Somatosensory Stimulation With XNKQ Acupuncture Modulates Functional Connectivity of Motor Areas

Till Nierhaus, Yinghui Chang, Bin Liu, Xuemin Shi, Ming Yi, Claudia M Witt, Daniel Pach, Till Nierhaus, Yinghui Chang, Bin Liu, Xuemin Shi, Ming Yi, Claudia M Witt, Daniel Pach

Abstract

Xingnao Kaiqiao (XNKQ) acupuncture is an acupuncture technique used for stroke patients. In 24 healthy volunteers, we applied this complex acupuncture intervention, which consists of a manual needle-stimulation on five acupuncture points (DU26 unilaterally, PC6, and SP6 bilaterally). XNKQ was compared to three control conditions: (1) insertion of needles on the XNKQ acupuncture points without stimulation, (2) manual needle-stimulation on five nearby non-acupuncture points, and (3) insertion of needles on the non-acupuncture points without stimulation. In a within-subject design, we investigated functional connectivity changes in resting-state functional magnetic resonance imaging (fMRI) by means of the data-driven eigenvector centrality (EC) approach. With a 2 × 2 factorial within-subjects design with two-factor stimulation (stimulation vs. non-stimulation) and location (acupuncture points vs. non-acupuncture points), we found decreased EC in the precuneus after needle-stimulation (stimulation<non-stimulation), whereas the factor location showed no statistically significant EC differences. XNKQ acupuncture compared with needle-stimulation on non-acupuncture points showed decreased EC primarily in subcortical structures such as the caudate nucleus, subthalamic nucleus, and red nucleus. Post-hoc seed-based analysis revealed that the decrease in EC was mainly driven by reduced temporal correlation to primary sensorimotor cortices. The comparison of XNKQ acupuncture with the other two (non-stimulation) interventions showed no significant differences in EC. Our findings support the importance of the stimulation component of the acupuncture intervention and hint toward the modulation of functional connectivity by XNKQ acupuncture, especially in areas involved in motor function. As a next step, similar mechanisms should be validated in stroke patients suffering from motor deficits. ClinicalTrials.gov ID: NCT02453906.

Keywords: acupuncture; centrality; functional connectivity; precuneus; red nucleus; resting-state fMRI; stroke.

Figures

Figure 1
Figure 1
Acupuncture points and respective control points.
Figure 2
Figure 2
Comparison of ECM values for the factor “stimulation.” Whole brain analysis for the contrast [stimulation vs. non-stimulation] shows decreased centrality for the stimulation conditions. Monte Carlo simulation with AlphaSim was used to identify significant clusters at pFWE X = −5, Y = −78, Z = 42. LH, left hemisphere.
Figure 3
Figure 3
Comparison of the two stimulation conditions. Effect on functional connectivity for the contrast [XNKQ vs. “non-acupuncture point with stimulation” (npws)]. (A) Data-driven ECM analysis shows decreased centrality for XNKQ, mainly in subcortical regions. Monte Carlo simulation with AlphaSim was used to identify significant clusters at pFWE < 0.05 (family-wise error (FWE) correction for multiple comparisons). Red circle (Red Nucleus) and yellow circle (Subthalamic Nucleus) indicate areas that were used for seed-based correlation analyses. MNI slice coordinates X = 8, Y = 22, Z = 18. (B) Seed-based functional connectivity with seed in Red Nucleus. Whole brain analysis shows for XNKQ decreased temporal correlation of the seed-region (red) with primary sensorimotor areas (voxel-wise FWE correction at pFWE < 0.05). MNI slice coordinates X = 41, Y = 22, Z = 51. (C) Seed-based functional connectivity with seed in Subthalamic Nucleus. Whole brain analysis shows for XNKQ decreased temporal correlation of the seed-region (yellow) with left primary sensorimotor areas (voxel-wise FWE correction at pFWE < 0.05). MNI slice coordinates X = 40, Y = 20, Z = 48. LH, left hemisphere.

