, Volume 14, Issue 2, pp 484–501 | Cite as

Occipital Nerve Field Transcranial Direct Current Stimulation Normalizes Imbalance Between Pain Detecting and Pain Inhibitory Pathways in Fibromyalgia

Original Article


Occipital nerve field (OCF) stimulation with subcutaneously implanted electrodes is used to treat headaches, more generalized pain, and even failed back surgery syndrome via unknown mechanisms. Transcranial direct current stimulation (tDCS) can predict the efficacy of implanted electrodes. The purpose of this study is to unravel the neural mechanisms involved in global pain suppression, mediated by occipital nerve field stimulation, within the realm of fibromyalgia. Nineteen patients with fibromyalgia underwent a placebo-controlled OCF tDCS. Electroencephalograms were recorded at baseline after active and sham stimulation. In comparison with healthy controls, patients with fibromyalgia demonstrate increased dorsal anterior cingulate cortex, increased premotor/dorsolateral prefrontal cortex activity, and an imbalance between pain-detecting dorsal anterior cingulate cortex and pain-suppressing pregenual anterior cingulate cortex activity, which is normalized after active tDCS but not sham stimulation associated with increased pregenual anterior cingulate cortex activation. The imbalance improvement between the pregenual anterior cingulate cortex and the dorsal anterior cingulate cortex is related to clinical changes. An imbalance assumes these areas communicate and, indeed, abnormal functional connectivity between the dorsal anterior cingulate cortex and pregenual anterior cingulate cortex is noted to be caused by a dysfunctional effective connectivity from the pregenual anterior cingulate cortex to the dorsal anterior cingulate cortex, which improves and normalizes after real tDCS but not sham tDCS. In conclusion, OCF tDCS exerts its effect via activation of the descending pain inhibitory pathway and de-activation of the salience network, both of which are abnormal in fibromyalgia.


Fibromyalgia tDCS Antinociceptive Salience Pain Inhibitory C2 Occipital nerve Connectivity Balance 

Supplementary material

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ESM 1(PDF 1224 kb)


  1. 1.
    Jenkins, B. and S.J. Tepper, Neurostimulation for primary headache disorders: Part 2, review of central neurostimulators for primary headache, overall therapeutic efficacy, safety, cost, patient selection, and future research in headache neuromodulation. Headache, 2011. 51(9): p. 1408-18.Google Scholar
  2. 2.
    Plazier, M., S. Vanneste, I. Dekelver, M. Thimineur and D. De Ridder, Peripheral nerve stimulation for fibromyalgia. Prog Neurol Surg, 2011. 24: p. 133-46.Google Scholar
  3. 3.
    Thimineur, M. and D. De Ridder, C2 area neurostimulation: a surgical treatment for fibromyalgia. Pain Med, 2007. 8(8): p. 639-46.CrossRefPubMedGoogle Scholar
  4. 4.
    De Ridder, D., M. Plazier, T. Menovsky, N. Kamerling and S. Vanneste, C2 subcutaneous stimulation for failed back surgery syndrome: a case report. Neuromodulation, 2013. 16(6): p. 610-3.Google Scholar
  5. 5.
    Plazier, M., S. Tchen, J. Ost, K. Joos, D. De Ridder and S. Vanneste, Is Transcranial Direct Current Stimulation an Effective Predictor for Invasive Occipital Nerve Stimulation Treatment Success in Fibromyalgia Patients? Neuromodulation, 2015. 18(7): p. 623-9.Google Scholar
  6. 6.
    Fields, H., State-dependent opioid control of pain. Nat Rev Neurosci, 2004. 5(7): p. 565-75.CrossRefPubMedGoogle Scholar
  7. 7.
    Kong, J., M.L. Loggia, C. Zyloney, P. Tu, P. Laviolette and R.L. Gollub, Exploring the brain in pain: activations, deactivations and their relation. Pain, 2010. 148(2): p. 257-67.Google Scholar
  8. 8.
