Is Migraine Associated to Brain Anatomical Alterations? New Data and Coordinate-Based Meta-analysis

Abstract

A growing number of studies investigate brain anatomy in migraine using voxel- (VBM) and surface-based morphometry (SBM), as well as diffusion tensor imaging (DTI). The purpose of this article is to identify consistent patterns of anatomical alterations associated with migraine. First, 19 migraineurs without aura and 19 healthy participants were included in a brain imaging study. T1-weighted MRIs and DTI sequences were acquired and analyzed using VBM, SBM and tract-based spatial statistics. No significant alterations of gray matter (GM) volume, cortical thickness, cortical gyrification, sulcus depth and white-matter tract integrity could be observed. However, migraineurs displayed decreased white matter (WM) volume in the left superior longitudinal fasciculus. Second, a systematic review of the literature employing VBM, SBM and DTI was conducted to investigate brain anatomy in migraine. Meta-analysis was performed using Seed-based d Mapping via permutation of subject images (SDM-PSI) on GM volume, WM volume and cortical thickness data. Alterations of GM volume, WM volume, cortical thickness or white-matter tract integrity were reported in 72%, 50%, 56% and 33% of published studies respectively. Spatial distribution and direction of the disclosed effects were highly inconsistent across studies. The SDM-PSI analysis revealed neither significant decrease nor significant increase of GM volume, WM volume or cortical thickness in migraine. Overall there is to this day no strong evidence of specific brain anatomical alterations reliably associated to migraine. Possible explanations of this conflicting literature are discussed. Trial registration number: NCT02791997, registrated February 6th, 2015.

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Availability of Data and Material

The data that support the findings of this study are not publically available as participants did not consent to data sharing.

References

  1. Acar F, Seurinck R, Eickhoff SB, Moerkerke B (2018) Assessing robustness against potential publication bias in Activation Likelihood Estimation (ALE) meta-analyses for fMRI. PLoS ONE 13:e0208177. https://doi.org/10.1371/journal.pone.0208177

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  2. Albajes-Eizagirre A, Solanes A, Fullana MA et al (2019a) Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI). JoVE. https://doi.org/10.3791/59841

    Article  PubMed  Google Scholar 

  3. Albajes-Eizagirre A, Solanes A, Vieta E, Radua J (2019b) Voxel-based meta-analysis via permutation of subject images (PSI): theory and implementation for SDM. NeuroImage 186:174–184. https://doi.org/10.1016/j.neuroimage.2018.10.077

    Article  PubMed  Google Scholar 

  4. Andersson JLR, Sotiropoulos SN (2016) An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. NeuroImage 125:1063–1078. https://doi.org/10.1016/j.neuroimage.2015.10.019

    Article  PubMed  PubMed Central  Google Scholar 

  5. Arkink EB, Schmitz N, Schoonman GG et al (2017) The anterior hypothalamus in cluster headache. Cephalalgia Int J Headache 37:1039–1050. https://doi.org/10.1177/0333102416660550

    Article  Google Scholar 

  6. Ashburner J (2007) A fast diffeomorphic image registration algorithm. NeuroImage 38:95–113. https://doi.org/10.1016/j.neuroimage.2007.07.007

    Article  PubMed  Google Scholar 

  7. Ashburner J (2015) VBM tutorial

  8. Bashir A, Lipton RB, Ashina S, Ashina M (2013) Migraine and structural changes in the brain. Neurology 81:1260–1268. https://doi.org/10.1212/WNL.0b013e3182a6cb32

    Article  PubMed  PubMed Central  Google Scholar 

  9. Bermudez P, Zatorre RJ (2005) Differences in gray matter between musicians and nonmusicians. Ann N Y Acad Sci 1060:395–399. https://doi.org/10.1196/annals.1360.057

    Article  PubMed  Google Scholar 

  10. Bermudez P, Lerch JP, Evans AC, Zatorre RJ (2009) Neuroanatomical correlates of musicianship as revealed by cortical thickness and voxel-based morphometry. Cereb Cortex 19:1583–1596. https://doi.org/10.1093/cercor/bhn196

    Article  PubMed  Google Scholar 

  11. Boyke J, Driemeyer J, Gaser C et al (2008) Training-induced brain structure changes in the elderly. J Neurosci 28:7031–7035. https://doi.org/10.1523/JNEUROSCI.0742-08.2008

