В обзорной статье анализируются современные данные о патогенезе боли. При помощи функциональной нейровизуализации было показано, что в ответ на ноцицептивные стимулы происходит более обширная активация церебральных связей, чем это считалось ранее. Также была продемонстрирована и важность функциональных связей, обеспечивающих интеграционную координацию активации структур головного мозга. При этом в процессе ощущения боли играют большую роль спонтанные церебральные осцилляции и изменения функции внимания. Процесс хронификации боли связан с изменениями нейрональных связей, их динамикой. При этом имеют значение и изменения в эмоциональной сфере, и когнитивные реакции. Детально рассматриваются изменения при головной боли разного генеза (мигрень, кластерная, абузусная головная боль, головная боль напряжения), а также при болях в спине. Делается вывод о том, что полученные данные открывают новые возможности для разработки методов воздействия, способных уменьшить или совсем избавиться от боли разного генеза.
Ключевые слова: структурная и функциональная организация головного мозга, коннектом, методы функциональной нейровизуализации, системная психоневрология, боль, патогенез.
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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.
Key words: structural and functional organization of the brain, connectome, methods of functional neuroimaging, systemic psychoneurology, pain, pathogenesis.
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/jnevro2016116111163-168 / Damulin I.V. Osobennosti strukturnoi i funktsionalnoi organizatsii golovnogo mozga. Zhurn. nevrologii i psikhiatrii im. S.S.Korsakova. 2016; 116 (11): 163–8. DOI: 10.17116/jnevro2016116111163-168 [in Russian]
2. Дамулин И.В. Системная психоневрология: современные представления о структурной и функциональной организации головного мозга. Consilium Medicum. 2017; 19 (2): 8–13. / Damulin I.V. Sistemnaia psikhonevrologiia: sovremennye predstavleniia o strukturnoi i funktsionalnoi organizatsii golovnogo mozga. Consilium Medicum. 2017; 19 (2): 8–13. [in Russian]
3. Bullmore E, Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Rev Neurosci 2009; 10 (3): 186–98. DOI: 10.1038/nrn2575
4. Petersen SE, Sporns O. Brain networks and cognitive architectures. Neuron 2015; 88 (1): 207–19. DOI: 10.1016/j.neuron.2015.09.027
5. Van den Heuvel MP, 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
6. Van den Heuvel MP, Bullmore ET, Sporns O. Comparative connectomics. Trends in Cognitive Sciences 2016; 20 (5): 345–61. DOI: 10.1016/j.tics.2016.03.001
7. Hu L, Iannetti GD. Painful issues in pain prediction. Trends in Neurosciences 2016; 39 (4): 212–20. DOI: 10.1016/j.tins.2016.01.004
8. Kucyi A, Davis KD. The dynamic pain connectome. Trends in Neurosciences 2015; 38 (2): 86–95. DOI: 10.1016/j.tins.2014.11.006
9. Kucyi A, Davis KD. The neural code for pain: from single cell electrophysiology to the dynamic pain connectome. Neuroscientist 2016; 107385841666771. DOI: 10.1177/1073858416667716
10. 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
11. Torta DM, 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
12. 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
13. 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
14. Wang Z, Yang Q, Chen LM. 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
15. 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
16. Amin FM, Hougaard A, Magon S et al. Change in brain network connectivity during PACAP38-induced migraine attacks. Neurology 2015; 86 (2): 180–7. DOI: 10.1212/wnl.0000000000002261
17. Colombo B, Rocca MA, 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
18. 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
19. Hougaard A, Amin FM, Larsson HBW 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
20. 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
21. 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
22. 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
23. Schulte LH, 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
24. Schulte LH, May A. Of generators, networks and migraine attacks. Curr Opin Neurol 2017; 30 (3): 241–5. DOI: 10.1097/wco.0000000000000441
25. Schwedt TJ, Schlaggar BL, 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
26. Schwedt TJ, Larson-Prior L, Coalson RS 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
27. 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
28. 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
29. 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
30. 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
31. Szabo N, Kincses ZT, 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
32. Seifert CL, 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
33. 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
34. 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
35. 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
36. 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
37. Tepper D. Medication overuse headache. Headache 2017; 57 (5): 845–6. DOI: 10.1111/head.13034
38. 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
39. Schwedt TJ, Chong CD. Medication overuse headache: pathophysiological insights from structural and functional brain MRI research. Headache 2017. DOI: 10.1111/head.13037
40. Torta DM, 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
41. 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
42. 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
43. 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
44. 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
45. 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
46. 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
47. Pijnenburg M, Hosseini SMH, 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
48. 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
49. Letzen JE, Robinson ME. 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
50. Apkarian AV, 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
51. Yuan CH, Shi HC, Pan PL et al. Gray matter abnormalities associated with chronic back pain. Clin J Pain 2017; p. 1–25. DOI: 10.1097/ajp.0000000000000489
52. Fritz H-C, McAuley JH, 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
53. Kolesar TA, 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
54. 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
55. 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
56. Sevel LS, Letzen JE, Staud R, Robinson ME. 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
57. Rehme AK, Eickhoff SB, 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
58. Bringmann LF, Scholte HS, Waldorp LJ. 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
59. Mears D, Pollard HB. 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