    Magis, D., M.A. Bruno, A. Fumal, P.Y. Gerardy, R. Hustinx, S. Laureys and J. Schoenen, Central modulation in cluster headache patients treated with occipital nerve stimulation: an FDG-PET study. BMC Neurol, 2011. 11: p. 25.Google Scholar
  9. 9.
    Baliki, M.N., B. Petre, S. Torbey, K.M. Herrmann, L. Huang, T.J. Schnitzer, H.L. Fields and A.V. Apkarian, Corticostriatal functional connectivity predicts transition to chronic back pain. Nat Neurosci, 2012. 15(8): p. 1117-9.Google Scholar
  10. 10.
    Mansour, A.R., M.N. Baliki, L. Huang, S. Torbey, K.M. Herrmann, T.J. Schnitzer and A.V. Apkarian, Brain white matter structural properties predict transition to chronic pain. Pain, 2013. 154(10): p. 2160-8.Google Scholar
  11. 11.
    Wolfe, F. and B. Walitt, Culture, science and the changing nature of fibromyalgia. Nat Rev Rheumatol, 2013. 9(12): p. 751-5.Google Scholar
  12. 12.
    Plazier, M., J. Ost, G. Stassijns, D. De Ridder and S. Vanneste, Pain characteristics in fibromyalgia: understanding the multiple dimensions of pain. Clin Rheumatol, 2015. 34(4): p. 775-83.Google Scholar
  13. 13.
    Cagnie, B., F. Struyf, A. Cools, B. Castelein, L. Danneels and S. O'Leary, The relevance of scapular dysfunction in neck pain: a brief commentary. J Orthop Sports Phys Ther, 2014. 44(6): p. 435-9.Google Scholar
  14. 14.
    Jensen, K.B., P. Srinivasan, R. Spaeth, Y. Tan, E. Kosek, F. Petzke, S. Carville, P. Fransson, H. Marcus, S.C. Williams, E. Choy, O. Vitton, R. Gracely, M. Ingvar and J. Kong, Overlapping structural and functional brain changes in patients with long-term exposure to fibromyalgia pain. Arthritis Rheum, 2013. 65(12): p. 3293-303.Google Scholar
  15. 15.
    Mouraux, A., A. Diukova, M.C. Lee, R.G. Wise and G.D. Iannetti, A multisensory investigation of the functional significance of the "pain matrix". Neuroimage, 2011. 54(3): p. 2237-49.Google Scholar
  16. 16.
    Pujol, J., D. Macia, A. Garcia-Fontanals, L. Blanco-Hinojo, M. Lopez-Sola, S. Garcia-Blanco, V. Poca-Dias, B.J. Harrison, O. Contreras-Rodriguez, J. Monfort, F. Garcia-Fructuoso and J. Deus, The contribution of sensory system functional connectivity reduction to clinical pain in fibromyalgia. Pain, 2014. 155(8): p. 1492-503.Google Scholar
  17. 17.
    Baliki, M.N., P.Y. Geha, A.V. Apkarian and D.R. Chialvo, Beyond feeling: chronic pain hurts the brain, disrupting the default-mode network dynamics. J Neurosci, 2008. 28(6): p. 1398-403.Google Scholar
  18. 18.
    Iannetti, G.D. and A. Mouraux, From the neuromatrix to the pain matrix (and back). Exp Brain Res, 2010. 205(1): p. 1-12.Google Scholar
  19. 19.
    Legrain, V., G.D. Iannetti, L. Plaghki and A. Mouraux, The pain matrix reloaded: a salience detection system for the body. Prog Neurobiol, 2011. 93(1): p. 111-24.Google Scholar
  20. 20.
    De Ridder, D. and S. Vanneste, Burst and Tonic Spinal Cord Stimulation: Different and Common Brain Mechanisms. Neuromodulation, 2016. 19(1): p. 47-59.Google Scholar
  21. 21.
    Plazier, M., I. Dekelver, S. Vanneste, G. Stassijns, T. Menovsky, M. Thimineur and D. De Ridder, Occipital nerve stimulation in fibromyalgia: a double-blind placebo-controlled pilot study with a sixmonth follow-up. Neuromodulation, 2014. 17(3): p. 256-64.Google Scholar
  22. 22.
