Detection of dynamic brain networks modulated by acupuncture using a graph theory model |
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Authors: | Lijun Bai Wei Qin Jie Tian Jianping Dai Wanhai Yang |
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Affiliation: | 1. Life Science Research Center, School of Electronic Engineering, Xidian University, Xi'an 710071, China 2. Life Science Research Center, School of Electronic Engineering, Xidian University, Xi'an 710071, China;Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China 3. Department of Radiology, Beijing Tiantan Hospital, Capital University of Medical Sciences, Beijing 100050, China |
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Abstract: | Neuroimaging studies involving acute acupuncture manipulation have already demonstrated significant modulatory effects on wide limbic/paralimbic nuclei, subcortical gray structures and the neocortical system of the brain. Due to the sustained effect of acupuncture, however, knowledge on the organization of such large-scale cortical networks behind the active needle stimulation phase is lacking. In this study, we originally adopted a network model analysis from graph theory to evaluate the functional connectivity among multiple brain regions during the post-stimulus phase. Evidence from our findings clearly supported the existence of a large organized functional connectivity network related to acupuncture function in the resting brain. More importantly, acupuncture can change such a network into a functional state underlying both pain perception and modulation, which is exhibited by significant changes in the functional connectivity of some brain regions. This analysis may help us to better understand the long-lasting effects of acupuncture on brain function, as well as the potential benefits of clinical treatments. |
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Keywords: | Acupuncture Brain network Graph theory model Functional magnetic resonance imaging (fMRI) |
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