Abstract

Millions of neurons drive the activity of hundreds of muscles, meaning many different neural population activity patterns could generate the same movement. Studies have suggested that these redundant (i.e., behaviorally equivalent) activity patterns may be beneficial for neural computation. However, it is unknown what constraints may limit the selection of different redundant activity patterns. We leveraged a brain-computer interface, allowing us to define precisely which neural activity patterns were redundant. Rhesus monkeys made cursor movements by modulating neural activity in primary motor cortex. We attempted to predict the observed distribution of redundant neural activity. Principles inspired by work on muscular redundancy did not accurately predict these distributions. Surprisingly, the distributions of redundant neural activity and task-relevant activity were coupled, which enabled accurate predictions of the distributions of redundant activity. This suggests limits on the extent to which redundancy may be exploited by the brain for computation.

Data availability

Source data files have been provided for Figures 2-6. Code for analysis has been made available at https://github.com/mobeets/neural-redundancy-elife2018, with an MIT open source license (copy archived at https://github.com/elifesciences-publications/neural-redundancy-elife2018).

Article and author information

Author details

  1. Jay A Hennig

    Program in Neural Computation, Carnegie Mellon University, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7982-8553
  2. Matthew D Golub

    Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4508-0537
  3. Peter J Lund

    Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Patrick T Sadtler

    Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Emily R Oby

    Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Kristin M Quick

    Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Stephen I Ryu

    Department of Neurosurgery, Palo Alto Medical Foundation, Palo Alto, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Elizabeth C Tyler-Kabara

    Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Aaron P Batista

    Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Byron M Yu

    Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2252-6938
  11. Steven M Chase

    Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States
    For correspondence
    schase@cmu.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4450-6313

Funding

National Science Foundation (NCS BCS1533672)

  • Aaron P Batista
  • Byron M Yu
  • Steven M Chase

National Institutes of Health (R01 HD071686)

  • Aaron P Batista
  • Byron M Yu
  • Steven M Chase

National Science Foundation (Career award IOS1553252)

  • Steven M Chase

National Institutes of Health (CRCNS R01 NS105318)

  • Aaron P Batista
  • Byron M Yu

Craig H. Neilsen Foundation (280028)

  • Aaron P Batista
  • Byron M Yu
  • Steven M Chase

Simons Foundation (364994)

  • Byron M Yu

Pennsylvania Department of Health (Research Formula Grant SAP 4100077048)

  • Byron M Yu
  • Steven M Chase

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

Reviewing Editor

  1. Eric Shea-Brown, University of Washington, United States

Ethics

Animal experimentation: All animal handling procedures were approved by the University of Pittsburgh Institutional Animal Care and Use Committee (protocol #15096685) in accordance with NIH guidelines. All surgery was performed under general anesthesia and strictly sterile conditions, and every effort was made to minimize suffering.

Version history

  1. Received: March 18, 2018
  2. Accepted: August 6, 2018
  3. Accepted Manuscript published: August 15, 2018 (version 1)
  4. Version of Record published: September 5, 2018 (version 2)

Copyright

© 2018, Hennig 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. Jay A Hennig
  2. Matthew D Golub
  3. Peter J Lund
  4. Patrick T Sadtler
  5. Emily R Oby
  6. Kristin M Quick
  7. Stephen I Ryu
  8. Elizabeth C Tyler-Kabara
  9. Aaron P Batista
  10. Byron M Yu
  11. Steven M Chase
(2018)
Constraints on neural redundancy
eLife 7:e36774.
https://doi.org/10.7554/eLife.36774

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https://doi.org/10.7554/eLife.36774