    Plazier, M., J. Ost, G. Stassijns, D. De Ridder and S. Vanneste, C2 Nerve Field Stimulation for the Treatment of Fibromyalgia: A Prospective, Double-blind, Randomized, Controlled Cross-over Study. Brain Stimul, 2015. 8(4): p. 751-7.Google Scholar
  23. 23.
    Vanneste, S., B. Langguth and D. De Ridder, Do tDCS and TMS influence tinnitus transiently via a direct cortical and indirect somatosensory modulating effect? A combined TMS-tDCS and TENS study. Brain Stimul, 2011. 4(4): p. 242-52.Google Scholar
  24. 24.
    Plazier, M., J. Ost, E. Snijders, M. Gilbers, T. Vancamp, D. De Ridder and S. Vanneste, Laser-Evoked Potentials in Fibromyalgia: The Influence of Greater Occipital Nerve Stimulation on Cerebral Pain Processing. Neuromodulation, 2015. 18(5): p. 376-83.Google Scholar
  25. 25.
    Kovacs, S., R. Peeters, D. De Ridder, M. Plazier, T. Menovsky and S. Sunaert, Central effects of occipital nerve electrical stimulation studied by functional magnetic resonance imaging. Neuromodulation, 2011. 14(1): p. 46-55; discussion 56-7.Google Scholar
  26. 26.
    Garcia-Larrea, L. and R. Peyron, Pain matrices and neuropathic pain matrices: a review. Pain, 2013. 154 Suppl 1: p. S29-43.Google Scholar
  27. 27.
    Wolfe, F., H.A. Smythe, M.B. Yunus, R.M. Bennett, C. Bombardier, D.L. Goldenberg, P. Tugwell, S.M. Campbell, M. Abeles, P. Clark and et al., The American College of Rheumatology 1990 Criteria for the Classification of Fibromyalgia. Report of the Multicenter Criteria Committee. Arthritis Rheum, 1990. 33(2): p. 160-72.Google Scholar
  28. 28.
    Plazier, M., J. Ost, G. Stassijns, D. De Ridder and S. Vanneste, Pain characteristics in fibromyalgia: understanding the multiple dimensions of pain. Clin Rheumatol, 2014.Google Scholar
  29. 29.
    Bennett, R., The Fibromyalgia Impact Questionnaire (FIQ): a review of its development, current version, operating characteristics and uses. Clin Exp Rheumatol, 2005. 23(5 Suppl 39): p. S154-62.Google Scholar
  30. 30.
    Osman, A., F.X. Barrios, B.A. Kopper, W. Hauptmann, J. Jones and E. O'Neill, Factor structure, reliability, and validity of the Pain Catastrophizing Scale. J Behav Med, 1997. 20(6): p. 589-605.Google Scholar
  31. 31.
    Congedo, M., EureKa! (Version 3.0) [Computer Software]. Knoxville, TN: NovaTech EEG Inc. Freeware available at www.NovaTechEEG. 2002.
  32. 32.
    Pascual-Marqui, R.D., Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods Find Exp Clin Pharmacol, 2002. 24 Suppl D: p. 5-12.PubMedGoogle Scholar
  33. 33.
    Jurcak V, Tsuzuki D, Dan I. 10/20, 10/10, and 10/5 systems revisited: their validity as relative headsurface-based positioning systems. Neuroimage. Feb 15 2007. 34(4): p.1600-1611.Google Scholar
  34. 34.
    Fuchs A. Combining Brain Imaging Technologies: Using Brain Surfaces. In: H. Nowak, J. Haueisen, F. Geißler, Huonker R, eds. Biomag 2002, Proceedings of the 13th International Conference on Biomagnetism. Berlin: VDE Verlag; 2002. p. 878-880.Google Scholar
  35. 35.
    Lancaster JL, Woldorff MG, Parsons LM, et al. Automated Talairach atlas labels for functional brain mapping. Hum Brain Mapp. Jul 2000. 10(3): p. 120-131.Google Scholar
  36. 36.
