Acupuncture has been used to treat various disorders in China and some other eastern countries for thousands of years. Nowadays, acupuncture is gradually accepted as an alternative and complementary method in western countries for its undeniable therapeutic effects. However, its central mechanism is still unclear. It is especially difficult to reveal how different regions in the brain influence one another and how the relationship is among these regions responding to acupuncture treatment. Recently, by applying neuroimaging techniques and network theory, acupuncture studies can make further efforts to investigate the influence of acupuncture on regional cerebral functional connectivity (FC) and the modulation on “acupuncture-related” networks. Connectomics appears to be a new direction in research to further understand the central mechanism underlying acupuncture. In this paper, an overview of connectomics application in acupuncture research will be discussed, with special emphasis on present findings of acupuncture and its influence on cerebral FC. Firstly, the connectomics concept and its significance on acupuncture will be outlined. Secondly, the commonly used brain imaging techniques will be briefly introduced. Thirdly, the influence of acupuncture on FC will be discussed in greater detail. Finally, the possible direction in forthcoming research will be reviewed by analyzing the limitation of present studies. 1. Introduction As one of the major medical resources, acupuncture has been widely used to treat various diseases in China and some other eastern countries for thousands of years. As an alternative and complementary method, acupuncture is gradually accepted in western countries for its undeniable therapeutic effects especially in analgesia [1–5]. Exploring the mechanism of acupuncture has been an active area in alternative and complementary medicine. Since the 1970s, several studies of acupuncture on experimental animals have proven that the integration of central nervous system (CNS) plays an important role in acupuncture efficacy [6]. With the application of multiple neuroimaging techniques such as Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging (fMRI) in acupuncture research, the understanding of the central mechanism of acupuncture has gradually increased [7, 8]. A number of neuroimaging studies indicated that acupuncture could modulate activity in multiple cortical and subcortical brain areas (i.e., somatosensory, brainstem, limbic, and cerebellum) [9]. This included endogenous antinociceptive limbic networks,
References
[1]
D. Irnich and A. Beyer, “Neurobiological mechanisms of acupuncture analgesia,” Schmerz, vol. 16, no. 2, pp. 93–102, 2002.
[2]
S.-M. Wang, Z. N. Kain, and P. White, “Acupuncture analgesia: I. The scientific basis,” Anesthesia and Analgesia, vol. 106, no. 2, pp. 602–610, 2008.
[3]
A. Otti and M. Noll-Hussong, “Acupuncture-induced pain relief and the human brain's default mode network—an extended view of central effects of acupuncture analgesia,” Forschende Komplement？rmedizin, vol. 19, no. 4, pp. 197–201, 2012.
[4]
Z. Yu, X. Cao, Y. Xia, et al., “Electroacupuncture stimulation at CV12 inhibits gastric motility via TRPV1 receptor,” Evidence-Based Complementary and Alternative Medicine, vol. 2013, Article ID 294789, 6 pages, 2013.
[5]
J. Kerr Grieve, S. Flucker, and J. O'Riordan, “Acupuncture is an effective treatment for pain and other ms symptoms,” Journal of Neurology, Neurosurgery & Psychiatry, vol. 84, article e2, 2013.
[6]
J.-S. Han, “Acupuncture: neuropeptide release produced by electrical stimulation of different frequencies,” Trends in Neurosciences, vol. 26, no. 1, pp. 17–22, 2003.
[7]
B. Liu, J. Chen, J. Wang, et al., “Altered small-world efficiency of brain functional networks in acupuncture at ST36: a functional MRI study,” PLoS ONE, vol. 7, no. 6, Article ID e39342, 2012.
[8]
F. Zeng, X.-G. Liu, Y. Tang, and F.-R. Liang, “Application of PET-CT technique to the research on central mechanism of acupuncture effects,” Zhen Ci Yan Jiu, vol. 33, no. 4, pp. 284–286, 2008.
[9]
R. P. Dhond, N. Kettner, and V. Napadow, “Neuroimaging acupuncture effects in the human brain,” Journal of Alternative and Complementary Medicine, vol. 13, no. 6, pp. 603–616, 2007.
[10]
Y. Zhang, C. B. Glielmi, Y. Jiang, et al., “Simultaneous CBF and BOLD mapping of high frequency acupuncture induced brain activity,” Neuroscience Letters, vol. 530, no. 1, pp. 12–17, 2012.
