Systemic psychoneurology and pain syndromes


Cite item

Full Text

Abstract

In the article review, modern data on the pathogenesis of pain are analyzed. With the help of functional neuroimaging it was shown that in response to nociceptive stimuli, there is a more extensive activation of the cerebral connections than was previously thought. Also, the importance of functional connections ensuring the integration coordination of activation of brain structures was demonstrated. In this process, during the sensation of pain, spontaneous cerebral oscillations and changes in the function of attention play a large role. The process of chronic pain is associated with changes in neural connections, their dynamics. At the same time, the changes in the emotional sphere, and cognitive reactions, also have significance. Changes in the headache of different genesis (migraine, cluster, abusus headache, tension headache), as well as with back pain, are considered in detail. It is concluded that the data obtained open up new opportunities for the development of methods of influence that can reduce or completely get rid of the pain of different genesis.

About the authors

I. V Damulin

I.M.Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation; Moscow Clinical Science-Research Center of the Department of Health of Moscow

Email: damulin@mmascience.ru
д-р мед. наук, проф. каф. нервных болезней и нейрохирургии; вед. науч. сотр. 119991, Russian Federation, Moscow, ul. Trubetskaia, d. 8, str. 2

References

  1. Дамулин И.В. Особенности структурной и функциональной организации головного мозга. Журн. неврологии и психиатрии им. с.с.корсакова. 2016; 116 (11): 163-8. doi: 10.17116/jnevro2016116111163-
  2. Van den Heuvel M.P, Sporns O. Network hubs in the human brain. Trends in Cognitive Sciences 2013; 17 (12): 683-96. doi: 10.1016/j.tics.2013.09.012
  3. Van den Heuvel M.P, Bullmore E.T, Sporns O. Comparative connectomics. Trends in Cognitive Sciences 2016; 20 (5): 345-61. doi: 10.1016/j.tics.2016.03.001
  4. Hu L, lannetti G.D. Painful issues in pain prediction. Trends in Neurosciences 2016; 39 (4): 212-20. doi: 10.1016/j.tins.2016.01.004
  5. Kucyi A, Davis K.D. The dynamic pain connectome. Trends in Neurosciences 2015; 38 (2): 86-95. doi: 10.1016/j.tins.2014.11.006
  6. Kucyi A, Davis K.D. The neural code for pain: from single cell electrophysiology to the dynamic pain connectome. Neuroscientist 2016; 107385841666771. doi: 10.1177/1073858416667716
  7. Sprenger C, Finsterbusch J, Buchel C. Spinal cord-midbrain functional connectivity is related to perceived pain intensity: a combined spino-cortical fMRI study. J Neurosci 2015; 35 (10): 4248-57. doi: 10.1523/jneurosci.4897-14.2015
  8. Torta D.M, Legrain V, Mouraux A, Valentini E. Attention to pain! A neurocognitive perspective on attentional modulation of pain in neuroimaging studies. Cortex 2017; 89: 120-34. doi: 10.1016/j.cortex.2017.01.010
  9. Ter Minassian A, Ricalens E, Humbert S et al. Dissociating anticipation from perception: acute pain activates default mode network. Human Brain Mapping 2012; 34 (9): 2228-43. doi: 10.1002/hbm.22062
  10. Cauda F, Palermo S, Costa T et al. Gray matter alterations in chronic pain: A network-oriented meta-analytic approach. NeuroImage: Clinical 2014; 4: 676-86. doi: 10.1016/j.nicl.2014.04.007
  11. Wang Z, Yang Q, Chen L.M. Abnormal dynamics of cortical resting state functional connectivity in chronic headache patients. Magn Reson Imaging 2017; 36: 56-67. doi: 10.1016/j.mri.2016.10.015
