Resting state EEG network modularity predicts literacy skills in L1 Chinese but not in L2 English

Kelvin Fai Hong LUI, Jason Chor Ming LO, Connie Suk Han HO, Catherine MCBRIDE, Urs MAURER*

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

6 Citations (Scopus)


EEG network modularity, as a proxy for cognitive plasticity, has been proposed to be a more reliable neural marker than power and coherence in predicting learning outcomes. The present study examined the associations between resting state EEG network modularity and both L1 Chinese and L2 English literacy skills among 90 Hong Kong first to fifth graders. The modularity indices of different frequency bands were highly correlated with one another. An exploratory factor analysis, performed to extract a general modularity index, explained 77.1% of the total variance. The modularity index was positively associated with Chinese word reading, Chinese phonological awareness, Chinese morphological awareness, and Chinese reading comprehension but was not significantly correlated with English word reading or English morphological awareness. Findings suggest that resting state EEG network modularity is likely to serve as a reasonable, reliable, and cost-effective neural marker of the development of first language but not second language literacy skills.

Original languageEnglish
Article number104984
Number of pages11
JournalBrain and Language
Early online date25 Jun 2021
Publication statusPublished - Sept 2021
Externally publishedYes

Bibliographical note

Funding Information: This research was funded by the Collaborative Research Fund from the Hong Kong Special Administrative Region Research Grants Council (CUHK8/CRF/13G, and C4054-17WF) and the BRAIN grant from the Lui Che Woo Institute of Innovative Medicine (8303402) awarded to C. McBride.

Copyright © 2021. Published by Elsevier Inc.


  • EEG
  • Language development
  • Literacy skills
  • Modularity
  • Reading
  • Resting state


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