[11]
Y. Feng, L. Bai, Y. Ren et al., “FMRI connectivity analysis of acupuncture effects on the whole brain network in mild cognitive impairment patients,” Magnetic Resonance Imaging, vol. 30, no. 5, pp. 672–682, 2012.
[12]
Y. Feng, L. Bai, W. Zhang et al., “Investigation of acupoint specificity by multivariate granger causality analysis from functional MRI data,” Journal of Magnetic Resonance Imaging, vol. 34, no. 1, pp. 31–42, 2011.
[13]
O. Sporns, G. Tononi, and R. K？tter, “The human connectome: a structural description of the human brain,” PLoS Computational Biology, vol. 1, no. 4, article e42, 2005.
[14]
H. J. Park and K. Friston, “Structural and functional brain networks: from connections to cognition,” Science, vol. 342, no. 6158, Article ID 1238411, 2013.
[15]
M. P. van den Heuvel and O. Sporns, “Rich-club organization of the human connectome,” Journal of Neuroscience, vol. 31, no. 44, pp. 15775–15786, 2011.
[16]
M. P. van den Heuvel, O. Sporns, G. Collin, et al., “Abnormal rich club organization and functional brain dynamics in schizophrenia,” JAMA Psychiatry, vol. 70, no. 8, pp. 783–792, 2013.
[17]
Y. Jiang, H. Wang, Z. Liu, et al., “Manipulation of and sustained effects on the human brain induced by different modalities of acupuncture: an fMRI study,” PLoS ONE, vol. 8, no. 6, Article ID e66815, 2013.
[18]
L. Bai, J. Tian, C. Zhong et al., “Acupuncture modulates temporal neural responses in wide brain networks: evidence from fMRI study,” Molecular Pain, vol. 6, article 73, 2010.
[19]
T. E. J. Behrens and O. Sporns, “Human connectomics,” Current Opinion in Neurobiology, vol. 22, no. 1, pp. 144–153, 2012.
[20]
P. Hagmann, L. Cammoun, X. Gigandet et al., “MR connectomics: principles and challenges,” Journal of Neuroscience Methods, vol. 194, no. 1, pp. 34–45, 2010.
[21]
A. Villringer, “Understanding functional neuroimaging methods based on neurovascular coupling,” Advances in Experimental Medicine and Biology, vol. 413, pp. 177–193, 1997.
[22]
J. Vrba and S. E. Robinson, “Signal processing in magnetoencephalography,” Methods, vol. 25, no. 2, pp. 249–271, 2001.
[23]
J.-J. Lemaire, G. Cosnard, L. Sakka et al., “White matter anatomy of the human deep brain revisited with high resolution DTI fibre tracking,” Neurochirurgie, vol. 57, no. 2, pp. 52–67, 2011.
[24]
W. Qin, J. Tian, X. Pan, L. Yang, and Z. Zhen, “The correlated network of acupuncture effect: a functional connectivity study,” in Proceedings of the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS '06), pp. 480–483, New York, NY, USA, September 2006.
[25]
K. K. S. Hui, O. Marina, J. D. Claunch et al., “Acupuncture mobilizes the brain's default mode and its anti-correlated network in healthy subjects,” Brain Research, vol. 1287, pp. 84–103, 2009.
[26]
Y. Feng, L. Bai, Y. Ren et al., “Investigation of the large-scale functional brain networks modulated by acupuncture,” Magnetic Resonance Imaging, vol. 29, no. 7, pp. 958–965, 2011.
[27]
Y. You, L. Bai, R. Dai, et al., “Altered hub configurations within default mode network following acupuncture at ST36: a multimodal investigation combining fMRI and MEG,” PLoS ONE, vol. 8, no. 5, Article ID e64509, 2013.
[28]
P. Liu, Y. Zhang, G. Zhou et al., “Partial correlation investigation on the default mode network involved in acupuncture: an fMRI study,” Neuroscience Letters, vol. 462, no. 3, pp. 183–187, 2009.
[29]
J. Fang, X. Wang, H. Liu et al., “The limbic-prefrontal network modulated by electroacupuncture at CV4 and CV12,” Evidence-Based Complementary and Alternative Medicine, vol. 2012, Article ID 515893, 11 pages, 2012.
[30]
Y. Zhang, J. Liang, W. Qin et al., “Comparison of visual cortical activations induced by electro-acupuncture at vision and nonvision-related acupoints,” Neuroscience Letters, vol. 458, no. 1, pp. 6–10, 2009.