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. Button KS, Ioannidis JPA, Mokrysz C et al (2013) Power failure: why small sample size undermines the reliability of neuroscience. Nat Rev Neurosci 14:365–376. https://doi.org/10.1038/nrn3475

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. Caliendo M, Kopeinig S (2008) Some practical guidance for the implementation of propensity score matching. J Econ Surv 22:31–72. https://doi.org/10.1111/j.1467-6419.2007.00527.x

    Article  Google Scholar 

  14. Catani M, Mesulam M (2008) The arcuate fasciculus and the disconnection theme in language and aphasia: history and current state. Cortex 44:953–961. https://doi.org/10.1016/j.cortex.2008.04.002

    Article  PubMed  PubMed Central  Google Scholar 

  15. Cha Y-H, Lee H, Santell L, Baloh R (2009) Association of benign recurrent vertigo and migraine in 208 patients. Cephalalgia 29:550–555. https://doi.org/10.1111/j.1468-2982.2008.01770.x

    Article  PubMed  PubMed Central  Google Scholar 

  16. Chen W-T, Chou K-H, Lee P-L et al (2018) Comparison of gray matter volume between migraine and “strict-criteria” tension-type headache. J Headache Pain. https://doi.org/10.1186/s10194-018-0834-6

    Article  PubMed  PubMed Central  Google Scholar 

  17. Chételat G, Desgranges B, de la Sayette V et al (2002) Mapping gray matter loss with voxel-based morphometry in mild cognitive impairment. NeuroReport 13:1939–1943. https://doi.org/10.1097/00001756-200210280-00022

    Article  PubMed  Google Scholar 

  18. Chong CD, Dodick DW, Schlaggar BL, Schwedt TJ (2014) Atypical age-related cortical thinning in episodic migraine. Cephalalgia 34:1115–1124. https://doi.org/10.1177/0333102414531157

    Article  PubMed  Google Scholar 

  19. Cohen J (1977) Statistical power analysis for the behavioral sciences, Rev edn. Lawrence Erlbaum Associates Inc, Hillsdale

    Google Scholar 

  20. Coppola G, Tinelli E, Lepre C et al (2014) Dynamic changes in thalamic microstructure of migraine without aura patients: a diffusion tensor magnetic resonance imaging study. Eur J Neurol 21:287-e13. https://doi.org/10.1111/ene.12296

    Article  PubMed  Google Scholar 

  21. Coppola G, Di Renzo A, Tinelli E et al (2015) Evidence for brain morphometric changes during the migraine cycle: a magnetic resonance-based morphometry study. Cephalalgia Int J Headache 35:783–791. https://doi.org/10.1177/0333102414559732

    Article  Google Scholar 

  22. Dai Z, Zhong J, Xiao P et al (2015) Gray matter correlates of migraine and gender effect: a meta-analysis of voxel-based morphometry studies. Neuroscience 299:88–96. https://doi.org/10.1016/j.neuroscience.2015.04.066

    CAS  Article  PubMed  Google Scholar 

  23. Draganski B, Gaser C, Busch V et al (2004) Changes in grey matter induced by training. Nature 427:311–312. https://doi.org/10.1038/427311a

    CAS  Article  PubMed  Google Scholar 

  24. Durnez J, Degryse J, Moerkerke B et al (2016) Power and sample size calculations for fMRI studies based on the prevalence of active peaks. bioRxiv. https://doi.org/10.1101/049429

    Article  Google Scholar 

  25. Eickhoff SB, Bzdok D, Laird AR et al (2012) Activation likelihood estimation meta-analysis revisited. NeuroImage 59:2349–2361. https://doi.org/10.1016/j.neuroimage.2011.09.017

    Article  PubMed  Google Scholar 

  26. Faul F, Erdfelder E, Lang A-G, Buchner A (2007) G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 39:175–191. https://doi.org/10.3758/BF03193146

    Article  PubMed  PubMed Central  Google Scholar 

  27. Frisoni GB, Testa C, Zorzan A et al (2002) Detection of grey matter loss in mild Alzheimer’s disease with voxel based morphometry. J Neurol Neurosurg Psychiatry 73:657–664. https://doi.org/10.1136/jnnp.73.6.657