  12. Yang Q, Wang Z, Yang L et al. Cortical thickness and functional connectivity abnormality in chronic headache and low back pain patients. Human Brain Mapping 2017; 38 (4): 1815-32. doi: 10.1002/hbm.23484
  13. Amin F.M, Hougaard A, Magon S et al. Change in brain network connectivity during PA- CAP38-induced migraine attacks. Neurology 2015; 86 (2): 180-7. doi: 10.1212/wnl.0000000000002261
  14. Colombo B, Rocca M.A, Messina R. et al. Resting-state fMRI functional connectivity: a new perspective to evaluate pain modulation in migraine? Neurol Sci 2015; 36 (Suppl. 1): S41-S45. doi: 10.1007/s10072-015-2145-x
  15. Coppola G, Di Renzo A, Tinelli E et al. Resting state connectivity between default mode network and insula encodes acute migraine headache. Cephalalgia 2017: 033310241771523. doi: 10.1177/0333102417715230
  16. Hougaard A, Amin F.M, Larsson H.B.W. et al. Increased intrinsic brain connectivity between pons and somatosensory cortex during attacks of migraine with aura. Human Brain Mapping 2017; 38 (5): 2635-642. doi: 10.1002/hbm.23548
  17. Mainero C, Boshyan J, Hadjikhani N. Altered functional magnetic resonance imaging resting-state connectivity in periaqueductal gray networks in migraine. Ann Neurol 2011; 70 (5) : 838-45. doi: 10.1002/ana.22537
  18. Russo A, Tessitore A, Giordano A. et al. Executive resting-state network connectivity in migraine without aura. Cephalalgia 2012; 32 (14): 1041-8. doi: 10.1177/0333102412457089
  19. Russo A, Conte F, Marcuccio L. et al. Abnormal connectivity within executive resting-state network in migraine with aura. J Headache Pain 2015; 16 (Suppl. 1): A156. doi: 10.1186/1129-2377-16-s1-a156
  20. Schulte L.H, May A. The migraine generator revisited: continuous scanning of the migraine cycle over 30 days and three spontaneous attacks. Brain 2016; 139 (7): 1987-93. doi: 10.1093/brain/aww097
  21. Schulte L.H, May A. Of generators, networks and migraine attacks. Curr Opin Neurol 2017; 30 (3): 241-5. doi: 10.1097/wco.0000000000000441
  22. Schwedt T.J, Schlaggar B.L., Mar S. et al. Atypical resting-state functional connectivity of affective pain regions in chronic migraine. Headache 2013; 53 (5): 737-51. doi: 10.1111/head.12081
  23. Schwedt T.J, Larson-Prior L, Coalson R.S. et al. Allodynia and descending pain modulation in migraine: a resting state functional connectivity analysis. Pain Med 2014; 15 (1): 154-65. doi: 10.1111/pme.12267
  24. Tessitore A, Russo A, Conte F. et al. Abnormal connectivity within executive resting-state network in migraine with aura. Headache: The Journal of Head and Face Pain 2015; 55 (6) : 794-805. doi: 10.1111/head.12587
  25. Wang T, Chen N, Zhan W.et al. Altered effective connectivity of posterior thalamus in migraine with cutaneous allodynia: a resting-state fMRI study with granger causality analysis. J Headache Pain 2016; 17 (1): 17-27. doi: 10.1186/s10194-016-0610-4
  26. Farago P, Tuka B, Toth E. et al. Interictal brain activity differs in migraine with and without aura: resting state fMRI study. J Headache Pain 2017; 18 (1): 8-16. doi: 10.1186/s10194- 016-0716-8
  27. Park S-P, Seo J-G, Lee W-K. Osmophobia and allodynia are critical factors for suicidality in patients with migraine. J Headache Pain 2015; 16 (1): 44-9. doi: 10.1186/s10194-015-0529-1
  28. Szabo N, Kincses Z.T, Pardutz A. et al. White matter disintegration in cluster headache. J Headache Pain 2013; 14 (1): 64-9. doi: 10.1186/1129-2377-14-64
