Relationship between the Long-Term Practice of Tai Chi Stance with Neural Patterns of the Brain: An Exploratory Study

Research has shown that practicing Tai Chi can alleviate brain tension and enhance the activity of the autonomic nervous system in the human body. However, there is limited research on the effects of Tai Chi Stance on brain function. This study aims to analyze the electroencephalogram (EEG) characteristics of long-term Tai Chi Zhuang practitioners and investigate the changes in brain dynamic neural patterns during different stages of Tai Chi Stance, together with the differences between long-term practitioners and a control group. In this study, we first analyzed the changes in EEG spectral characteristics during different stages of Tai Chi Stance practice of long-term practitioners. We found that the alpha (8–13 Hz) power significantly increased during the stance, indicating a state of deep relaxation during the Tai Chi practice. The experimental group also exhibited significant changes in brain functional network parameters in the alpha band during the stance, including increased clustering coefficient and global efficiency. Finally, inter-group differences in EEG characteristic parameters were analyzed between the experimental group and control group. The results showed significant differences in relative power and functional connectivity in the alpha band between the two groups, indicating that long-term Tai Chi Stance practice can effectively enhance brain network efficiency and improve information integration capabilities. This study provides scientific evidence for Tai Chi Stance training to enhance brain health.

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Published
2024-11-01
DOI
https://doi.org/10.1109/cac63892.2024.10865729
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
0.00

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article

Relationship between the Long-Term Practice of Tai Chi Stance with Neural Patterns of the Brain: An Exploratory Study

Peifen Zhang, Mengmeng Li, Hong Wan
Stroke Rehabilitation and Recovery
article

Relationship between the Long-Term Practice of Tai Chi Stance with Neural Patterns of the Brain: An Exploratory Study

Peifen Zhang, Mengmeng Li, Hong Wan
article en

Abstract

Research has shown that practicing Tai Chi can alleviate brain tension and enhance the activity of the autonomic nervous system in the human body. However, there is limited research on the effects of Tai Chi Stance on brain function. This study aims to analyze the electroencephalogram (EEG) characteristics of long-term Tai Chi Zhuang practitioners and investigate the changes in brain dynamic neural patterns during different stages of Tai Chi Stance, together with the differences between long-term practitioners and a control group. In this study, we first analyzed the changes in EEG spectral characteristics during different stages of Tai Chi Stance practice of long-term practitioners. We found that the alpha (8–13 Hz) power significantly increased during the stance, indicating a state of deep relaxation during the Tai Chi practice. The experimental group also exhibited significant changes in brain functional network parameters in the alpha band during the stance, including increased clustering coefficient and global efficiency. Finally, inter-group differences in EEG characteristic parameters were analyzed between the experimental group and control group. The results showed significant differences in relative power and functional connectivity in the alpha band between the two groups, indicating that long-term Tai Chi Stance practice can effectively enhance brain network efficiency and improve information integration capabilities. This study provides scientific evidence for Tai Chi Stance training to enhance brain health.

Zhengzhou University (CN)
National Natural Science Foundation of China
Reduced inequalities
Openalex Percentile: Top 68%
Stroke Rehabilitation and Recovery
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Relationship between the Long-Term Practice of Tai Chi Stance with Neural Patterns of the Brain: An Exploratory Study — Peifen Zhang, Mengmeng Li, et al. · (2024) | TGRS Research Map | TGRS