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  28. Friston K (2012) Ten ironic rules for non-statistical reviewers. NeuroImage 61:1300–1310. https://doi.org/10.1016/j.neuroimage.2012.04.018

    Article  PubMed  Google Scholar 

  29. Frye RE, Hasan K, Malmberg B et al (2010) Superior longitudinal fasciculus and cognitive dysfunction in adolescents born preterm and at term. Dev Med Child Neurol 52:760–766. https://doi.org/10.1111/j.1469-8749.2010.03633.x

    Article  PubMed  PubMed Central  Google Scholar 

  30. Gomez-Beldarrain M, Oroz I, Zapirain BG et al (2016) Right fronto-insular white matter tracts link cognitive reserve and pain in migraine patients. J Headache Pain 17:4. https://doi.org/10.1186/s10194-016-0593-1

    CAS  Article  PubMed Central  Google Scholar 

  31. Gorgolewski K, Burns CD, Madison C et al (2011) Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python. Front Neuroinform. https://doi.org/10.3389/fninf.2011.00013

    Article  PubMed  PubMed Central  Google Scholar 

  32. Granovsky Y, Shor M, Shifrin A et al (2018) Assessment of responsiveness to everyday non-noxious stimuli in pain-free migraineurs with versus without aura. J Pain Off J Am Pain Soc 19:943–951. https://doi.org/10.1016/j.jpain.2018.03.008

    Article  Google Scholar 

  33. Granziera C, DaSilva AFM, Snyder J et al (2006) Anatomical alterations of the visual motion processing network in migraine with and without aura. PLoS Med. https://doi.org/10.1371/journal.pmed.0030402

    Article  PubMed  PubMed Central  Google Scholar 

  34. Henry P, Auray JP, Gaudin AF et al (2002) Prevalence and clinical characteristics of migraine in France. Neurology 59:232–237. https://doi.org/10.1212/WNL.59.2.232

    CAS  Article  PubMed  Google Scholar 

  35. Ho D, Imai K, King G, Stuart EA (2011) MatchIt: Nonparametric Preprocessing for Parametric Causal Inference. J Stat Softw. https://doi.org/10.18637/jss.v042.i08

    Article  Google Scholar 

  36. Hooker WD, Raskin NH (1986) Neuropsychologic alterations in classic and common migraine. Arch Neurol 43:709–712. https://doi.org/10.1001/archneur.1986.00520070065020

    CAS  Article  PubMed  Google Scholar 

  37. Hu W, Guo J, Chen N et al (2015) A meta-analysis of voxel-based morphometric studies on migraine. Int J Clin Exp Med 8:4311–4319

    PubMed  PubMed Central  Google Scholar 

  38. Jia Z, Yu S (2017) Grey matter alterations in migraine: a systematic review and meta-analysis. NeuroImage Clin 14:130–140. https://doi.org/10.1016/j.nicl.2017.01.019

    Article  PubMed  PubMed Central  Google Scholar 

  39. Kara B, Atamer AK, Onat L et al (2013) DTI findings during spontaneous migraine attacks. Clin Neuroradiol 23:31–36. https://doi.org/10.1007/s00062-012-0165-y

    CAS  Article  PubMed  Google Scholar 

  40. Karas GB, Burton EJ, Rombouts SARB et al (2003) A comprehensive study of gray matter loss in patients with Alzheimer’s disease using optimized voxel-based morphometry. NeuroImage 18:895–907. https://doi.org/10.1016/S1053-8119(03)00041-7

    CAS  Article  PubMed  Google Scholar 

  41. Kim JH, Suh S-I, Seol HY et al (2008) Regional grey matter changes in patients with migraine: a voxel-based morphometry study. Cephalalgia Int J Headache 28:598–604. https://doi.org/10.1111/j.1468-2982.2008.01550.x

    CAS  Article  Google Scholar 

  42. Kosinski M, Bayliss MS, Bjorner JB et al (2003) A six-item short-form survey for measuring headache impact: The HIT-6TM. Qual Life Res 12:963–974. https://doi.org/10.1023/A:1026119331193

    CAS  Article  PubMed  Google Scholar 

  43. Lévêque Y, Masson R, Fornoni L et al (2020) Self-perceived attention difficulties are associated with sensory hypersensitivity in migraine. Rev Neurol. https://doi.org/10.1016/j.neurol.2020.01.360