References

    1. Almeida S. R., Vicentini J., Bonilha L., De Campos B. M., Casseb R. F., Min L. L. (2017). Brain connectivity and functional recovery in patients with ischemic stroke. J. Neuroimaging 27, 65–70. 10.1111/jon.12362
    1. Antonenko D., Nierhaus T., Meinzer M., Prehn K., Thielscher A., Ittermann B., et al. . (2018). Age-dependent effects of brain stimulation on network centrality. Neuroimage 176, 71–82. 10.1016/j.neuroimage.2018.04.038
    1. Bai L., Qin W., Tian J., Dong M., Pan X., Chen P., et al. . (2009). Acupuncture modulates spontaneous activities in the anticorrelated resting brain networks. Brain Res. 1279, 37–49. 10.1016/j.brainres.2009.04.056
    1. Baldassarre A., Ramsey L. E., Siegel J. S., Shulman G. L., Corbetta M. (2016). Brain connectivity and neurological disorders after stroke. Curr. Opin. Neurol. 29, 706–713. 10.1097/WCO.0000000000000396
    1. Behzadi Y., Restom K., Liau J., Liu T. T. (2007). A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage 37, 90–101. 10.1016/j.neuroimage.2007.04.042
    1. Buckner R. L., Sepulcre J., Talukdar T., Krienen F. M., Liu H., Hedden T., et al. . (2009). Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer's disease. J. Neurosci. 29, 1860–1873. 10.1523/JNEUROSCI.5062-08.2009
    1. Chae Y., Chang D. S., Lee S. H., Jung W. M., Lee I. S., Jackson S., et al. . (2013). Inserting needles into the body: a meta-analysis of brain activity associated with acupuncture needle stimulation. J. Pain 14, 215–222. 10.1016/j.jpain.2012.11.011
    1. Choi E. M., Jiang F., Longhurst J. C. (2012). Point specificity in acupuncture. Chin. Med. 7:4. 10.1186/1749-8546-7-4
    1. Deng D., Liao H., Duan G., Liu Y., He Q., Liu H., et al. . (2016). Modulation of the default mode network in first-episode, drug-naive major depressive disorder via acupuncture at Baihui (GV20) acupoint. Front. Hum. Neurosci. 10:230. 10.3389/fnhum.2016.00230
    1. Dhond R. P., Kettner N., Napadow V. (2007). Neuroimaging acupuncture effects in the human brain. J. Altern Complement. Med. 13, 603–616. 10.1089/acm.2007.7040
    1. Dhond R. P., Yeh C., Park K., Kettner N., Napadow V. (2008). Acupuncture modulates resting state connectivity in default and sensorimotor brain networks. Pain 136, 407–418. 10.1016/j.pain.2008.01.011
    1. Fransson P., Aden U., Blennow M., Lagercrantz H. (2011). The functional architecture of the infant brain as revealed by resting-state fMRI. Cereb. Cortex 21, 145–154. 10.1093/cercor/bhq071
    1. Gläscher J., Gitelman D. (2008). Contrast Weights in Flexible Factorial Design With Multiple Groups of Subjects. Available online at: (Accessed March 23, 2016).
    1. Goffaux P., Girard-Tremblay L., Marchand S., Daigle K., Whittingstall K. (2014). Individual differences in pain sensitivity vary as a function of precuneus reactivity. Brain Topogr. 27, 366–374. 10.1007/s10548-013-0291-0
    1. Grefkes C., Fink G. R. (2011). Reorganization of cerebral networks after stroke: new insights from neuroimaging with connectivity approaches. Brain 134, 1264–1276. 10.1093/brain/awr033
    1. Hakon J., Quattromani M. J., Sjolund C., Tomasevic G., Carey L., Lee J. M., et al. . (2018). Multisensory stimulation improves functional recovery and resting-state functional connectivity in the mouse brain after stroke. Neuroimage Clin. 17, 717–730. 10.1016/j.nicl.2017.11.022
    1. Hsieh J. C., Tu C. H., Chen F. P., Chen M. C., Yeh T. C., Cheng H. C., et al. . (2001). Activation of the hypothalamus characterizes the acupuncture stimulation at the analgesic point in human: a positron emission tomography study. Neurosci. Lett. 307, 105–108. 10.1016/S0304-3940(01)01952-8
