Sequence structure organizes items in varied latent states of working memory neural network

  1. Qiaoli Huang
  2. Huihui Zhang
  3. Huan Luo  Is a corresponding author
  1. Peking University, China

Abstract

In memory experiences, events do not exist independently but are linked with each other via structure-based organization. Structure context largely influences memory behavior, but how it is implemented in the brain remains unknown. Here, we combined magnetoencephalogram (MEG) recordings, computational modeling, and impulse-response approaches to probe the latent states when subjects held a list of items in working memory (WM). We demonstrate that sequence context reorganizes WM items into distinct latent states, i.e., being reactivated at different latencies during WM retention, and the reactivation profiles further correlate with recency behavior. In contrast, memorizing the same list of items without sequence task requirements weakens the recency effect and elicits comparable neural reactivations. Computational modeling further reveals a dominant function of sequence context, instead of passive memory decaying, in characterizing recency effect. Taken together, sequence structure context shapes the way WM items are stored in the human brain and essentially influences memory behavior.

Data availability

Source data files have been provided here: https://osf.io/f2wnu/

Article and author information

Author details

  1. Qiaoli Huang

    School of Psychological and Cognitive Sciences, Peking University, Beijing, China
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4592-9270
  2. Huihui Zhang

    School of Psychological and Cognitive Sciences, Peking University, Beijing, China
    Competing interests
    No competing interests declared.
  3. Huan Luo

    School of Psychological and Cognitive Sciences, Peking University, Beijing, China
    For correspondence
    huan.luo@pku.edu.cn
    Competing interests
    Huan Luo, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8349-9796

Funding

National Natural Science Foundation of China (31930052)

  • Huan Luo

Beijing Municipal Science and Technology Commission (Z181100001518002)

  • Huan Luo

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

Reviewing Editor

  1. Ole Jensen, University of Birmingham, United Kingdom

Ethics

Human subjects: All experiments were carried out in accordance with the Declaration of Helsinki. All participants provided written informed consent prior to the start of the experiment, which was approved by the Research Ethics Committee at Peking University (2019-02-05).

Version history

  1. Preprint posted: June 20, 2020 (view preprint)
  2. Received: February 16, 2021
  3. Accepted: July 25, 2021
  4. Accepted Manuscript published: July 26, 2021 (version 1)
  5. Version of Record published: August 2, 2021 (version 2)

Copyright

© 2021, Huang 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. Qiaoli Huang
  2. Huihui Zhang
  3. Huan Luo
(2021)
Sequence structure organizes items in varied latent states of working memory neural network
eLife 10:e67589.
https://doi.org/10.7554/eLife.67589

Share this article

https://doi.org/10.7554/eLife.67589

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