Effects of Computerized Working-Memory Training with EEG-Based Assessment—

Chia Yen Yang*, Hsin Yung Chen

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

1 Scopus citations

Abstract

Purpose: Because training appears to affect working memory, early evaluation and training may help to improve working memory capacity. The aim of this study was to develop a computerized platform that employs electroencephalography (EEG) to investigate the effects of working-memory training. Methods: The platform included two systems: (i) in the assessment system we designed n-back paradigms and estimated synchronization index between the theta and gamma bands with working memory index (WMI) verification, while (ii) in the improvement system we designed working-memory training tasks based on three categories—a numerical version of a complex-span task, a figure-based version of a task-switching task, and a matrix version of a pattern task. Twenty-eight healthy volunteers were randomly assigned to the passive control and experimental groups. Results: Significant correlations between WMI and level of difficulty were found for the numerical complex-span task and the pattern-integration task which suggested that training can improve working memory performance. Furthermore, the EEG coupling analysis revealed significantly different in the theta-band phase and high-gamma-band power (i.e., 70–90 Hz) at FC1 which could be used to uncover relationships with the working memory. Conclusion: The system estimating the brainwave responses provided a complementary way of quantifying the degree of working memory other than using a psychophysical questionnaire. Furthermore, it could be simply and rapidly modified for implementing different training tasks, with features of flexibility, low cost, and minimal development time.

Original languageEnglish
Pages (from-to)216-223
Number of pages8
JournalJournal of Medical and Biological Engineering
Volume41
Issue number2
DOIs
StatePublished - 04 2021

Bibliographical note

Publisher Copyright:
© 2021, Taiwanese Society of Biomedical Engineering.

Keywords

  • Cross-frequency coupling
  • EEG
  • Training
  • Working-memory
  • n-back

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