    1. Huang W., Pach D., Napadow V., Park K., Long X., Neumann J., et al. . (2012). Characterizing acupuncture stimuli using brain imaging with FMRI–a systematic review and meta-analysis of the literature. PLoS ONE 7:e32960. 10.1371/journal.pone.0032960
    1. Hui K. K., Liu J., Marina O., Napadow V., Haselgrove C., Kwong K. K., et al. . (2005). The integrated response of the human cerebro-cerebellar and limbic systems to acupuncture stimulation at ST 36 as evidenced by fMRI. Neuroimage 27, 479–496. 10.1016/j.neuroimage.2005.04.037
    1. Hui K. K., Marina O., Claunch J. D., Nixon E. E., Fang J., Liu J., et al. . (2009). Acupuncture mobilizes the brain's default mode and its anti-correlated network in healthy subjects. Brain Res. 1287, 84–103. 10.1016/j.brainres.2009.06.061
    1. Kong J., Gollub R., Huang T., Polich G., Napadow V., Hui K., et al. . (2007). Acupuncture de qi, from qualitative history to quantitative measurement. J. Altern. Complement. Med. 13, 1059–1070. 10.1089/acm.2007.0524
    1. Langevin H. M., Wayne P. M. (2018). What Is the point? The problem with acupuncture research that no one wants to talk about. J. Altern. Complement. Med. 24, 200–207. 10.1089/acm.2017.0366
    1. Li J., Zhang J. H., Yi T., Tang W. J., Wang S. W., Dong J. C. (2014). Acupuncture treatment of chronic low back pain reverses an abnormal brain default mode network in correlation with clinical pain relief. Acupunct. Med. 32, 102–108. 10.1136/acupmed-2013-010423
    1. Liang P., Wang Z., Qian T., Li K. (2014). Acupuncture stimulation of Taichong (Liv3) and Hegu (LI4) modulates the default mode network activity in Alzheimer's disease. Am. J. Alzheimers Dis. Other Demen 29, 739–748. 10.1177/1533317514536600
    1. Liu G., Ma H. J., Hu P. P., Tian Y. H., Hu S., Fan J., et al. . (2013). Effects of painful stimulation and acupuncture on attention networks in healthy subjects. Behav. Brain Funct. 9:23. 10.1186/1744-9081-9-23
    1. Lohmann G., Margulies D. S., Horstmann A., Pleger B., Lepsien J., Goldhahn D., et al. . (2010). Eigenvector centrality mapping for analyzing connectivity patterns in fMRI data of the human brain. PLoS ONE 5:e10232. 10.1371/journal.pone.0010232
    1. Long X., Huang W., Napadow V., Liang F., Pleger B., Villringer A., et al. . (2016). Sustained effects of acupuncture stimulation investigated with centrality mapping analysis. Front. Hum. Neurosci. 10:510. 10.3389/fnhum.2016.00510
    1. Milardi D., Cacciola A., Cutroneo G., Marino S., Irrera M., Cacciola G., et al. . (2016). Red nucleus connectivity as revealed by constrained spherical deconvolution tractography. Neurosci. Lett. 626, 68–73. 10.1016/j.neulet.2016.05.009
    1. Napadow V., Lee J., Kim J., Cina S., Maeda Y., Barbieri R., et al. . (2013). Brain correlates of phasic autonomic response to acupuncture stimulation: an event-related fMRI study. Hum. Brain Mapp. 34, 2592–2606. 10.1002/hbm.22091
    1. Nierhaus T., Forschack N., Piper S. K., Holtze S., Krause T., Taskin B., et al. . (2015a). Imperceptible somatosensory stimulation alters sensorimotor background rhythm and connectivity. J. Neurosci. 35, 5917–5925. 10.1523/JNEUROSCI.3806-14.2015
    1. Nierhaus T., Pach D., Huang W., Long X., Napadow V., Roll S., et al. . (2015b). Differential cerebral response to somatosensory stimulation of an acupuncture point vs. two non-acupuncture points measured with EEG and fMRI. Front. Hum. Neurosci. 9:74. 10.3389/fnhum.2015.00074
