Low-frequency neural activity reflects rule-based chunking during speech listening

  1. Peiqing Jin
  2. Yuhan Lu
  3. Nai Ding  Is a corresponding author
  1. Zhejiang University, China

Abstract

Chunking is a key mechanism for sequence processing. Studies on speech sequences have suggested low-frequency cortical activity tracks spoken phrases, i.e., chunks of words defined by tacit linguistic knowledge. Here we investigate whether low-frequency cortical activity reflects a general mechanism for sequence chunking and can track chunks defined by temporarily learned artificial rules. The experiment records magnetoencephalographic (MEG) responses to a sequence of spoken words. To dissociate word properties from the chunk structures, two tasks separately require listeners to group pairs of semantically similar or semantically dissimilar words into chunks. In the MEG spectrum, a clear response is observed at the chunk rate. More importantly, the chunk-rate response is task-dependent. It is phase locked to chunk boundaries, instead of the semantic relatedness between words. The results strongly suggest that cortical activity can track chunks constructed based on task-related rules and potentially reflects a general mechanism for chunk-level representations.

Data availability

The MEG data and analysis code (in MatLab) were uploaded as Source data files.

Article and author information

Author details

  1. Peiqing Jin

    Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou, China 310027, Zhejiang University, Hangzhou, China
    Competing interests
    The authors declare that no competing interests exist.
  2. Yuhan Lu

    Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou, China 310027, Zhejiang University, Hangzhou, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Nai Ding

    Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou, China 310027, Zhejiang University, Hangzhou, China
    For correspondence
    ding_nai@zju.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3428-2723

Funding

National Natural Science Foundation of China (31771248)

  • Nai Ding

Major Scientific Research Project of Zhejiang Lab (2019KB0AC02)

  • Nai Ding

Fundamental Research Funds for the Central Universities

  • Nai Ding

Zhejiang Provincial Natural Science Foundation of China (LY20C090008)

  • Peiqing Jin

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

Ethics

Human subjects: The experimental procedures were approved by the Research Ethics Committee of the College of Medicine, Zhejiang University (2019-047) and the Research Ethics Committee of Peking University (2019-02-05). The participants provided written consent and were paid.

Copyright

© 2020, Jin 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. Peiqing Jin
  2. Yuhan Lu
  3. Nai Ding
(2020)
Low-frequency neural activity reflects rule-based chunking during speech listening
eLife 9:e55613.
https://doi.org/10.7554/eLife.55613

Share this article

https://doi.org/10.7554/eLife.55613

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