The rate of transient beta frequency events predicts behavior across tasks and species

  1. Hyeyoung Shin  Is a corresponding author
  2. Robert Law
  3. Shawn Tsutsui
  4. Christopher I Moore
  5. Stephanie R Jones  Is a corresponding author
  1. Brown University, United States

Abstract

Beta oscillations (15-29Hz) are among the most prominent signatures of brain activity. Beta power is predictive of healthy and abnormal behaviors, including perception, attention and motor action. In non-averaged signals, beta can emerge as transient high-power 'events'. As such, functionally relevant differences in averaged power across time and trials can reflect changes in event number, power, duration, and / or frequency span. We show that functionally relevant differences in averaged beta power in primary somatosensory neocortex reflect a difference in the number of high-power beta events per trial, i.e. event rate. Further, beta events occurring close to the stimulus were more likely to impair perception. These results are consistent across detection and attention tasks in human magnetoencephalography, and in local field potentials from mice performing a detection task. These results imply that an increased propensity of beta events predicts the failure to effectively transmit information through specific neocortical representations.

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The following data sets were generated

Article and author information

Author details

  1. Hyeyoung Shin

    Department of Neuroscience, Brown University, Providence, United States
    For correspondence
    shinehyeyoung@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7587-8577
  2. Robert Law

    Department of Neuroscience, Brown University, Providence, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Shawn Tsutsui

    Department of Neuroscience, Brown University, Providence, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3805-1519
  4. Christopher I Moore

    Department of Neuroscience, Brown University, Providence, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Stephanie R Jones

    Department of Neuroscience, Brown University, Providence, United States
    For correspondence
    Stephanie_Jones@brown.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6760-5301

Funding

National Institute of Mental Health (R01MH106174)

  • Stephanie R Jones

Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Rehabilitation Research and Development Service (N9228-C)

  • Stephanie R Jones

National Institute of Neurological Disorders and Stroke (R01NS045130)

  • Christopher I Moore

Brown Institute for Brain Science

  • Hyeyoung Shin

Fulbright Association

  • Hyeyoung Shin

National Science Foundation Collaborative Research in Computational Neuroscience (NSF CRCNS-1131850)

  • Stephanie R Jones

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 procedures and animal care protocols were approved by Brown University Institutional Animal Care and Use Committees and were in accordance with US National Institutes of Health guidelines. All surgery was performed under isofluorane anesthesia, and every effort was made to minimize suffering.

Human subjects: All MEG experimental protocols were approved by the Massachusetts General Hospital Internal Review Board, and each subject gave informed consent before data acquisition.

Reviewing Editor

  1. Yoshinao Kajikawa, The Nathan S. Kline Institute for Psychiatric Research, United States

Publication history

  1. Received: May 30, 2017
  2. Accepted: November 3, 2017
  3. Accepted Manuscript published: November 6, 2017 (version 1)
  4. Version of Record published: November 13, 2017 (version 2)
  5. Version of Record updated: November 16, 2017 (version 3)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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  1. Hyeyoung Shin
  2. Robert Law
  3. Shawn Tsutsui
  4. Christopher I Moore
  5. Stephanie R Jones
(2017)
The rate of transient beta frequency events predicts behavior across tasks and species
eLife 6:e29086.
https://doi.org/10.7554/eLife.29086

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