    Article  PubMed  Google Scholar 

  44. Li XL, Fang YN, Gao QC et al (2011) A diffusion tensor magnetic resonance imaging study of corpus callosum from adult patients with migraine complicated with depressive/anxious disorder. Headache 51:237–245. https://doi.org/10.1111/j.1526-4610.2010.01774.x

    Article  PubMed  Google Scholar 

  45. Lim KO, Helpern JA (2002) Neuropsychiatric applications of DTI—a review. NMR Biomed 15:587–593. https://doi.org/10.1002/nbm.789

    CAS  Article  PubMed  Google Scholar 

  46. Liu J, Lan L, Li G et al (2013) Migraine-related gray matter and white matter changes at a 1-year follow-up evaluation. J Pain 14:1703–1708. https://doi.org/10.1016/j.jpain.2013.08.013

    Article  PubMed  Google Scholar 

  47. Liu J, Mu J, Chen T et al (2018) White matter tract microstructure of the mPFC-amygdala predicts interindividual differences in placebo response related to treatment in migraine patients. Hum Brain Mapp. https://doi.org/10.1002/hbm.24372

    Article  PubMed  PubMed Central  Google Scholar 

  48. Luders E, Thompson PM, Narr KL et al (2006) A curvature-based approach to estimate local gyrification on the cortical surface. NeuroImage 29:1224–1230. https://doi.org/10.1016/j.neuroimage.2005.08.049

    CAS  Article  PubMed  Google Scholar 

  49. Madhavan KM, McQueeny T, Howe SR et al (2014) Superior longitudinal fasciculus and language functioning in healthy aging. Brain Res 1562:11–22. https://doi.org/10.1016/j.brainres.2014.03.012

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  50. Magon S, May A, Stankewitz A et al (2018) Cortical abnormalities in episodic migraine: a multi-center 3T MRI study. Cephalalgia Int J Headache. https://doi.org/10.1177/0333102418795163

    Article  Google Scholar 

  51. Main A, Dowson A, Gross M (1997) Photophobia and phonophobia in migraineurs between attacks. Headache J Head Face Pain 37:492–495. https://doi.org/10.1046/j.1526-4610.1997.3708492.x

    CAS  Article  Google Scholar 

  52. Maldonado IL, Moritz-Gasser S, Duffau H (2011) Does the left superior longitudinal fascicle subserve language semantics? A brain electrostimulation study. Brain Struct Funct 216:263. https://doi.org/10.1007/s00429-011-0309-x

    Article  PubMed  Google Scholar 

  53. Makris N, Biederman J, Valera EM et al (2007) Cortical thinning of the attention and executive function networks in adults with attention-deficit/hyperactivity disorder. Cereb Cortex 17:1364–1375. https://doi.org/10.1093/cercor/bhl047

    Article  PubMed  Google Scholar 

  54. Marciszewski KK, Meylakh N, Di Pietro F et al (2018) Altered brainstem anatomy in migraine. Cephalalgia Int J Headache 38:476–486. https://doi.org/10.1177/0333102417694884

    Article  Google Scholar 

  55. Matsuo K, Nicoletti M, Nemoto K et al (2009) A voxel-based morphometry study of frontal gray matter correlates of impulsivity. Hum Brain Mapp 30:1188–1195. https://doi.org/10.1002/hbm.20588

    Article  PubMed  Google Scholar 

  56. May A (2009) Morphing voxels: the hype around structural imaging of headache patients. Brain 132:1419–1425. https://doi.org/10.1093/brain/awp116

    Article  PubMed  Google Scholar 

  57. Messina R, Rocca MA, Colombo B et al (2017) Structural brain abnormalities in patients with vestibular migraine. J Neurol 264:295–303. https://doi.org/10.1007/s00415-016-8349-z

    Article  PubMed  Google Scholar 

  58. Messina R, Rocca MA, Colombo B et al (2018) Gray matter volume modifications in migraine: a cross-sectional and longitudinal study. Neurology 91:e280–e292. https://doi.org/10.1212/WNL.0000000000005819

    Article  PubMed  Google Scholar 

  59. Mongini F, Keller R, Deregibus A et al (2005) Frontal lobe dysfunction in patients with chronic migraine: a clinical–neuropsychological study. Psychiatry Res 133:101–106. https://doi.org/10.1016/j.psychres.2003.12.028