[31]
G. Zhang, S. Qu, Y. Zheng, et al., “Key regions of the cerebral network are altered after electroacupuncture at the Baihui (GV20) and Yintang acupuncture points in healthy volunteers: an analysis based on resting fcMRI,” Acupuncture in Medicine, vol. 31, no. 4, pp. 383–388, 2013.
[32]
Y. Ren, L. Bai, Y. Feng, J. Tian, and K. Li, “Investigation of acupoint specificity by functional connectivity analysis based on graph theory,” Neuroscience Letters, vol. 482, no. 2, pp. 95–100, 2010.
[33]
V. Napadow, N. Kettner, J. Liu et al., “Hypothalamus and amygdala response to acupuncture stimuli in carpal tunnel syndrome,” Pain, vol. 130, no. 3, pp. 254–266, 2007.
[34]
S. Chen, L. Bai, M. Xu, et al., “Multivariate granger causality analysis of acupuncture effects in mild cognitive impairment patients: an FMRI study,” Evidence-Based Complementary and Alternative Medicine, vol. 2013, Article ID 127271, 12 pages, 2013.
[35]
H. Chen, J. Dai, X. Zhang, et al., “Hypothalamus-related resting brain network underlying short-term acupuncture treatment in primary hypertension,” Evidence-Based Complementary and Alternative Medicine, vol. 2013, Article ID 808971, 9 pages, 2013.
[36]
Y. Ye, B. Li, and Z. Chen, “Resting state-functional magnetic resonance imaging technology applied to a balancing acupuncture treatment for central mechanisms,” Journal of Clinical Rehabilitative Tissue Engineering Research, vol. 15, no. 48, pp. 8998–9002, 2011.
[37]
Y. Yi, F. Xu, P. Xie et al., “Acupuncturing Taichong point for regulating the brain function of depression patients:resting-state fMRI study,” China Journal of Traditional Chinese Medicine and Pharmacy, vol. 27, no. 2, pp. 369–373, 2012.
[38]
J. Li, J.-C. Dong, J.-J. Yue, and W. Tang, “Effects of acupuncture on default mode network images of chronic sciatica patients in the resting network state,” Chinese Journal of Integrated Traditional and Western Medicine Press, vol. 32, no. 12, pp. 1624–1627, 2012.
[39]
L. Bai, J. Tian, W. Qin, et al., “Exploratory analysis of functional connectivity network in acupuncture study by a graph theory mode,” in Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS '07), pp. 2023–2026, Lyon, France, August 2007.
[40]
W. Qin, J. Tian, L. Bai et al., “FMRI connectivity analysis of acupuncture effects on an amygdala-associated brain network,” Molecular Pain, vol. 4, article 55, 2008.
[41]
R. P. Dhond, C. Yeh, K. Park, N. Kettner, and V. Napadow, “Acupuncture modulates resting state connectivity in default and sensorimotor brain networks,” Pain, vol. 136, no. 3, pp. 407–418, 2008.
[42]
P. Liu, W. Qin, Y. Zhang et al., “Combining spatial and temporal information to explore function-guide action of acupuncture using fMRI,” Journal of Magnetic Resonance Imaging, vol. 30, no. 1, pp. 41–46, 2009.
[43]
B. Liu, X. Liu, J. Chen et al., “Study on the effects of acupuncture at acupoint and non-acupoint on functional connectivity of different brain regions with functional magnetic resonance imaging,” Chinese Acupuncture and Moxibustion, vol. 29, no. 12, pp. 981–985, 2009.
[44]
Y. Long, B. Liu, X. Liu et al., “Resting-state functional MRI evaluation of after-effect of acupuncture at Zusanli point,” Chinese Journal of Medical Imaging Technology, vol. 25, no. 3, pp. 373–376, 2009.
[45]
C. E. Zyloney, K. Jensen, G. Polich et al., “Imaging the functional connectivity of the Periaqueductal Gray during genuine and sham electroacupuncture treatment,” Molecular Pain, vol. 6, article 80, 2010.
[46]
W. Q. Qiu, J. Claunch, J. Kong et al., “The effects of acupuncture on the brain networks for emotion and cognition: an observation of gender differences,” Brain Research, vol. 1362, pp. 56–67, 2010.
[47]
K. K. S. Hui, V. Napadow, J. Liu et al., “Monitoring acupuncture effects on human brain by fMRI,” Journal of Visualized Experiments, no. 38, Article ID e1190, 4 pages, 2010.
