1. Computational and Systems Biology
  2. Neuroscience

Spike-timing-dependent ensemble encoding by non-classically responsive cortical neurons

  1. Michele N Insanally
  2. Ioana Carcea
  3. Rachel E Field
  4. Chris C Rodgers
  5. Brian DePasquale
  6. Kanaka Rajan
  7. Michael R DeWeese
  8. Badr F Albanna
  9. Robert C Froemke  Is a corresponding author
  1. New York University School of Medicine, United States
  2. Columbia University, United States
  3. Princeton University, United States
  4. Icahn School of Medicine at Mount Sinai, United States
  5. University of California, Berkeley, United States
  6. Fordham University, United States
https://doi.org/10.7554/eLife.42409
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Cite this article
  1. Michele N Insanally
  2. Ioana Carcea
  3. Rachel E Field
  4. Chris C Rodgers
  5. Brian DePasquale
  6. Kanaka Rajan
  7. Michael R DeWeese
  8. Badr F Albanna
  9. Robert C Froemke
(2019)
Spike-timing-dependent ensemble encoding by non-classically responsive cortical neurons
eLife 8:e42409.
https://doi.org/10.7554/eLife.42409
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Abstract

Neurons recorded in behaving animals often do not discernibly respond to sensory input and are not overtly task-modulated. These non-classically responsive neurons are difficult to interpret and are typically neglected from analysis, confounding attempts to connect neural activity to perception and behavior. Here we describe a trial-by-trial, spike-timing-based algorithm to reveal the coding capacities of these neurons in auditory and frontal cortex of behaving rats. Classically responsive and non-classically responsive cells contained significant information about sensory stimuli and behavioral decisions. Stimulus category was more accurately represented in frontal cortex than auditory cortex, via ensembles of non-classically responsive cells coordinating the behavioral meaning of spike timings on correct but not error trials. This unbiased approach allows the contribution of all recorded neurons – particularly those without obvious task-related, trial-averaged firing rate modulation – to be assessed for behavioral relevance on single trials.

Data availability

The code and data underlying our analyses are freely available online (https://github.com/badralbanna/Insanally2017)

The following data sets were generated

Article and author information

Author details

  1. Michele N Insanally

    Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  2. Ioana Carcea

    Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Rachel E Field

    Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  4. Chris C Rodgers

    Department of Neuroscience, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  5. Brian DePasquale

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3830-3184

  6. Kanaka Rajan

    Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  7. Michael R DeWeese

    Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.

  8. Badr F Albanna

    Department of Natural Sciences, Fordham 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:" 0000-0002-5536-6443

  9. Robert C Froemke

    Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, United States
    For correspondence
    robert.froemke@med.nyu.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1230-6811

Funding

National Institute on Deafness and Other Communication Disorders (DC015543)

  • Michele N Insanally

Howard Hughes Medical Institute (Faculty Scholarship)

  • Robert C Froemke

NARSAD

  • Michele N Insanally
  • Ioana Carcea

James McDonnell

  • Kanaka Rajan

Sloan Research Fellowship

  • Robert C Froemke

National Institute on Deafness and Other Communication Disorders (DC009635)

  • Robert C Froemke

National Institute on Deafness and Other Communication Disorders (DC012557)

  • Robert C Froemke

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 procedures were performed in accordance with National Institutes of Health standards and were conducted under a protocol (#160611-03) approved by the New York University School of Medicine Institutional Animal Care and Use Committee.

Copyright

© 2019, Insanally 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.

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  1. Michele N Insanally
  2. Ioana Carcea
  3. Rachel E Field
  4. Chris C Rodgers
  5. Brian DePasquale
  6. Kanaka Rajan
  7. Michael R DeWeese
  8. Badr F Albanna
  9. Robert C Froemke
(2019)
Spike-timing-dependent ensemble encoding by non-classically responsive cortical neurons
eLife 8:e42409.
https://doi.org/10.7554/eLife.42409

Share this article

https://doi.org/10.7554/eLife.42409

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