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

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.

Data availability

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

Version 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.

Metrics

  • 6,925
    Page views
  • 1,135
    Downloads
  • 145
    Citations

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

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. 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

Share this article

https://doi.org/10.7554/eLife.29086

Further reading

    1. Neuroscience
    Peibo Xu, Jian Peng ... Yuejun Chen
    Research Article

    Deciphering patterns of connectivity between neurons in the brain is a critical step toward understanding brain function. Imaging-based neuroanatomical tracing identifies area-to-area or sparse neuron-to-neuron connectivity patterns, but with limited throughput. Barcode-based connectomics maps large numbers of single-neuron projections, but remains a challenge for jointly analyzing single-cell transcriptomics. Here, we established a rAAV2-retro barcode-based multiplexed tracing method that simultaneously characterizes the projectome and transcriptome at the single neuron level. We uncovered dedicated and collateral projection patterns of ventromedial prefrontal cortex (vmPFC) neurons to five downstream targets and found that projection-defined vmPFC neurons are molecularly heterogeneous. We identified transcriptional signatures of projection-specific vmPFC neurons, and verified Pou3f1 as a marker gene enriched in neurons projecting to the lateral hypothalamus, denoting a distinct subset with collateral projections to both dorsomedial striatum and lateral hypothalamus. In summary, we have developed a new multiplexed technique whose paired connectome and gene expression data can help reveal organizational principles that form neural circuits and process information.

    1. Neuroscience
    Maureen van der Grinten, Jaap de Ruyter van Steveninck ... Yağmur Güçlütürk
    Tools and Resources

    Blindness affects millions of people around the world. A promising solution to restoring a form of vision for some individuals are cortical visual prostheses, which bypass part of the impaired visual pathway by converting camera input to electrical stimulation of the visual system. The artificially induced visual percept (a pattern of localized light flashes, or ‘phosphenes’) has limited resolution, and a great portion of the field’s research is devoted to optimizing the efficacy, efficiency, and practical usefulness of the encoding of visual information. A commonly exploited method is non-invasive functional evaluation in sighted subjects or with computational models by using simulated prosthetic vision (SPV) pipelines. An important challenge in this approach is to balance enhanced perceptual realism, biologically plausibility, and real-time performance in the simulation of cortical prosthetic vision. We present a biologically plausible, PyTorch-based phosphene simulator that can run in real-time and uses differentiable operations to allow for gradient-based computational optimization of phosphene encoding models. The simulator integrates a wide range of clinical results with neurophysiological evidence in humans and non-human primates. The pipeline includes a model of the retinotopic organization and cortical magnification of the visual cortex. Moreover, the quantitative effects of stimulation parameters and temporal dynamics on phosphene characteristics are incorporated. Our results demonstrate the simulator’s suitability for both computational applications such as end-to-end deep learning-based prosthetic vision optimization as well as behavioral experiments. The modular and open-source software provides a flexible simulation framework for computational, clinical, and behavioral neuroscientists working on visual neuroprosthetics.