Brain Functional Network Analysis Of Acupuncture Effects At Acupoint ST36

Acupuncture originated in China, with clinics of history for thousands of years. In the past 30 years, the influence of acupuncture in the West was increasing, but it was thought to be a supporting health care. The reason is that the mechanism of acupuncture is still unclear. As we know, fMRI is a non-invasive imaging technique, it offeres us a new way to study the acupuncture theory. The related research by using the fMRI is based on the analysis of the experimental data. This needs to select the appropriate data analysis tools, optimize and organize the data based on the experimental design. According to that we can get the statistical information which would be used to inference the results.The main software which are often used to process the fMRI data include REST,SPM and DPARSF. And the experimental design model of the"ON-OFF"is widely used in the data analyzing of the fMRI. In this experimental design model, the stimulation state (ON) and resting state (OFF) alternately presented several times. And this experimental design model has a underlying assumption, that is the activation of the brain stimulated by acupuncture will return to the baseline when the "ON" phase is over, and will not affect the brain signals at the "OFF" phase. Undoubtedly, experimental data must meet this assumption. However , in recent years, numerous studies show that the effect of the acupuncture can sustain for a period of time even the twisted had finished for a long time, namely the acupuncture has the property of sustain. And , our research group provided some direct evidence for existence of the sustained central effect of acupuncture, and pointed out that due to the influence of the sustained effect of acupuncture, acupuncture response model can not meet the "ON-OFF" assumption.Taking the above factors into account, we use a new function to process the fMRI data—an method based on graph theory model. That is , complex network analysis (Graph Theory Model, GTA). This method not only can depict the relationship of the system and the subsystem, but also can describe the changing of the whole system. We applied the approach to analyze the data of the acupuncture group and the control group. By comparing the network statistics in the two sets, we find out that the network topologies in these two groups are significantly different. Further, from the point of view of the network's functional connectivity, we analyzed the network matrix, and find out three different functional connectivity network: the functional connectivity existed in both of the two sets, the functional connectivity existed only in the acupuncture group and in the control group respectively. Thus, we find out the hubs among these three different networks are different. This discover not only provide strong evidence that the acupuncture can adjust the connection mode of brain functional connectivity, but also offer some reference for using the GTA method to process the fMRI data.