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

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.

Data availability

The data that support the findings of this study are openly available in Dryad Digital Repository (https://datadryad.org/).

The following data sets were generated

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.

Reviewing Editor

  1. Roberto Cabeza, Duke University, United States

Ethics

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

Version 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.

Metrics

  • 3,140
    views
  • 435
    downloads
  • 25
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

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. Ruedeerat Keerativittayayut
  2. Ryuta Aoki
  3. Mitra Taghizadeh Sarabi
  4. Koji Jimura
  5. Kiyoshi Nakahara
(2018)
Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance
eLife 7:e32696.
https://doi.org/10.7554/eLife.32696

Share this article

https://doi.org/10.7554/eLife.32696

Further reading

    1. Neuroscience
    Songyao Zhang, Tuo Zhang ... Tianming Liu
    Research Article

    Cortical folding is an important feature of primate brains that plays a crucial role in various cognitive and behavioral processes. Extensive research has revealed both similarities and differences in folding morphology and brain function among primates including macaque and human. The folding morphology is the basis of brain function, making cross-species studies on folding morphology important for understanding brain function and species evolution. However, prior studies on cross-species folding morphology mainly focused on partial regions of the cortex instead of the entire brain. Previously, our research defined a whole-brain landmark based on folding morphology: the gyral peak. It was found to exist stably across individuals and ages in both human and macaque brains. Shared and unique gyral peaks in human and macaque are identified in this study, and their similarities and differences in spatial distribution, anatomical morphology, and functional connectivity were also dicussed.

    1. Neuroscience
    Avani Koparkar, Timothy L Warren ... Lena Veit
    Research Article

    Complex skills like speech and dance are composed of ordered sequences of simpler elements, but the neuronal basis for the syntactic ordering of actions is poorly understood. Birdsong is a learned vocal behavior composed of syntactically ordered syllables, controlled in part by the songbird premotor nucleus HVC (proper name). Here, we test whether one of HVC’s recurrent inputs, mMAN (medial magnocellular nucleus of the anterior nidopallium), contributes to sequencing in adult male Bengalese finches (Lonchura striata domestica). Bengalese finch song includes several patterns: (1) chunks, comprising stereotyped syllable sequences; (2) branch points, where a given syllable can be followed probabilistically by multiple syllables; and (3) repeat phrases, where individual syllables are repeated variable numbers of times. We found that following bilateral lesions of mMAN, acoustic structure of syllables remained largely intact, but sequencing became more variable, as evidenced by ‘breaks’ in previously stereotyped chunks, increased uncertainty at branch points, and increased variability in repeat numbers. Our results show that mMAN contributes to the variable sequencing of vocal elements in Bengalese finch song and demonstrate the influence of recurrent projections to HVC. Furthermore, they highlight the utility of species with complex syntax in investigating neuronal control of ordered sequences.