Modulation of Spectral Power and Functional Connectivity in Human Brain by Acupuncture Stimulation

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 26; no. 5; pp. 977 - 986
• Main Authors: Yu, Haitao, Wu, Xinyu, Cai, Lihui, Deng, Bin, Wang, Jiang
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.05.2018
• Subjects: Acupuncture; Brain; Electroencephalography; Functional magnetic resonance imaging; Indexes; Needles; small-world connectivity; spectral power; Synchronization
• ISSN: 1534-4320; 1558-0210; 1558-0210
• DOI: 10.1109/TNSRE.2018.2828143

Acupuncture, as an external stimulation, can produce clinical effects via the central nervous system. In order to investigate the modulatory efficacy of acupuncture on brain activity, multichannel EEG signals evoked by acupuncture at "Zusanli" acupoint were recorded from healthy humans in three states: pre-acupuncture, acupuncture, and post-acupuncture. Power spectral density is first used to analyze the EEG power change during acupuncture process. It is found that EEG power significantly increased in the delta and alpha bands under acupuncture and high power level remained in alpha band after acupuncture. Then, we calculated phase lag index to quantify the phase synchronization of pair-wise channels. In acupuncture state, delta and alpha bands exhibit significantly higher synchronization degree than pre-acupuncture state. Additionally, post-effect of acupuncture can be observed in alpha band as high synchronization degree remains in post-acupuncture state. Moreover, functional brain networks converted from synchronization matrix in each band are reconstructed. Acupuncture increases long-range connections between left and right hemispheres and changes the position of main nodes. Graph theory metrics are extracted to explore the change of functional connectivity in different states. The result shows the functional networks in delta and alpha bands are small world networks (SWN) and acupuncture improves the SWN efficiency of functional network.