[48]
J. Liu, W. Qin, Q. Guo et al., “Divergent neural processes specific to the acute and sustained phases of verum and SHAM acupuncture,” Journal of Magnetic Resonance Imaging, vol. 33, no. 1, pp. 33–40, 2011.
[49]
Y. Feng, L. Bai, W. Zhang et al., “Investigation of acupoint specificity by whole brain functional connectivity analysis from fMRI data,” in Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS '11), pp. 2784–2787, Boston, Mass, USA, September 2011.
[50]
Y. Feng, L. Bai, Y. Ren et al., “Investigation of the large-scale functional brain networks modulated by acupuncture,” Magnetic Resonance Imaging, vol. 29, no. 7, pp. 958–965, 2011.
[51]
Y. Ye, Z. Yang, B. Liu, Z. Chen, and X. Li, “Response of balancing acupuncture by using brain functional magnetic resonance imaging at resting- state,” Journal of Jinan University, vol. 32, no. 4, pp. 419–421, 2011.
[52]
Y. Ye, B. Liu, Z. Chen, J. Chen, X. Liu, and X. Li, “Brain functional connectivity of balancing technique acupuncture on Backleg pain,” Journal of Liaoning University of TCM, vol. 13, no. 9, pp. 174–176, 2011.
[53]
N. Li, P. Wang, B. Deng et al., “Influence of acupuncture of Zusanli (ST 36) on connectivity of brain functional network in healthy subjects,” Acupuncture Research, vol. 36, no. 4, pp. 278–287, 2011.
[54]
J.-L. Fang, Y. Hong, X.-L. Wang et al., “Electroacupuncture at Guanyuan (CV 4) and Zhongwan (CV 12) modulates functional connectivity of the brain network in healthy volunteers,” Acupuncture Research, vol. 36, no. 5, pp. 366–372, 2011.
[55]
C. Zhong, L. Bai, R. Dai et al., “Modulatory effects of acupuncture on resting-state networks: a functional MRI study combining independent component analysis and multivariate granger causality analysis,” Journal of Magnetic Resonance Imaging, vol. 35, no. 3, pp. 572–581, 2012.
[56]
Y. You, L. Bai, R. Dai, C. Zhong, T. Xue, H. Wang, et al., “Acupuncture induces divergent alterations of functional connectivity within conventional frequency bands: evidence from MEG recordings,” PLoS ONE, vol. 7, no. 11, Article ID e49250, 2012.
[57]
Y. Jiang, Y. Hao, Y. Zhang et al., “Thirty minute transcutaneous electric acupoint stimulation modulates resting state brain activities: a perfusion and BOLD fMRI study,” Brain Research, vol. 1457, pp. 13–25, 2012.
[58]
B. Zhao, L. Li, J. Yang, C. Li, C. Xu, and Y. Zhu, “Study on acupuncture effect of Hegu point(LI4)with resting-state fMRI,” Chinese Imaging Journal of Integrated Traditional and Western Medicine, vol. 10, no. 2, pp. 97–100, 2012.
[59]
J. Fang, K. K. Hui, J. Liu, E. E. Nixon, K. Zhou, and X. Wang, “Deqi and Sharp pain during acupuncture at Taichong eliciting the opposite functional brain network effects—an fMRI study,” Chinese Imaging Journal of Integrated Traditional and Western Medicine, vol. 10, no. 1, pp. 4–9, 2012.
[60]
X.-J. Dai, Y.-J. Min, H.-H. Gong et al., “Evaluation of the post-effect of acupuncture at Sanyinjiao (SP 6) under sleep deprivation by resting- state amplitude of low-frequency fluctuation: a fMRI study,” Chinese Acupuncture and Moxibustion, vol. 32, no. 1, pp. 47–52, 2012.
[61]
M. Dong, W. Qin, L. Zhao, X. Yang, K. Yuan, F. Zeng, et al., “Expertise modulates local regional homogeneity of spontaneous brain activity in the resting brain: an fMRI study using the model of skilled acupuncturists,” Human Brain Mapping, 2013.
[62]
S. Chen, M. Xu, X. Peng, J. Huang, W. Yang, Q. Xu, et al., “Study of resting-state fMRI in acupuncture at DU26 point in patients with mild cognitive impairment,” Journal of Yunnan University of Traditional Chinese Medicine, vol. 36, no. 1, pp. 5–7, 2013.
