• Mol Pain · Mar 2011

    The temporal-spatial encoding of acupuncture effects in the brain.

    • Wei Qin, Lijun Bai, Jianping Dai, Peng Liu, Minghao Dong, Jixin Liu, Jinbo Sun, Kai Yuan, Peng Chen, Baixiao Zhao, Qiyong Gong, Jie Tian, and Yijun Liu.
    • Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
    • Mol Pain. 2011 Mar 23; 7: 19.

    BackgroundFunctional acupoint specificity is crucial to the clinical efficacy of acupuncture treatment, such as pain relief. Whether acupuncture needling at a peripheral acupoint produces distinct patterns of brain responses remains controversial.ResultsThis fMRI study employed the complex network analysis (CNA) to test the hypothesis that acupuncture stimulation at an acupoint correspondingly induced activity changes in one or more intrinsic or resting-state brain networks. Built upon the sustained effect of acupuncture and its time-varying characteristics, we constructed a dynamic encoding system with the hub anchored at the posterior cingulate cortex and precuneus (PCC/pC). We found that needling at two visual acupoints (GB37 and BL60) and a non-visual acupoint (KI8) induced a spatially converging brain response, which overlapped at the PCC/pC. We also found distinct neural modulations during and after acupoint stimulation. During this period, the PCC/pC interacted with a visual resting-state network in different patterns. Furthermore, there was a delayed functional correspondence between the intrinsic visual network and manipulation over the visual acupoints (i.e., GB37 or BL60), but not the non-visual acupoint (KI8) via the PCC/pC, implicating a specific temporal-spatial encoding/decoding mechanism underlying the post-effect of acupuncture.ConclusionsThis study provided an integrated view exploring the functional specificity of acupuncture in which both the needling sensation and the following neural cascades may contribute to the overall effect of acupuncture through dynamic reconfiguration of complex neural networks.fMRI, acupoints, posterior cingulate cortex, precuneus, temporal-spatial encoding, resting-state networks.

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