    Pascual-Marqui, R. Instantaneous and lagged measurements of linear and nonlinear dependence between groups of multivariate time series: frequency decomposition. 2007.
  37. 37.
    Pascual-Marqui, R. Discrete, 3D distributed, linear imaging methods of electric neuronal activity. Part 1: exact, zero error localization. 2007.
  38. 38.
    Congedo, M., R.E. John, D. De Ridder, L. Prichep and R. Isenhart, On the "dependence" of "independent" group EEG sources; an EEG study on two large databases. Brain Topogr, 2010. 23(2): p. 134-8.Google Scholar
  39. 39.
    Bloomfield P. Fourier Analysis of Time Series: An Introduction, 2nd Edition. New York: Wiley; 2000.Google Scholar
  40. 40.
    Geweke, J., Measurement of lineair dependence and feedback between multiple time series. J. Am. Stat. Assoc., 1982. 77: p. 304.Google Scholar
  41. 41.
    Granger, C.W.J., Investigating causal relations by econometrics models and crosss-spectral methods. Econometrica, 1969. 37: p. 424.CrossRefGoogle Scholar
  42. 42.
    Nichols, T.E. and A.P. Holmes, Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp, 2002. 15(1): p. 1-25.Google Scholar
  43. 43.
    Frank, E., S. Wilfurth, M. Landgrebe, P. Eichhammer, G. Hajak and B. Langguth, Anodal skin lesions after treatment with transcranial direct current stimulation. Brain Stimul, 2010. 3(1): p. 58-9.Google Scholar
  44. 44.
    Price, D.D., Psychological and neural mechanisms of the affective dimension of pain. Science, 2000. 288(5472): p. 1769-72.CrossRefPubMedGoogle Scholar
  45. 45.
    Bushnell, M.C., M. Ceko and L.A. Low, Cognitive and emotional control of pain and its disruption in chronic pain. Nat Rev Neurosci, 2013. 14(7): p. 502-11.CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Rainville, P., G.H. Duncan, D.D. Price, B. Carrier and M.C. Bushnell, Pain affect encoded in human anterior cingulate but not somatosensory cortex. Science, 1997. 277(5328): p. 968-71.Google Scholar
  47. 47.
    Frot, M., F. Mauguiere, M. Magnin and L. Garcia-Larrea, Parallel processing of nociceptive A-delta inputs in SII and midcingulate cortex in humans. J Neurosci, 2008. 28(4): p. 944-52.Google Scholar
  48. 48.
    Leknes, S., C. Berna, M.C. Lee, G.D. Snyder, G. Biele and I. Tracey, The importance of context: when relative relief renders pain pleasant. Pain, 2013. 154(3): p. 402-10.Google Scholar
  49. 49.
    Craig, A.D., How do you feel? Interoception: the sense of the physiological condition of the body. Nat Rev Neurosci, 2002. 3(8): p. 655-66.CrossRefPubMedGoogle Scholar
  50. 50.
    Craig, A.D., Distribution of trigeminothalamic and spinothalamic lamina I terminations in the macaque monkey. J Comp Neurol, 2004. 477(2): p. 119-48.CrossRefPubMedGoogle Scholar
  51. 51.
    Aminoff, E., N. Gronau and M. Bar, The parahippocampal cortex mediates spatial and nonspatial associations. Cereb Cortex, 2007. 17(7): p. 1493-503.CrossRefPubMedGoogle Scholar
  52. 52.
    Aminoff, E.M., K. Kveraga and M. Bar, The role of the parahippocampal cortex in cognition. Trends Cogn Sci, 2013. 17(8): p. 379-90.CrossRefPubMedPubMedCentralGoogle Scholar
  53. 53.
    Eippert, F., U. Bingel, E.D. Schoell, J. Yacubian, R. Klinger, J. Lorenz and C. Buchel, Activation of the opioidergic descending pain control system underlies placebo analgesia. Neuron, 2009. 63(4): p. 533-43Google Scholar
  54. 54.
