Shared mechanisms of auditory and non-auditory vocal learning in the songbird brain
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.'
-
McGregor_et_al_Figure_4_Source_data_3.mat. figshare. Dataset.Figshare, 10.6084/m9.figshare.20183351.v1.
-
McGregor_et_al_Figure_4_Source_data_1.mat. figshare. Dataset.FigShare, 10.6084/m9.figshare.20183354.v1.
-
McGregor_et_al_Figure_3_Source_Code_3.m. figshare. Software.FigShare, 10.6084/m9.figshare.20183357.v1.
-
McGregor_et_al_Figure_4_Source_Code_2.m. figshare. Software.FigShare, 10.6084/m9.figshare.20183360.v1.
-
McGregor_et_al_Figure_3_Source_data_1.mat. figshare. Dataset.FigShare, 10.6084/m9.figshare.20183348.v1.
-
McGregor_et_al_Figure_4_Source_Code_3.m. figshare. Software.FigShare, 10.6084/m9.figshare.20183339.v1.
-
McGregor_et_al_Figure_4_Source_data_2.mat. figshare. Dataset.FigShare, 10.6084/m9.figshare.20183342.v1.
-
McGregor_et_al_Figure_2_Source_data_3.mat. figshare. Dataset.FigShare, 10.6084/m9.figshare.20183345.v1.
-
McGregor_et_al_Figure_3_Source_Code_2.m. figshare. Software.FigShare, 10.6084/m9.figshare.20183327.v1.
-
McGregor_et_al_Figure_3_Source_data_2.mat. figshare. Dataset.FigShare, 10.6084/m9.figshare.20183330.v1.
-
McGregor_et_al_Figure_2_Source_data_2.mat. figshare. Dataset.FigShare, 10.6084/m9.figshare.20183333.v1.
-
McGregor_et_al_Figure_3_Source_Code_4.m. figshare. Software.FigShare, 10.6084/m9.figshare.20183336.v1.
-
McGregor_et_al_Figure_2_Source_data_1.mat. figshare. Dataset.FigShare, 10.6084/m9.figshare.20183318.v1.
-
McGregor_et_al_Figure_3_Source_data_3.mat. figshare. Dataset.FigShare, 10.6084/m9.figshare.20183321.v1.
-
McGregor_et_al_Figure_4_Source_Code_1.m. figshare. Software.FigShare, 10.6084/m9.figshare.20183324.v1.
-
McGregor_et_al_Figure_2_Source_code_3.m. figshare. Software.FigShare, 10.6084/m9.figshare.20183315.v1.
-
McGregor_et_al_Figure_2_Source_code_4.m. figshare. Software.FigShare, 10.6084/m9.figshare.20183303.v1.
-
McGregor_et_al_Figure_2_Source_Code_1.m. figshare. Software.FigShare, 10.6084/m9.figshare.20183306.v1.
-
McGregor_et_al_Figure_2_Source_Code_2.m. figshare. Software.FigShare, 10.6084/m9.figshare.20183309.v1.
-
McGregor_et_al_Figure_3_Source_Code_1.m. figshare. Software.FigShare, 10.6084/m9.figshare.20183312.v1.
Article and author information
Author details
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
-
- 3,324
- views
-
- 495
- downloads
-
- 14
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
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)
Further reading
-
- Neuroscience
Complex macro-scale patterns of brain activity that emerge during periods of wakeful rest provide insight into the organisation of neural function, how these differentiate individuals based on their traits, and the neural basis of different types of self-generated thoughts. Although brain activity during wakeful rest is valuable for understanding important features of human cognition, its unconstrained nature makes it difficult to disentangle neural features related to personality traits from those related to the thoughts occurring at rest. Our study builds on recent perspectives from work on ongoing conscious thought that highlight the interactions between three brain networks – ventral and dorsal attention networks, as well as the default mode network. We combined measures of personality with state-of-the-art indices of ongoing thoughts at rest and brain imaging analysis and explored whether this ‘tri-partite’ view can provide a framework within which to understand the contribution of states and traits to observed patterns of neural activity at rest. To capture macro-scale relationships between different brain systems, we calculated cortical gradients to describe brain organisation in a low-dimensional space. Our analysis established that for more introverted individuals, regions of the ventral attention network were functionally more aligned to regions of the somatomotor system and the default mode network. At the same time, a pattern of detailed self-generated thought was associated with a decoupling of regions of dorsal attention from regions in the default mode network. Our study, therefore, establishes that interactions between attention systems and the default mode network are important influences on ongoing thought at rest and highlights the value of integrating contemporary perspectives on conscious experience when understanding patterns of brain activity at rest.
-
- Neuroscience
Gamma oscillations in brain activity (30–150 Hz) have been studied for over 80 years. Although in the past three decades significant progress has been made to try to understand their functional role, a definitive answer regarding their causal implication in perception, cognition, and behavior still lies ahead of us. Here, we first review the basic neural mechanisms that give rise to gamma oscillations and then focus on two main pillars of exploration. The first pillar examines the major theories regarding their functional role in information processing in the brain, also highlighting critical viewpoints. The second pillar reviews a novel research direction that proposes a therapeutic role for gamma oscillations, namely the gamma entrainment using sensory stimulation (GENUS). We extensively discuss both the positive findings and the issues regarding reproducibility of GENUS. Going beyond the functional and therapeutic role of gamma, we propose a third pillar of exploration, where gamma, generated endogenously by cortical circuits, is essential for maintenance of healthy circuit function. We propose that four classes of interneurons, namely those expressing parvalbumin (PV), vasointestinal peptide (VIP), somatostatin (SST), and nitric oxide synthase (NOS) take advantage of endogenous gamma to perform active vasomotor control that maintains homeostasis in the neuronal tissue. According to this hypothesis, which we call GAMER (GAmma MEdiated ciRcuit maintenance), gamma oscillations act as a ‘servicing’ rhythm that enables efficient translation of neural activity into vascular responses that are essential for optimal neurometabolic processes. GAMER is an extension of GENUS, where endogenous rather than entrained gamma plays a fundamental role. Finally, we propose several critical experiments to test the GAMER hypothesis.