摘要
Background Previous studies have demonstrated that acupuncture could modulate various brain systems in the resting brain networks. Graph theoretical analysis offers a novel way to investigate the functional organization of the large-scale cortical networks modulated by acupuncture at whole brain level. In this study, we used wavelets correlation analysis to estimate the pairwise correlations between 90 cortical and subcortical human brain regions in normal human volunteers scanned during the post-stimulus resting state. Methods Thirty-two college students, all right-handed and acupuncture na＇fve, participated in this study. Every participant received only one acupoint stimulation, resulting in 16 subjects in one group. Both structural functional magnetic resonance imaging （fMRI） data （3D sequence with a voxel size of 1 mm3 for anatomical localization） and functional fMRI data （TR=1500 ms, TE=30 ms, flip angle=90°） were collected for each subject. After thresholding the resulting scale-specific wavelet correlation matrices to generate undirected binary graphs, we compared graph metrics of brain organization following verum manual acupuncture （ACU） and sham acupuncture （SHAM） groups. Results The topological parameters of the large-scale brain networks in ACU group were different from those of the SHAM group at multiple scales. There existed distinct modularity functional brain networks during the post-stimulus resting state following ACU and SHAM at multiple scales. Conclusions The distinct modulation patterns of the resting brain attributed to the specific effects evoked by acupuncture. In addition, we also identified that there existed frequency-specific modulation in the post-stimulus resting brain following ACU and SHAM. The modulation may be related to the effects of verum acupuncture on modulating special disorder treatment. This preliminary finding may provide a new clue to understand the relatively function- oriented specificity of acupuncture effects.
Background Previous studies have demonstrated that acupuncture could modulate various brain systems in the resting brain networks. Graph theoretical analysis offers a novel way to investigate the functional organization of the large-scale cortical networks modulated by acupuncture at whole brain level. In this study, we used wavelets correlation analysis to estimate the pairwise correlations between 90 cortical and subcortical human brain regions in normal human volunteers scanned during the post-stimulus resting state. Methods Thirty-two college students, all right-handed and acupuncture na＇fve, participated in this study. Every participant received only one acupoint stimulation, resulting in 16 subjects in one group. Both structural functional magnetic resonance imaging （fMRI） data （3D sequence with a voxel size of 1 mm3 for anatomical localization） and functional fMRI data （TR=1500 ms, TE=30 ms, flip angle=90°） were collected for each subject. After thresholding the resulting scale-specific wavelet correlation matrices to generate undirected binary graphs, we compared graph metrics of brain organization following verum manual acupuncture （ACU） and sham acupuncture （SHAM） groups. Results The topological parameters of the large-scale brain networks in ACU group were different from those of the SHAM group at multiple scales. There existed distinct modularity functional brain networks during the post-stimulus resting state following ACU and SHAM at multiple scales. Conclusions The distinct modulation patterns of the resting brain attributed to the specific effects evoked by acupuncture. In addition, we also identified that there existed frequency-specific modulation in the post-stimulus resting brain following ACU and SHAM. The modulation may be related to the effects of verum acupuncture on modulating special disorder treatment. This preliminary finding may provide a new clue to understand the relatively function- oriented specificity of acupuncture effects.
基金
This work was supported by the National Key Basic Research and Development Program ＂973＂ Project （No. 2007CB512503）, the National Natural Science Foundation of China （No. 81071217）, Fundamental Research Funds for the Central University, Beijing Nova Program （No. Zl11101054511116）, and Beijing Natural Science Foundation （No. 4122082）.
