1. Neuroscience
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Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance

  1. Ruedeerat Keerativittayayut
  2. Ryuta Aoki  Is a corresponding author
  3. Mitra Taghizadeh Sarabi
  4. Koji Jimura
  5. Kiyoshi Nakahara  Is a corresponding author
  1. Kochi University of Technology, Japan
  2. Keio University, Japan
Research Article
  • Cited 3
  • Views 2,134
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Cite this article as: eLife 2018;7:e32696 doi: 10.7554/eLife.32696

Abstract

Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30–40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding.

Article and author information

Author details

  1. Ruedeerat Keerativittayayut

    School of Information, Kochi University of Technology, Kami, Japan
    Competing interests
    The authors declare that no competing interests exist.
  2. Ryuta Aoki

    Research Center for Brain Communication, Kochi University of Technology, Kami, Japan
    For correspondence
    qqqqaokiq@yahoo.co.jp
    Competing interests
    The authors declare that no competing interests exist.
  3. Mitra Taghizadeh Sarabi

    School of Information, Kochi University of Technology, Kami, Japan
    Competing interests
    The authors declare that no competing interests exist.
  4. Koji Jimura

    Department of Biosciences and Informatics, Keio University, Yokohama, Japan
    Competing interests
    The authors declare that no competing interests exist.
  5. Kiyoshi Nakahara

    School of Information, Kochi University of Technology, Kami, Japan
    For correspondence
    nakahara.kiyoshi@kochi-tech.ac.jp
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6701-6216

Funding

Japan Society for the Promotion of Science (17H00891)

  • Ryuta Aoki
  • Koji Jimura
  • Kiyoshi Nakahara

Japan Society for the Promotion of Science (17H06268)

  • Kiyoshi Nakahara

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

Ethics

Human subjects: All experimental procedures were approved by the Ethics Committee of Kochi University of Technology. Informed consent was obtained from all participants.

Reviewing Editor

  1. Roberto Cabeza, Duke University, United States

Publication history

  1. Received: October 11, 2017
  2. Accepted: June 16, 2018
  3. Accepted Manuscript published: June 18, 2018 (version 1)
  4. Version of Record published: July 10, 2018 (version 2)
  5. Version of Record updated: July 29, 2019 (version 3)

Copyright

© 2018, Keerativittayayut 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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