    Yilmaz, P., M. Diers, S. Diener, M. Rance, M. Wessa and H. Flor, Brain correlates of stress-induced analgesia. Pain, 2010. 151(2): p. 522-9.Google Scholar
  55. 55.
    Kuhn, S. and J. Gallinat, The neural correlates of subjective pleasantness. Neuroimage, 2012. 61(1): p. 289-94.CrossRefPubMedGoogle Scholar
  56. 56.
    Ellingsen, D.M., J. Wessberg, M. Eikemo, J. Liljencrantz, T. Endestad, H. Olausson and S. Leknes, Placebo improves pleasure and pain through opposite modulation of sensory processing. Proc Natl Acad Sci U S A, 2013. 110(44): p. 17993-8.Google Scholar
  57. 57.
    Kamping, S., I.C. Bomba, P. Kanske, E. Diesch and H. Flor, Deficient modulation of pain by a positive emotional context in fibromyalgia patients. Pain, 2013. 154(9): p. 1846-55.Google Scholar
  58. 58.
    De Ridder, D., A.B. Elgoyhen, R. Romo and B. Langguth, Phantom percepts: tinnitus and pain as persisting aversive memory networks. Proc Natl Acad Sci U S A, 2011. 108(20): p. 8075-80.Google Scholar
  59. 59.
    Flor, H., L. Nikolajsen and T. Staehelin Jensen, Phantom limb pain: a case of maladaptive CNS plasticity? Nat Rev Neurosci, 2006. 7(11): p. 873-81.CrossRefPubMedGoogle Scholar
  60. 60.
    De Ridder, D., M. Plazier, N. Kamerling, T. Menovsky and S. Vanneste, Burst spinal cord stimulation for limb and back pain. World Neurosurg, 2013. 80(5): p. 642-649 e1.Google Scholar
  61. 61.
    Fornito, A. and E.T. Bullmore, Connectomics: A new paradigm for understanding brain disease. Eur Neuropsychopharmacol, 2015. 25(5): p. 733-48.Google Scholar
  62. 62.
    Newman, H.M., R.T. Stevens and A.V. Apkarian, Direct spinal projections to limbic and striatal areas: anterograde transport studies from the upper cervical spinal cord and the cervical enlargement in squirrel monkey and rat. J Comp Neurol, 1996. 365(4): p. 640-58.CrossRefPubMedGoogle Scholar
  63. 63.
    Chandler, M.J., J. Zhang and R.D. Foreman, Vagal, sympathetic and somatic sensory inputs to upper cervical (C1-C3) spinothalamic tract neurons in monkeys. J Neurophysiol, 1996. 76(4): p. 2555-67.PubMedGoogle Scholar
  64. 64.
    Chandler, M.J., S.F. Hobbs, D.C. Bolser and R.D. Foreman, Effects of vagal afferent stimulation on cervical spinothalamic tract neurons in monkeys. Pain, 1991. 44(1): p. 81-7.Google Scholar
  65. 65.
    Chandler, M.J., C. Qin, Y. Yuan and R.D. Foreman, Convergence of trigeminal input with visceral and phrenic inputs on primate C1-C2 spinothalamic tract neurons. Brain Res, 1999. 829(1-2): p. 204-8.Google Scholar
  66. 66.
    Leone, M., A. Proietti Cecchini, E. Mea, V. Tullo, M. Curone and G. Bussone, Neuroimaging and pain: a window on the autonomic nervous system. Neurol Sci, 2006. 27 Suppl 2: p. S134-7.Google Scholar
  67. 67.
    Boly, M., E. Balteau, C. Schnakers, C. Degueldre, G. Moonen, A. Luxen, C. Phillips, P. Peigneux, P. Maquet and S. Laureys, Baseline brain activity fluctuations predict somatosensory perception in humans. Proc Natl Acad Sci U S A, 2007. 104(29): p. 12187-92.Google Scholar
  68. 68.
    Smith, M.V., A.V. Apkarian and C.J. Hodge, Jr., Somatosensory response properties of contralaterally projecting spinothalamic and nonspinothalamic neurons in the second cervical segment of the cat. J Neurophysiol, 1991. 66(1): p. 83-102.PubMedGoogle Scholar
  69. 69.
