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