  29. Seifert C.L., Magon S., Staehle K. et al. A case-control study on cortical thickness in episodic cluster headache. Headache 2012; 52 (9): 1362-8. doi: 10.1111/j.1526- 4610.2012.02217.x
  30. Naegel S, Holle D, Desmarattes N. et al. Cortical plasticity in episodic and chronic cluster headache. NeuroImage: Clinical 2014; 6: 415-23. doi: 10.1016/j.nicl.2014.10.003
  31. Chiapparini L, Ferraro S, Nigri A. et al. Resting state fMRI in cluster headache: which role? Neurol Sci 2015; 36 (Suppl. 1): S47-S50. doi: 10.1007/s10072-015-2129-x
  32. Kiraly A, Szabo N, Pardutz A. et al. Macro-and microstructural alterations of the subcortical structures in episodic cluster headache. Cephalalgia 2017: 033310241770376. doi: 10.1177/0333102417703762
  33. Farago P, Szabo N, Toth E. et al. Ipsilateral alteration of resting state activity suggests that cortical dysfunction contributes to the pathogenesis of cluster headache. Brain Topography 2016; 30 (2): 281-9. doi: 10.1007/s10548-016-0535-x
  34. Tepper D. Medication overuse headache. Headache 2017; 57 (5): 845-6. doi: 10.1111/head.13034
  35. Chen Z, Chen X, Liu M et al. Altered functional connectivity architecture of the brain in medication overuse headache using resting state fMRI. J Headache Pain 2017; 18 (1): 1-9. doi: 10.1186/s10194-017-0735-0
  36. Schwedt T.J, Chong C.D. Medication overuse headache: pathophysiological insights from structural and functional brain MRI research. Headache 2017. doi: 10.1111/he- ad.13037
  37. Torta D.M, Costa T, Luda E. et al. Nucleus accumbens functional connectivity discriminates medication-overuse headache. NeuroImage: Clinical 2016; 11: 686-93. doi: 10.1016/j.nicl.2016.05.007
  38. Meyer M, Di Scala G, Edde M. et al. Brain structural investigation and hippocampal tractography in medication overuse headache: a native space analysis. Behav Brain Functions 2017; 13 (6): 1-9. doi: 10.1186/s12993-017-0124-5
  39. Schoenen J, Bottin D, Hardy F, Gerard P. Cephalic and extracephalic pressure pain thresholds in chronic tension-type headache. Pain 1991; 47 (2): 145-9. doi: 10.1016/0304- 3959(91)90198-7
  40. Olesen J, Jensen R. Getting away from simple muscle contraction as a mechanism of tension-type headache. Pain 1991; 46 (2): 123-4. doi: 10.1016/0304-3959(91)90065-6
  41. Yu S, Han X. Update of chronic tension-type headache. Curr Pain Headache Rep 2014; 19 (1): 469-76. doi: 10.1007/s11916-014-0469-5
  42. Chen B, He Y, Xia L et al. Cortical plasticity between the pain and pain-free phases in patients with episodic tension-type headache. J Headache Pain 2016; 17 (1): 105-10. doi: 10.1186/s10194-016-0698-6
  43. Pijnenburg M, Brumagne S, Caeyenberghs K. et al. Resting-state functional connectivity of the sensorimotor network in individuals with nonspecific low back pain and the association with the sit-to-stand-to-sit task. Brain Connectivity 2015; 5 (5): 303-11. doi: 10.1089/brain.2014.0309
  44. Pijnenburg M, Hosseini S.M.H, Brumagne S. et al. Structural brain connectivity and the sit- to-stand-to-sit performance in individuals with nonspecific low back pain: a diffusion magnetic resonance imaging-based network analysis. Brain Connectivity 2016; 6 (10): 795-803. doi: 10.1089/brain.2015.0401
  45. Zhang S, Wu W, Huang G. et al. Resting-state connectivity in the default mode network and insula during experimental low back pain. Neural Regeneration Research 2014; 9 (2): 135-42. doi: 10.4103/1673-5374.125341