    Kanold, P.O. and E.D. Young, Proprioceptive information from the pinna provides somatosensory input to cat dorsal cochlear nucleus. J Neurosci, 2001. 21(19): p. 7848-58.Google Scholar
  70. 70.
    Kanold, P.O. and E.D. Young, Proprioceptive information from the pinna provides somatosensory input to cat dorsal cochlear nucleus. J Neurosci 2001. 21(19): p. 7848-7858.PubMedGoogle Scholar
  71. 71.
    Seeley, W.W., V. Menon, A.F. Schatzberg, J. Keller, G.H. Glover, H. Kenna, A.L. Reiss and M.D. Greicius, Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci, 2007. 27(9): p. 2349-56.Google Scholar
  72. 72.
    Mulert, C., L. Jager, R. Schmitt, P. Bussfeld, O. Pogarell, H.J. Moller, G. Juckel and U. Hegerl, Integration of fMRI and simultaneous EEG: towards a comprehensive understanding of localization and time-course of brain activity in target detection. Neuroimage, 2004. 22(1): p. 83-94.Google Scholar
  73. 73.
    Vitacco, D., D. Brandeis, R. Pascual-Marqui and E. Martin, Correspondence of event-related potential tomography and functional magnetic resonance imaging during language processing. Hum Brain Mapp, 2002. 17(1): p. 4-12.Google Scholar
  74. 74.
    Worrell, G.A., T.D. Lagerlund, F.W. Sharbrough, B.H. Brinkmann, N.E. Busacker, K.M. Cicora and T.J. O'Brien, Localization of the epileptic focus by low-resolution electromagnetic tomography in patients with a lesion demonstrated by MRI. Brain Topogr, 2000. 12(4): p. 273-82.Google Scholar
  75. 75.
    Dierks, T., V. Jelic, R.D. Pascual-Marqui, L. Wahlund, P. Julin, D.E. Linden, K. Maurer, B. Winblad and A. Nordberg, Spatial pattern of cerebral glucose metabolism (PET) correlates with localization of intracerebral EEG-generators in Alzheimer's disease. Clin Neurophysiol, 2000. 111(10): p. 1817-24.Google Scholar
  76. 76.
    Pizzagalli, D.A., T.R. Oakes, A.S. Fox, M.K. Chung, C.L. Larson, H.C. Abercrombie, S.M. Schaefer, R.M. Benca and R.J. Davidson, Functional but not structural subgenual prefrontal cortex abnormalities in melancholia. Mol Psychiatry, 2004. 9(4): p. 325, 393-405.Google Scholar
  77. 77.
    Zumsteg, D., R.A. Wennberg, V. Treyer, A. Buck and H.G. Wieser, H2(15)O or 13NH3 PET and electromagnetic tomography (LORETA) during partial status epilepticus. Neurology, 2005. 65(10): p. 1657-60.Google Scholar
  78. 78.
    Zaehle, T., L. Jancke and M. Meyer, Electrical brain imaging evidences left auditory cortex involvement in speech and non-speech discrimination based on temporal features. Behav Brain Funct, 2007. 3: p. 63.Google Scholar
  79. 79.
    Vanneste, S., M. Plazier, E. van der Loo, P. Van de Heyning and D. De Ridder, The difference between uni- and bilateral auditory phantom percept. Clin Neurophysiol, 2010.Google Scholar
  80. 80.
    Vanneste, S., M. Plazier, E. van der Loo, P. Van de Heyning and D. De Ridder, The difference between uni- and bilateral auditory phantom percept. Clin Neurophysiol, 2011. 122(3): p. 578-87.Google Scholar
  81. 81.
    Zumsteg, D., A.M. Lozano and R.A. Wennberg, Depth electrode recorded cerebral responses with deep brain stimulation of the anterior thalamus for epilepsy. Clin Neurophysiol, 2006. 117(7): p. 1602-9.Google Scholar
  82. 82.