    1. Nierhaus T., Pach D., Huang W., Long X., Napadow V., Roll S., et al. . (2016). Difficulties choosing control points in acupuncture research. response: commentary: differential cerebral response, measured with both an EEG and fMRI, to somatosensory stimulation of a single acupuncture point vs. two non-acupuncture points. Front. Hum. Neurosci. 10:404. 10.3389/fnhum.2016.00404
    1. Oldfield R. C. (1971). The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9, 97–113. 10.1016/0028-3932(71)90067-4
    1. Pach D., Hohmann C., Ludtke R., Zimmermann-Viehoff F., Witt C. M., Thiele C. (2011). German translation of the southampton needle sensation questionnaire: use in an experimental acupuncture study. Forsch. Komplementarmed. Klass. Naturheilkd. 18, 321–326. 10.1159/000335241
    1. Power J. D., Barnes K. A., Snyder A. Z., Schlaggar B. L., Petersen S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59, 2142–2154. 10.1016/j.neuroimage.2011.10.018
    1. Rehme A. K., Grefkes C. (2013). Cerebral network disorders after stroke: evidence from imaging-based connectivity analyses of active and resting brain states in humans. J. Physiol. 591, 17–31. 10.1113/jphysiol.2012.243469
    1. Schaechter J. D. (2004). Motor rehabilitation and brain plasticity after hemiparetic stroke. Prog. Neurobiol. 73, 61–72. 10.1016/j.pneurobio.2004.04.001
    1. Schaechter J. D., Connell B. D., Stason W. B., Kaptchuk T. J., Krebs D. E., Macklin E. A., et al. . (2007). Correlated change in upper limb function and motor cortex activation after verum and sham acupuncture in patients with chronic stroke. J. Altern. Complement. Med. 13, 527–532. 10.1089/acm.2007.6316
    1. Shi X. (2002). Science of Acupuncture and Moxibustion. Beijing: China Press of Traditional Chinese Medicine.
    1. Shi X. (2013). Shi Xue-min's Comprehensive Textbook of Acupuncture and Moxibustion. Beijing: Peoples Medical Pub House.
    1. Taubert M., Lohmann G., Margulies D. S., Villringer A., Ragert P. (2011). Long-term effects of motor training on resting-state networks and underlying brain structure. Neuroimage 57, 1492–1498. 10.1016/j.neuroimage.2011.05.078
    1. Wink A. M., De Munck J. C., Van Der Werf Y. D., Van Den Heuvel O. A., Barkhof F. (2012). Fast eigenvector centrality mapping of voxel-wise connectivity in functional magnetic resonance imaging: implementation, validation, and interpretation. Brain Connect. 2, 265–274. 10.1089/brain.2012.0087
    1. Yan C. G., Cheung B., Kelly C., Colcombe S., Craddock R. C., Di Martino A., et al. (2013). A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics. Neuroimage 76C, 183–201. 10.1016/j.neuroimage.2013.03.004
    1. Zhao L., Liu J., Zhang F., Dong X., Peng Y., Qin W., et al. . (2014). Effects of long-term acupuncture treatment on resting-state brain activity in migraine patients: a randomized controlled trial on active acupoints and inactive acupoints. PLoS ONE 9:e99538. 10.1371/journal.pone.0099538
    1. Zuo X. N., Ehmke R., Mennes M., Imperati D., Castellanos F. X., Sporns O., et al. . (2012). Network centrality in the human functional connectome. Cereb. Cortex 22, 1862–1875. 10.1093/cercor/bhr269
    1. 李筱媛, 李军 (LI Xiaoyuan, LI Jun) (2009). “醒脑开窍”针刺法对照非经穴点的设立—经穴特异性临床研究的方法探讨 (Discussion for Non-point Sham Control of Xingnao Kaiqiao Acupuncture). 天津中医药 (Tianjin TCM) 26, 388–390. Retreived from:
    1. 杜蓉, 张春红, 张新亚 (Du Rong, Zhang Chunhong, Zhang Xinya) (2015). “醒脑开窍”针刺法治疗中风后痉挛性瘫痪疗效观察 (Therapeutic Observation on Paralysis after Stroke Treated with Xingnao Kaiqiao Needling Terapy). 针灸临床杂志 (Journal of Clinical Acupuncture and Moxibustion). 31, 21–23. Retreived from:

Source: PubMed

3
Subskrybuj