60. Iannetti GD, 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
61. Legrain V, Iannetti GD, 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
62. Mouraux A, Diukova A, Lee MC et al. A multisensory investigation of the functional significance of the “pain matrix”. NeuroImage 2011; 54 (3): 2237–49. DOI: 10.1016/j.neuroimage.2010.09.084
63. Iannetti GD, 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
64. 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
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1. Damulin I.V. Osobennosti strukturnoi i funktsionalnoi organizatsii golovnogo mozga. Zhurn. nevrologii i psikhiatrii im. S.S.Korsakova. 2016; 116 (11): 163–8. DOI: 10.17116/jnevro2016116111163-168 [in Russian]
2. Damulin I.V. Sistemnaia psikhonevrologiia: sovremennye predstavleniia o strukturnoi i funktsionalnoi organizatsii golovnogo mozga. Consilium Medicum. 2017; 19 (2): 8–13. [in Russian]
3. Bullmore E, Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Rev Neurosci 2009; 10 (3): 186–98. DOI: 10.1038/nrn2575
4. Petersen SE, Sporns O. Brain networks and cognitive architectures. Neuron 2015; 88 (1): 207–19. DOI: 10.1016/j.neuron.2015.09.027
5. Van den Heuvel MP, 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
6. Van den Heuvel MP, Bullmore ET, Sporns O. Comparative connectomics. Trends in Cognitive Sciences 2016; 20 (5): 345–61. DOI: 10.1016/j.tics.2016.03.001
7. Hu L, Iannetti GD. Painful issues in pain prediction. Trends in Neurosciences 2016; 39 (4): 212–20. DOI: 10.1016/j.tins.2016.01.004
8. Kucyi A, Davis KD. The dynamic pain connectome. Trends in Neurosciences 2015; 38 (2): 86–95. DOI: 10.1016/j.tins.2014.11.006
9. Kucyi A, Davis KD. The neural code for pain: from single cell electrophysiology to the dynamic pain connectome. Neuroscientist 2016; 107385841666771. DOI: 10.1177/1073858416667716
10. 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
11. Torta DM, 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
12. 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
13. 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
14. Wang Z, Yang Q, Chen LM. 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
15. 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
16. Amin FM, Hougaard A, Magon S et al. Change in brain network connectivity during PACAP38-induced migraine attacks. Neurology 2015; 86 (2): 180–7. DOI: 10.1212/wnl.0000000000002261
17. Colombo B, Rocca MA, 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
18. 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
19. Hougaard A, Amin FM, Larsson HBW 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
20. 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
21. 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
22. 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
23. Schulte LH, 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
24. Schulte LH, May A. Of generators, networks and migraine attacks. Curr Opin Neurol 2017; 30 (3): 241–5. DOI: 10.1097/wco.0000000000000441
25. Schwedt TJ, Schlaggar BL, 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
26. Schwedt TJ, Larson-Prior L, Coalson RS 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
27. 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
28. 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
29. 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
30. 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
31. Szabo N, Kincses ZT, 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
32. Seifert CL, 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
33. 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
34. 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
35. 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
36. 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
37. Tepper D. Medication overuse headache. Headache 2017; 57 (5): 845–6. DOI: 10.1111/head.13034
38. 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
39. Schwedt TJ, Chong CD. Medication overuse headache: pathophysiological insights from structural and functional brain MRI research. Headache 2017. DOI: 10.1111/head.13037
40. Torta DM, 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
41. 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
42. 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
43. 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
44. 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
45. 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
46. 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
47. Pijnenburg M, Hosseini SMH, 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
48. 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
49. Letzen JE, Robinson ME. 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
50. Apkarian AV, 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
51. Yuan CH, Shi HC, Pan PL et al. Gray matter abnormalities associated with chronic back pain. Clin J Pain 2017; p. 1–25. DOI: 10.1097/ajp.0000000000000489
52. Fritz H-C, McAuley JH, 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
53. Kolesar TA, 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
54. 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
55. 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
56. Sevel LS, Letzen JE, Staud R, Robinson ME. 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
57. Rehme AK, Eickhoff SB, 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
58. Bringmann LF, Scholte HS, Waldorp LJ. 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
59. Mears D, Pollard HB. 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
60. Iannetti GD, 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
61. Legrain V, Iannetti GD, 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
62. Mouraux A, Diukova A, Lee MC et al. A multisensory investigation of the functional significance of the “pain matrix”. NeuroImage 2011; 54 (3): 2237–49. DOI: 10.1016/j.neuroimage.2010.09.084
63. Iannetti GD, 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
64. 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
Авторы
И.В.Дамулин
ФГАОУ ВО «Первый Московский государственный медицинский университет им. И.М.Сеченова» Минздрава России. 119991, Россия, Москва, ул. Трубецкая, д. 8, стр. 2;
ГБУЗ «Московский клинический научно-практический центр» Департамента здравоохранения г. Москвы. 111123, Россия, Москва, ш. Энтузиастов, д. 86 damulin@mmascience.ru
________________________________________________
I.V.Damulin
I.M.Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation. 119991, Russian Federation, Moscow, ul. Trubetskaia, d. 8, str. 2;
Moscow Clinical Science-Research Center of the Department of Health of Moscow. 111123, Russian Federation, Moscow, sh. Entuziastov, d. 86 damulin@mmascience.ru