    Zumsteg, D., A.M. Lozano, H.G. Wieser and R.A. Wennberg, Cortical activation with deep brain stimulation of the anterior thalamus for epilepsy. Clin Neurophysiol, 2006. 117(1): p. 192-207.Google Scholar
  83. 83.
    Volpe, U., A. Mucci, P. Bucci, E. Merlotti, S. Galderisi and M. Maj, The cortical generators of P3a and P3b: a LORETA study. Brain Res Bull, 2007. 73(4-6): p. 220-30.Google Scholar
  84. 84.
    Pizzagalli, D., R.D. Pascual-Marqui, J.B. Nitschke, T.R. Oakes, C.L. Larson, H.C. Abercrombie, S.M. Schaefer, J.V. Koger, R.M. Benca and R.J. Davidson, Anterior cingulate activity as a predictor of degree of treatment response in major depression: evidence from brain electrical tomography analysis. Am J Psychiatry, 2001. 158(3): p. 405-15.Google Scholar
  85. 85.
    Zumsteg, D., A.M. Lozano and R.A. Wennberg, Mesial temporal inhibition in a patient with deep brain stimulation of the anterior thalamus for epilepsy. Epilepsia, 2006. 47(11): p. 1958-62.CrossRefPubMedGoogle Scholar
  86. 86.
    Vanneste, S., M. Plazier, E. der Loo, P.V. de Heyning, M. Congedo and D. De Ridder, The neural correlates of tinnitus-related distress. Neuroimage, 2010. 52(2): p. 470-80.Google Scholar
  87. 87.
    von Leupoldt, A., T. Sommer, S. Kegat, H.J. Baumann, H. Klose, B. Dahme and C. Buchel, Dyspnea and pain share emotion-related brain network. Neuroimage, 2009. 48(1): p. 200-6.Google Scholar
  88. 88.
    Mataix-Cols, D., S.K. An, N.S. Lawrence, X. Caseras, A. Speckens, V. Giampietro, M.J. Brammer and M.L. Phillips, Individual differences in disgust sensitivity modulate neural responses to aversive/disgusting stimuli. Eur J Neurosci, 2008. 27(11): p. 3050-8.Google Scholar
  89. 89.
    Song, J.J., S. Vanneste and D. De Ridder, Dysfunctional noise cancelling of the rostral anterior cingulate cortex in tinnitus patients. PLoS One, 2015. 10(4): p. e0123538.Google Scholar
  90. 90.
    Alsalman, O., J. Ost, R. Vanspauwen, C. Blaivie, D. De Ridder and S. Vanneste, The Neural Correlates of Chronic Symptoms of Vertigo Proneness in Humans. PLoS One, 2016. 11(4): p. e0152309.Google Scholar
  91. 91.
    Buckholtz, J.W. and A. Meyer-Lindenberg, MAOA and the neurogenetic architecture of human aggression. Trends Neurosci, 2008. 31(3): p. 120-9.CrossRefPubMedGoogle Scholar
  92. 92.
    Eisenberger, N.I., B.M. Way, S.E. Taylor, W.T. Welch and M.D. Lieberman, Understanding genetic risk for aggression: clues from the brain's response to social exclusion. Biol Psychiatry, 2007. 61(9): p. 1100-8.Google Scholar
  93. 93.
    Meyer-Lindenberg, A., J.W. Buckholtz, B. Kolachana, R.H. A, L. Pezawas, G. Blasi, A. Wabnitz, R. Honea, B. Verchinski, J.H. Callicott, M. Egan, V. Mattay and D.R. Weinberger, Neural mechanisms of genetic risk for impulsivity and violence in humans. Proc Natl Acad Sci U S A, 2006. 103(16): p. 6269-74.Google Scholar

Copyright information

© The American Society for Experimental NeuroTherapeutics, Inc. 2016

Authors and Affiliations

  1. 1.Department of Surgical Sciences, Dunedin School of MedicineUniversity of OtagoDunedinNew Zealand
  2. 2.BRAI2N, Sint Augustinus Hospital AntwerpAntwerpBelgium
  3. 3.School of Behavioral and Brain SciencesThe University of Texas at DallasDallasUSA

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