    Article  PubMed  Google Scholar 

  60. Nagae LM, Zarnow DM, Blaskey L et al (2012) Elevated mean diffusivity in the left hemisphere superior longitudinal fasciculus in autism spectrum disorders increases with more profound language impairment. Am J Neuroradiol 33:1720–1725. https://doi.org/10.3174/ajnr.A3037

    CAS  Article  PubMed  Google Scholar 

  61. Neeb L, Bastian K, Villringer K et al (2017) Structural gray matter alterations in chronic migraine: implications for a progressive disease? Headache J Head Face Pain 57:400–416. https://doi.org/10.1111/head.13012

    Article  Google Scholar 

  62. Palm-Meinders IH, Arkink EB, Koppen H et al (2017) Volumetric brain changes in migraineurs from the general population. Neurology 89:2066–2074. https://doi.org/10.1212/WNL.0000000000004640

    Article  PubMed  PubMed Central  Google Scholar 

  63. Pell GS, Briellmann RS, Chan CH et al (2008) Selection of the control group for VBM analysis: influence of covariates, matching and sample size. NeuroImage 41:1324–1335. https://doi.org/10.1016/j.neuroimage.2008.02.050

    Article  PubMed  Google Scholar 

  64. Radua J, van den Heuvel OA, Surguladze S, Mataix-Cols D (2010) Meta-analytical comparison of voxel-based morphometry studies in obsessive-compulsive disorder vs other anxiety disorders. Arch Gen Psychiatry 67:701–711. https://doi.org/10.1001/archgenpsychiatry.2010.70

    Article  PubMed  Google Scholar 

  65. Radua J, Mataix-Cols D, Phillips ML et al (2012) A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps. Eur Psychiatry 27:605–611. https://doi.org/10.1016/j.eurpsy.2011.04.001

    CAS  Article  PubMed  Google Scholar 

  66. Ridgway GR, Henley SMD, Rohrer JD et al (2008) Ten simple rules for reporting voxel-based morphometry studies. NeuroImage 40:1429–1435. https://doi.org/10.1016/j.neuroimage.2008.01.003

    Article  PubMed  Google Scholar 

  67. Rocca MA, Pagani E, Colombo B et al (2008) Selective diffusion changes of the visual pathways in patients with migraine: a 3-T tractography study. Cephalalgia Int J Headache 28:1061–1068. https://doi.org/10.1111/j.1468-2982.2008.01655.x

    CAS  Article  Google Scholar 

  68. Schmahmann JD, Smith EE, Eichler FS, Filley CM (2008) Cerebral white matter. Ann N Y Acad Sci 1142:266–309. https://doi.org/10.1196/annals.1444.017

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  69. Schmitz N, Admiraal-Behloul F, Arkink EB et al (2008) Attack frequency and disease duration as indicators for brain damage in migraine. Headache J Head Face Pain 48:1044–1055. https://doi.org/10.1111/j.1526-4610.2008.01133.x

    Article  Google Scholar 

  70. Sheng L, Zhao P, Ma H et al (2020) A lack of consistent brain grey matter alterations in migraine. Brain J Neurol. https://doi.org/10.1093/brain/awaa123

    Article  Google Scholar 

  71. Shibata Y, Ishiyama S, Matsushita A (2018) White matter diffusion abnormalities in migraine and medication overuse headache: a 1.5-T tract-based spatial statistics study. Clin Neurol Neurosurg 174:167–173. https://doi.org/10.1016/j.clineuro.2018.09.022

    Article  PubMed  Google Scholar 

  72. Silani G, Frith U, Demonet J-F et al (2005) Brain abnormalities underlying altered activation in dyslexia: a voxel based morphometry study. Brain 128:2453–2461. https://doi.org/10.1093/brain/awh579

    CAS  Article  PubMed  Google Scholar 

  73. Smith SM, Nichols TE (2009) Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. NeuroImage 44:83–98. https://doi.org/10.1016/j.neuroimage.2008.03.061

    Article  Google Scholar 

  74. Smith SM, Jenkinson M, Woolrich MW et al (2004) Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 23(Suppl 1):S208–S219. https://doi.org/10.1016/j.neuroimage.2004.07.051

