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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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Biography
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Posts
Brain Computer Interface Study Recruitment
Published:
Brain Computer Interface Study Recruitment Advertisement
Common Spatial Pattern
Published:
Introduction of Common Spatial Pattern(CSP) Algorithm
portfolio
Portfolio item number 1
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Portfolio item number 2
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publications
Zero-Shot Learning for EEG Classification in Motor Imagery-Based BCI System
Published in IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2020
A motor imagery-based BCI using zero-shot learning reduces calibration time and achieves 91.81% of traditional method accuracy.
Recommended citation: Duan, L., Li, J., Ji, H., Pang, Z., Zheng, X., Lu, R., Li, M., & Zhuang, J. (2020). Zero-Shot Learning for EEG Classification in Motor Imagery-Based BCI System. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(11), 2411–2419. https://doi.org/10.1109/tnsre.2020.3027004 https://doi.org/10.1109/TNSRE.2020.3027004
Task Transfer Learning for EEG Classification in Motor Imagery‐Based BCI System
Published in Computational and Mathematical Methods in Medicine, 2020
The motor-imagery brain-computer interface (MI-BCI) system improves by using command combinations and transfer learning to reduce calibration time and increase accuracy.
Recommended citation: Zheng, X., Li, J., Ji, H., Duan, L., Li, M., Pang, Z., Zhuang, J., Rongrong, L., & Tianhao, G. (2020). Task Transfer Learning for EEG Classification in Motor Imagery-Based BCI System. Computational and Mathematical Methods in Medicine, 2020, 1–11. https://doi.org/10.1155/2020/6056383 https://doi.org/10.1155/2020/6056383
Psychopy based Continuous Pain Monitoring Task
Published in Zenodo, 2024
This continuous pain rating task assesses pain intensity using the open-source software PsychoPy hosted on Pavlovia.
Recommended citation: Zheng, X., Rajwal, S., Ho, S. Y. S., Ashworth, C., Seymour, B., Shenker, N., & Mancini, F. (2024). Psychopy based Continuous Pain Monitoring Task (1.0.0). Zenodo. https://doi.org/10.5281/zenodo.13754802 https://doi.org/10.5281/zenodo.13754802
Short-term variability of chronic musculoskeletal pain
Published in Frontiers in Pain Research, 2025
Short-term variability in chronic musculoskeletal pain is clinically significant, correlating with pain severity and providing insights for personalized pain management.
Recommended citation: Zheng, X., Rajwal, S., Ashworth, C., Ho, S. Y. S., Seymour, B., Shenker, N., & Mancini, F. (2025). Short-term variability of chronic musculoskeletal pain. Frontiers in Pain Research, 6. https://doi.org/10.3389/fpain.2025.1626589 https://doi.org/10.3389/fpain.2025.1626589
Word selection, concreteness and brain lateralization
Published in Brain and Language, 2025
fMRI evidence reveals distinct neural mechanisms for semantic selection and competition in Mandarin Chinese, dynamically modulated by word concreteness.
Recommended citation: Zhao, J., Zhao, Y., Zheng, X., Wang, X., Ning, Z., Chen, Y., Ji, H., Li, J., & Zhuang, J. (2025). Word selection, concreteness and brain lateralization. Brain and Language, 272, 105659–105659. https://doi.org/10.1016/j.bandl.2025.105659 https://doi.org/10.1016/j.bandl.2025.105659
Towards a Brain-Computer Interface (BCI) for Improving Phonological Processing in Developmental Dyslexia: An Exploratory Study
Published in bioRxiv, 2026
An EEG-based BCI targeting speech-related neural rhythms shows potential for improving phonological processing and reading skills in developmental dyslexia.
Recommended citation: Zheng, X., Araújo, J., Busson, Q., & Goswami, U. (2026). Towards a Brain-Computer Interface (BCI) for Improving Phonological Processing in Developmental Dyslexia: An Exploratory Study. https://doi.org/10.64898/2026.01.23.700941 https://doi.org/10.64898/2026.01.23.700941
Atypical cortical encoding of the low-frequency temporal dynamics of natural speech identifies children with Developmental Language Disorder
Published in bioRxiv, 2026
EEG analyses reveal atypical low-frequency neural dynamics during natural speech processing in children with Developmental Language Disorder (DLD).
Recommended citation: Zheng, X., Araújo, J., Keshavarzi, M., Feltham, G., Richards, S., Parvez, L., & Goswami, U. (2026). Atypical cortical encoding of the low-frequency temporal dynamics of natural speech identifies children with Developmental Language Disorder. https://doi.org/10.64898/2026.03.08.710292 https://doi.org/10.64898/2026.03.08.710292
talks
Towards a Brain-Computer Interface (BCI) for Improving Phonological Processing in Developmental Dyslexia: An Exploratory Study
Published:
Towards a Brain-Computer Interface (BCI) for Improving Phonological Processing in Developmental Dyslexia: An Exploratory Study
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.