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Functional brain networks in healthy subjects under acupuncture stimulation: An EEG study based on nonlinear synchronization likelihood analysis

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  • Yu, Haitao
  • Liu, Jing
  • Cai, Lihui
  • Wang, Jiang
  • Cao, Yibin
  • Hao, Chongqing

Abstract

Electroencephalogram (EEG) signal evoked by acupuncture stimulation at ”Zusanli” acupoint is analyzed to investigate the modulatory effect of manual acupuncture on the functional brain activity. Power spectral density of EEG signal is first calculated based on the autoregressive Burg method. It is shown that the EEG power is significantly increased during and after acupuncture in delta and theta bands, but decreased in alpha band. Furthermore, synchronization likelihood is used to estimate the nonlinear correlation between each pairwise EEG signals. By applying a threshold to resulting synchronization matrices, functional networks for each band are reconstructed and further quantitatively analyzed to study the impact of acupuncture on network structure. Graph theoretical analysis demonstrates that the functional connectivity of the brain undergoes obvious change under different conditions: pre-acupuncture, acupuncture, and post-acupuncture. The minimum path length is largely decreased and the clustering coefficient keeps increasing during and after acupuncture in delta and theta bands. It is indicated that acupuncture can significantly modulate the functional activity of the brain, and facilitate the information transmission within different brain areas. The obtained results may facilitate our understanding of the long-lasting effect of acupuncture on the brain function.

Suggested Citation

  • Yu, Haitao & Liu, Jing & Cai, Lihui & Wang, Jiang & Cao, Yibin & Hao, Chongqing, 2017. "Functional brain networks in healthy subjects under acupuncture stimulation: An EEG study based on nonlinear synchronization likelihood analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 566-577.
    • Handle: RePEc:eee:phsmap:v:468:y:2017:i:c:p:566-577
    DOI: 10.1016/j.physa.2016.10.068
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    References listed on IDEAS

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    1. Wenjing Huang & Daniel Pach & Vitaly Napadow & Kyungmo Park & Xiangyu Long & Jane Neumann & Yumi Maeda & Till Nierhaus & Fanrong Liang & Claudia M Witt, 2012. "Characterizing Acupuncture Stimuli Using Brain Imaging with fMRI - A Systematic Review and Meta-Analysis of the Literature," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-1, April.
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    Cited by:

    1. Filho, F.M. Oliveira & Ribeiro, F.F. & Cruz, J.A. Leyva & de Castro, A.P. Nunes & Zebende, G.F., 2023. "Statistical study of the EEG in motor tasks (real and imaginary)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).
    2. Lahmiri, Salim, 2018. "Causal influences between spontaneous fluctuations in resting state fMRI of central and peripheral eccentricity representations in the human visual cortex," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 756-762.

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