A transient postnatal quiescent period precedes emergence of mature cortical dynamics

  1. Soledad Dominguez
  2. Liang Ma
  3. Han Yu
  4. Gabrielle Pouchelon
  5. Christian Mayer
  6. George D Spyropoulos
  7. Claudia Cea
  8. György Buzsáki
  9. Gordon Fishell
  10. Dion Khodagholy  Is a corresponding author
  11. Jennifer N Gelinas  Is a corresponding author
  1. Columbia University, United States
  2. Harvard University, United States
  3. Max Planck, Germany
  4. New York University, United States
  5. Harvard Medical School, United States

Abstract

Mature neural networks synchronize and integrate spatiotemporal activity patterns to support cognition. Emergence of these activity patterns and functions is believed to be developmentally regulated, but the postnatal time course for neural networks to perform complex computations remains unknown. We investigate the progression of large-scale synaptic and cellular activity patterns across development using high spatiotemporal resolution in vivo electrophysiology in immature mice. We reveal that mature cortical processes emerge rapidly and simultaneously after a discrete but volatile transition period at the beginning of the second postnatal week of rodent development. The transition is characterized by relative neural quiescence, after which spatially distributed, temporally precise, and internally organized activity occurs. We demonstrate a similar developmental trajectory in humans, suggesting an evolutionarily conserved mechanism that could facilitate a transition in network operation. We hypothesize that this transient quiescent period is a requisite for the subsequent emergence of coordinated cortical networks.

Data availability

Source data are presented in Supplementary Figures and uploaded to Dryad. Data pertaining to human subjects is governed by IRB policy and can be accessed through application to the IRB. Pooled, processed human subject data are uploaded to Dryad.

The following data sets were generated

Article and author information

Author details

  1. Soledad Dominguez

    Neurology, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Liang Ma

    Biomedical Engineering, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Han Yu

    Electrical Engineering, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Gabrielle Pouchelon

    Neurobiology, Harvard University, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Christian Mayer

    Neurobiology, Max Planck, Martinsried, Germany
    Competing interests
    The authors declare that no competing interests exist.
  6. George D Spyropoulos

    Electrical Engineering, Columbia University, new York, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Claudia Cea

    Electrical Engineering, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. György Buzsáki

    Neuroscience Institute, Langone Medical Center, Department of Neurology, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3100-4800
  9. Gordon Fishell

    Department of Neurobiology, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9640-9278
  10. Dion Khodagholy

    Electrical Engineering, Columbia University, New York, United States
    For correspondence
    dk2955@Columbia.edu
    Competing interests
    The authors declare that no competing interests exist.
  11. Jennifer N Gelinas

    Neurology, Columbia University, New York, United States
    For correspondence
    jng2146@cumc.columbia.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1164-638X

Funding

National Institutes of Health (R21 EY032381)

  • Dion Khodagholy
  • Jennifer N Gelinas

H2020 European Research Council (Marie Skłodowska-Curie grant agreement No 799501)

  • Soledad Dominguez

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 animal experiments were performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health and approved by the Institutional Animal Care and Use Committee at Columbia University Irving Medical Center.protocol AABI5568.

Human subjects: We retrospectively analyzed EEG recordings from 54 patients who underwent continuous monitoring with surface electroencephalography (EEG) as part of clinical diagnostic assessment. Analysis of these data were approved by the Institutional Review Board at Columbia University Irving Medical Center, and all data collection occurred at this institution. All data reviewed was initially obtained for clinical management purposes and informed consent was waived as per 45 CFR 46.116.

Reviewing Editor

  1. Sacha B Nelson, Brandeis University, United States

Publication history

  1. Preprint posted: February 17, 2021 (view preprint)
  2. Received: April 1, 2021
  3. Accepted: June 26, 2021
  4. Accepted Manuscript published: July 23, 2021 (version 1)
  5. Version of Record published: August 11, 2021 (version 2)

Copyright

© 2021, Dominguez 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

  • 1,487
    Page views
  • 263
    Downloads
  • 5
    Citations

Article citation count generated by polling the highest count across the following sources: PubMed Central, Crossref, Scopus.

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. Soledad Dominguez
  2. Liang Ma
  3. Han Yu
  4. Gabrielle Pouchelon
  5. Christian Mayer
  6. George D Spyropoulos
  7. Claudia Cea
  8. György Buzsáki
  9. Gordon Fishell
  10. Dion Khodagholy
  11. Jennifer N Gelinas
(2021)
A transient postnatal quiescent period precedes emergence of mature cortical dynamics
eLife 10:e69011.
https://doi.org/10.7554/eLife.69011

Further reading

    1. Neuroscience
    Flavia Venetucci Gouveia, Jurgen Germann ... Clement Hamani
    Research Article Updated

    Deep brain stimulation targeting the posterior hypothalamus (pHyp-DBS) is being investigated as a treatment for refractory aggressive behavior, but its mechanisms of action remain elusive. We conducted an integrated imaging analysis of a large multi-centre dataset, incorporating volume of activated tissue modeling, probabilistic mapping, normative connectomics, and atlas-derived transcriptomics. Ninety-one percent of the patients responded positively to treatment, with a more striking improvement recorded in the pediatric population. Probabilistic mapping revealed an optimized surgical target within the posterior-inferior-lateral region of the posterior hypothalamic area. Normative connectomic analyses identified fiber tracts and functionally connected with brain areas associated with sensorimotor function, emotional regulation, and monoamine production. Functional connectivity between the target, periaqueductal gray and key limbic areas – together with patient age – were highly predictive of treatment outcome. Transcriptomic analysis showed that genes involved in mechanisms of aggressive behavior, neuronal communication, plasticity and neuroinflammation might underlie this functional network.

    1. Chromosomes and Gene Expression
    2. Neuroscience
    Bradley M Colquitt, Kelly Li ... Michael S Brainard
    Research Article

    Sensory feedback is required for the stable execution of learned motor skills, and its loss can severely disrupt motor performance. The neural mechanisms that mediate sensorimotor stability have been extensively studied at systems and physiological levels, yet relatively little is known about how disruptions to sensory input alter the molecular properties of associated motor systems. Songbird courtship song, a model for skilled behavior, is a learned and highly structured vocalization that is destabilized following deafening. Here, we sought to determine how the loss of auditory feedback modifies gene expression and its coordination across the birdsong sensorimotor circuit. To facilitate this system-wide analysis of transcriptional responses, we developed a gene expression profiling approach that enables the construction of hundreds of spatially-defined RNA-sequencing libraries. Using this method, we found that deafening preferentially alters gene expression across birdsong neural circuitry relative to surrounding areas, particularly in premotor and striatal regions. Genes with altered expression are associated with synaptic transmission, neuronal spines, and neuromodulation and show a bias toward expression in glutamatergic neurons and Pvalb/Sst-class GABAergic interneurons. We also found that connected song regions exhibit correlations in gene expression that were reduced in deafened birds relative to hearing birds, suggesting that song destabilization alters the inter-region coordination of transcriptional states. Finally, lesioning LMAN, a forebrain afferent of RA required for deafening-induced song plasticity, had the largest effect on groups of genes that were also most affected by deafening. Combined, this integrated transcriptomics analysis demonstrates that the loss of peripheral sensory input drives a distributed gene expression response throughout associated sensorimotor neural circuitry and identifies specific candidate molecular and cellular mechanisms that support the stability and plasticity of learned motor skills.