    Article  Google Scholar 

  75. Spena G, Gatignol P, Capelle L, Duffau H (2006) Superior longitudinal fasciculus subserves vestibular network in humans. NeuroReport 17:1403. https://doi.org/10.1097/01.wnr.0000223385.49919.61

    Article  PubMed  Google Scholar 

  76. Stewart WF, Lipton RB, Whyte J et al (1999) An international study to assess reliability of the Migraine Disability Assessment (MIDAS) score. Neurology 53:988–994. https://doi.org/10.1212/wnl.53.5.988

    CAS  Article  PubMed  Google Scholar 

  77. Szabó N, Faragó P, Király A et al (2017) Evidence for plastic processes in migraine with aura: a diffusion weighted MRI study. Front Neuroanat 11:138. https://doi.org/10.3389/fnana.2017.00138

    Article  PubMed  Google Scholar 

  78. Thornton A, Lee P (2000) Publication bias in meta-analysis: its causes and consequences. J Clin Epidemiol 53:207–216. https://doi.org/10.1016/S0895-4356(99)00161-4

    CAS  Article  PubMed  Google Scholar 

  79. Valente AA, Miguel EC, Castro CC et al (2005) Regional gray matter abnormalities in obsessive-compulsive disorder: a voxel-based morphometry study. Biol Psychiatry 58:479–487. https://doi.org/10.1016/j.biopsych.2005.04.021

    Article  PubMed  Google Scholar 

  80. Valfrè W, Rainero I, Bergui M, Pinessi L (2007) Voxel-based morphometry reveals gray matter abnormalities in migraine. Headache J Head Face Pain 48:109–117. https://doi.org/10.1111/j.1526-4610.2007.00723.x

    Article  Google Scholar 

  81. Vingen JV, Pareja JA, Støren O et al (1998) Phonophobia in migraine. Cephalalgia Int J Headache 18:243–249. https://doi.org/10.1111/j.1468-2982.1998.1805243.x

    CAS  Article  Google Scholar 

  82. Vuković V, Plavec D, Galinović I et al (2007) Prevalence of vertigo, dizziness, and migrainous vertigo in patients with migraine. Headache J Head Face Pain 47:1427–1435. https://doi.org/10.1111/j.1526-4610.2007.00939.x

    Article  Google Scholar 

  83. Vuralli D, Ayata C, Bolay H (2018) Cognitive dysfunction and migraine. J Headache Pain. https://doi.org/10.1186/s10194-018-0933-4

    Article  PubMed  PubMed Central  Google Scholar 

  84. Yuan K, Qin W, Liu P et al (2012) Reduced fractional anisotropy of corpus callosum modulates inter-hemispheric resting state functional connectivity in migraine patients without aura. PLoS ONE. https://doi.org/10.1371/journal.pone.0045476

    Article  PubMed  PubMed Central  Google Scholar 

  85. Zeitlin C, Oddy M (1984) Cognitive impairment in patients with severe migraine. Br J Clin Psychol 23:27–35. https://doi.org/10.1111/j.2044-8260.1984.tb00623.x

    Article  PubMed  Google Scholar 

  86. Zhang J, Wu Y-L, Su J et al (2017) Assessment of gray and white matter structural alterations in migraineurs without aura. J Headache Pain 18:74. https://doi.org/10.1186/s10194-017-0783-5

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The acquisition of imaging data was performed at the CERMEP imaging center in Lyon, we thank Frank Lamberton for his technical assistance. We thank Hesham ElShafei and Lesly Fornoni for their help in recruiting the participants.

Funding

This work was supported by the French National Research Agency (ANR) Grant ANR-14-CE30-0001-01 (to Aurélie Bidet-Caulet and Anne Caclin). This work was performed within the framework of the LABEX CORTEX (ANR-11-LABX-0042) and the LABEX CeLyA (ANR-10-LABX-0060) of Université de Lyon, within the program “Investissements d’Avenir” (ANR-16-IDEX-0005) operated by the French ANR.

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Masson, R., Demarquay, G., Meunier, D. et al. Is Migraine Associated to Brain Anatomical Alterations? New Data and Coordinate-Based Meta-analysis. Brain Topogr (2021). https://doi.org/10.1007/s10548-021-00824-6

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Keywords

  • Migraine
  • Voxel-based morphometry
  • Surface-based morphometry
  • Diffusion tensor imaging
  • Tract-based spatial statistics
  • Coordinate-based meta-analysis