Emotional learning retroactively promotes memory integration through rapid neural reactivation and reorganization

  1. Yannan Zhu  Is a corresponding author
  2. Yimeng Zeng
  3. Jingyuan Ren
  4. Lingke Zhang
  5. Changming Chen
  6. Guillén Fernández
  7. Shaozheng Qin  Is a corresponding author
  1. Radboud University Nijmegen Medical Centre, Netherlands
  2. Beijing Normal University, China
  3. Xinyang Normal University, China

Abstract

Neutral events preceding emotional experiences can be better remembered, likely by assigning them as significant to guide possible use in future. Yet, the neurobiological mechanisms of how emotional learning enhances memory for past mundane events remain unclear. By two behavioral studies and one functional magnetic resonance imaging study with an adapted sensory preconditioning paradigm, we show rapid neural reactivation and connectivity changes underlying emotion-charged retroactive memory enhancement. Behaviorally, emotional learning enhanced initial memory for neutral associations across the three studies. Neurally, emotional learning potentiated trial-specific reactivation of overlapping neural traces in the hippocampus and stimulus-relevant neocortex. It further induced rapid hippocampal-neocortical functional reorganization supporting such retroactive memory benefit, as characterized by enhanced hippocampal-neocortical coupling modulated by the amygdala during emotional learning, and a shift of hippocampal connectivity from stimulus-relevant neocortex to transmodal prefrontal-parietal areas at post-learning rests. Together, emotional learning retroactively promotes memory integration for past neutral events through stimulating trial-specific reactivation of overlapping representations and reorganization of associated memories into an integrated network to foster its priority for future use.

Data availability

All fMRI data collected in this study are available on OpenNeuro under the accession number ds004109 (https://openneuro.org/datasets/ds004109/versions/1.0.0).All code used for analysis are available on GitHub (https://github.com/QinBrainLab/2017_EmotionLearning.git).

Article and author information

Author details

  1. Yannan Zhu

    Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
    For correspondence
    yan-nan.zhu@donders.ru.nl
    Competing interests
    The authors declare that no competing interests exist.
  2. Yimeng Zeng

    State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Jingyuan Ren

    Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  4. Lingke Zhang

    State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Changming Chen

    Department of Psychology, Xinyang Normal University, Xinyang, China
    Competing interests
    The authors declare that no competing interests exist.
  6. Guillén Fernández

    Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  7. Shaozheng Qin

    State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
    For correspondence
    szqin@bnu.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1859-2150

Funding

National Natural Science Foundation of China (32130045)

  • Shaozheng Qin

National Natural Science Foundation of China (31522028)

  • Shaozheng Qin

National Natural Science Foundation of China (81571056)

  • Shaozheng Qin

Open Research Fund of the State Key Laboratory of Cognitive Neuroscience and Learning (CNLZD1503)

  • Shaozheng Qin

Chinese Scholarship Council (201806040186)

  • Yannan Zhu

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

Ethics

Human subjects: Informed written consent was obtained from each participant before the experiment. The Institutional Review Board for Human Subjects at Beijing Normal University (ICBIR_A_0098_002), Xinyang Normal University (same as above) and Peking University (IRB#2015-09-04) approved the procedures for Study 1, 2 and 3 respectively.

Reviewing Editor

  1. Thorsten Kahnt, National Institute on Drug Abuse Intramural Research Program, United States

Version history

  1. Received: June 18, 2020
  2. Preprint posted: September 9, 2020 (view preprint)
  3. Accepted: December 6, 2022
  4. Accepted Manuscript published: December 8, 2022 (version 1)
  5. Accepted Manuscript updated: December 9, 2022 (version 2)
  6. Version of Record published: January 5, 2023 (version 3)

Copyright

© 2022, Zhu 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. Yannan Zhu
  2. Yimeng Zeng
  3. Jingyuan Ren
  4. Lingke Zhang
  5. Changming Chen
  6. Guillén Fernández
  7. Shaozheng Qin
(2022)
Emotional learning retroactively promotes memory integration through rapid neural reactivation and reorganization
eLife 11:e60190.
https://doi.org/10.7554/eLife.60190

Share this article

https://doi.org/10.7554/eLife.60190

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