Jaffe
  • Michael S Brainard

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

Ethics

Animal experimentation: All experimental protocols were approved by the Emory University and UC San Francisco Institutional Animal Care and Use Committees (protocol #201700359)

Copyright

© 2022, McGregor 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

  • 3,396
    views
  • 509
    downloads
  • 14
    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. James N McGregor
  2. Abigail L Grassler
  3. Paul I Jaffe
  4. Amanda Louise Jacob
  5. Michael S Brainard
  6. Samuel J Sober
(2022)
Shared mechanisms of auditory and non-auditory vocal learning in the songbird brain
eLife 11:e75691.
https://doi.org/10.7554/eLife.75691

Share this article

https://doi.org/10.7554/eLife.75691

Categories and tags

Further reading

    1. Neuroscience

    The NeuroML ecosystem for standardized multi-scale modeling in neuroscience

    Ankur Sinha, Padraig Gleeson ... Robin Angus Silver
    Tools and Resources

    Data-driven models of neurons and circuits are important for understanding how the properties of membrane conductances, synapses, dendrites, and the anatomical connectivity between neurons generate the complex dynamical behaviors of brain circuits in health and disease. However, the inherent complexity of these biological processes makes the construction and reuse of biologically detailed models challenging. A wide range of tools have been developed to aid their construction and simulation, but differences in design and internal representation act as technical barriers to those who wish to use data-driven models in their research workflows. NeuroML, a model description language for computational neuroscience, was developed to address this fragmentation in modeling tools. Since its inception, NeuroML has evolved into a mature community standard that encompasses a wide range of model types and approaches in computational neuroscience. It has enabled the development of a large ecosystem of interoperable open-source software tools for the creation, visualization, validation, and simulation of data-driven models. Here, we describe how the NeuroML ecosystem can be incorporated into research workflows to simplify the construction, testing, and analysis of standardized models of neural systems, and supports the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, thus promoting open, transparent and reproducible science.

    1. Neuroscience

    Parabrachial CGRP neurons modulate active defensive behavior under a naturalistic threat

    Gyeong Hee Pyeon, Hyewon Cho ... Yong Sang Jo
    Research Article

    Recent studies suggest that calcitonin gene-related peptide (CGRP) neurons in the parabrachial nucleus (PBN) represent aversive information and signal a general alarm to the forebrain. If CGRP neurons serve as a true general alarm, their activation would modulate both passive nad active defensive behaviors depending on the magnitude and context of the threat. However, most prior research has focused on the role of CGRP neurons in passive freezing responses, with limited exploration of their involvement in active defensive behaviors. To address this, we examined the role of CGRP neurons in active defensive behavior using a predator-like robot programmed to chase mice. Our electrophysiological results revealed that CGRP neurons encode the intensity of aversive stimuli through variations in firing durations and amplitudes. Optogenetic activation of CGRP neuron during robot chasing elevated flight responses in both conditioning and retention tests, presumably by amyplifying the perception of the threat as more imminent and dangerous. In contrast, animals with inactivated CGRP neurons exhibited reduced flight responses, even when the robot was programmed to appear highly threatening during conditioning. These findings expand the understanding of CGRP neurons in the PBN as a critical alarm system, capable of dynamically regulating active defensive behaviors by amplifying threat perception, ensuring adaptive responses to varying levels of danger.

    1. Neuroscience

    Mapping patterns of thought onto brain activity during movie-watching

    Raven Star Wallace, Bronte Mckeown ... Jonathan Smallwood
    Research Article

    Movie-watching is a central aspect of our lives and an important paradigm for understanding the brain mechanisms behind cognition as it occurs in daily life. Contemporary views of ongoing thought argue that the ability to make sense of events in the ‘here and now’ depend on the neural processing of incoming sensory information by auditory and visual cortex, which are kept in check by systems in association cortex. However, we currently lack an understanding of how patterns of ongoing thoughts map onto the different brain systems when we watch a film, partly because methods of sampling experience disrupt the dynamics of brain activity and the experience of movie-watching. Our study established a novel method for mapping thought patterns onto the brain activity that occurs at different moments of a film, which does not disrupt the time course of brain activity or the movie-watching experience. We found moments when experience sampling highlighted engagement with multi-sensory features of the film or highlighted thoughts with episodic features, regions of sensory cortex were more active and subsequent memory for events in the movie was better—on the other hand, periods of intrusive distraction emerged when activity in regions of association cortex within the frontoparietal system was reduced. These results highlight the critical role sensory systems play in the multi-modal experience of movie-watching and provide evidence for the role of association cortex in reducing distraction when we watch films.