  46. Letzen J.E, Robinson M.E. Negative mood influences default mode network functional connectivity in patients with chronic low back pain. Pain 2017; 158 (1): 48-57. doi: 10.1097/j.pain.0000000000000708
  47. Apkarian A.V, Sosa Y, Sonty S. et al. Chronic back pain is associated with decreased prefrontal and thalamic gray matter density. J Neurosci 2004; 24 (46): 10410-5. doi: 10.1523/jneurosci.2541-04.2004
  48. Yuan C.H, Shi H.C, Pan P.L. et al. Gray matter abnormalities associated with chronic back pain. Clin J Pain 2017; p. 1-25. doi: 10.1097/ajp.0000000000000489
  49. Fritz H.-C, McAuley J.H, Wittfeld K. et al. Chronic back pain is associated with decreased prefrontal and anterior insular gray matter. Results from a population-based cohort study. J Pain 2016; 17 (1): 111-8. doi: 10.1016/j.jpain.2015.10.003
  50. Kolesar T.A., Bilevicius E., Kornelsen J. Salience, central executive, and sensorimotor network functional connectivity alterations in failed back surgery syndrome. Scand J Pain 2017; 16: 10-4. doi: 10.1016/j.sjpain.2017.01.008
  51. Kornelsen J, Sboto-Frankenstein U, McIver T. et al. Default mode network functional connectivity altered in failed back surgery syndrome. J Pain 2013; 14 (5): 483-91. doi: 10.1016/j.jpain.2012.12.018
  52. Yoon M-S, Manack A, Schramm S. et al. Chronic migraine and chronic tension-type headache are associated with concomitant low back pain: Results of the German Headache Consortium study. Pain 2013; 154 (3): 484-92. doi: 10.1016/j.pain.2012.12.010
  53. Sevel L.S, Letzen J.E, Staud R, Robinson M.E. Interhemispheric dorsolateral prefrontal cortex connectivity is associated with individual differences in pain sensitivity in healthy controls. Brain Connectivity 2016; 6 (5): 357-64. doi: 10.1089/brain.2015.0405
  54. Rehme A.K, Eickhoff S.B, Grefkes C. State-dependent differences between functional and effective connectivity of the human cortical motor system. NeuroImage 2013; 67: 237-46. doi: 10.1016/j.neuroimage.2012.11.027
  55. Bringmann L.F, Scholte H.S, Waldorp L.J. Matching structural, effective, and functional connectivity: a comparison between structural equation modeling and ancestral graphs. Brain Connectivity 2013; 3 (4): 375-85. doi: 10.1089/brain.2012.0130
  56. Mears D, Pollard H.B. Network science and the human brain: Using graph theory to understand the brain and one of its hubs, the amygdala, in health and disease. J Neurosci Res 2016; 94 (6): 590-605. doi: 10.1002/jnr.23705
  57. Iannetti G.D, Mouraux A. From the neuromatrix to the pain matrix (and back). Exp Brain Res 2010; 205 (1): 1-12. doi: 10.1007/s00221-010-2340-1
  58. Legrain V, Iannetti G.D, Plaghki L, Mouraux A. The pain matrix reloaded. A salience detection system for the body. Progress Neurobiol 2011; 93 (1): 111-24. doi: 10.1016/j.pneurobio.2010.10.005
  59. Mouraux A, Diukova A, Lee M.C. et al. A multisensory investigation of the functional significance of the “pain matrix”. NeuroImage 2011; 54 (3): 2237-49. doi: 10.1016/j.neuroi- mage.2010.09.084
  60. Iannetti G.D, Mouraux A. Can the functional MRI responses to physical pain really tell us why social rejection "hurts"? Proceedings of the National Academy of Sciences 2011; 108 (30): E343-E343. doi: 10.1073/pnas.1105451108
  61. Takagi K. A distribution model of functional connectome based on criticality and energy constraints. PLoS ONE 2017; 12 (5): e0177446. doi: 10.1371/journal.pone.0177446

Supplementary files

Supplementary Files
Action
1. JATS XML
Download

Copyright (c) 2017 Consilium Medicum

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).