Advertisement

The Cerebellum

, Volume 14, Issue 3, pp 364–374 | Cite as

The Role of the Cerebellum in Multiple Sclerosis

  • Katrin WeierEmail author
  • Brenda Banwell
  • Antonio Cerasa
  • D. Louis Collins
  • Anne-Marie Dogonowski
  • Hans Lassmann
  • Aldo Quattrone
  • Mohammad A. Sahraian
  • Hartwig R. Siebner
  • Till Sprenger
Consensus paper

Abstract

In multiple sclerosis (MS), cerebellar signs and symptoms as well as cognitive dysfunction are frequent and contribute to clinical disability with only poor response to symptomatic treatment. The current consensus paper highlights the broad range of clinical signs and symptoms of MS patients, which relate to cerebellar dysfunction. There is considerable evidence of cerebellar involvement in MS based on clinical, histopathological as well as structural and functional magnetic resonance imaging (MRI) studies. The review of the recent literature, however, also demonstrates a high variability of results. These discrepancies are, at least partially, caused by the use of different techniques and substantial heterogeneity among the patient cohorts in terms of disease duration, number of patients, and progressive vs. relapsing disease courses. Moreover, the majority of studies were cross-sectional, providing little insight into the dynamics of cerebellar involvement in MS. Some links between the histopathological changes, the structural and functional abnormalities as captured by MRI, cerebellar dysfunction, and the clinical consequences are starting to emerge and warrant further study. A consensus is formed that this line of research will benefit from advances in neuroimaging techniques that allow to trace cerebellar involvement at higher resolution. Using a prospective study design, multimodal high-resolution cerebellar imaging is highly promising, particularly in patients who present with radiologically or clinically isolated syndromes or newly diagnosed MS.

Keywords

Multiple sclerosis Cerebellum Cognition Magnetic resonance imaging Demyelination 

Notes

Conflict of Interest Statement

K.W. received funding from the Swiss National Science Foundation (PBSKP3_145838). Dr. Weier reports no conflict of interest.

B.B. serves as a consultant to Novartis, Sanofi-Aventis, and Biogen Idec. She is a senior editor of Multiple Sclerosis and Related Disorders.

A.C. reports no conflict of interest.

D.L.C discloses consulting for NeuroRx. He is co-founder of True Positive Medical Devices Inc.

A.M.D. has received speaker’s fee from Biogen Idec and Merck-Serono and congress fee to ECTRIMS 2010 covered by Merck-Serono, Denmark.

H.L. reports no conflict of interest

A.Q. reports no conflict of interest.

M.A.S. reports that he has received travel grants to different congresses and symposiums from Biogen Idec, Biologix, Novartis, Merck-Serono, and Cinnagen and also received research supports from Iranian MS Society, Cinnagen, Merck-Serono, and Novartis Iran.

H.S. has received honoraria as speaker from Lundbeck A/S, Valby, Denmark, Biogen Idec, Denmark A/S, Genzyme, Denmark and Merck-Serono, Denmark, honoraria as editor from Elsevier Publishers, Amsterdam, The Netherlands and Springer Publishing, Stuttgart, Germany, and travel support from MagVenture, Denmark.

T.S. has received no personal compensation for consultancy activities. His employer, the University Hospital Basel, received compensation for him serving on scientific advisory boards from Novartis, ATI, Allergan, Teva, Genzyme, and Biogen Idec. He has received research support from Novartis Switzerland, EFIC, and the Swiss MS Society.

References

  1. 1.
    Reynolds R, Roncaroli F, Nicholas R, Radotra B, Gveric D, Howell O. The neuropathological basis of clinical progression in multiple sclerosis. Acta Neuropathol. 2011;122(2):155–70.CrossRefPubMedGoogle Scholar
  2. 2.
    Miller DH, Barkhof F, Frank JA, Parker GJ, Thompson AJ. Measurement of atrophy in multiple sclerosis: pathological basis, methodological aspects and clinical relevance. Brain. 2002;125(Pt 8):1676–95.CrossRefPubMedGoogle Scholar
  3. 3.
    Fisher E, Rudick RA, Simon JH, Cutter G, Baier M, Lee JC, et al. Eight-year follow-up study of brain atrophy in patients with MS. Neurology. 2002;59(9):1412–20.CrossRefPubMedGoogle Scholar
  4. 4.
    Geurts JJ, Calabrese M, Fisher E, Rudick RA. Measurement and clinical effect of grey matter pathology in multiple sclerosis. Lancet Neurol. 2012;11(12):1082–92.CrossRefPubMedGoogle Scholar
  5. 5.
    Lassmann H, Bruck W, Lucchinetti CF. The immunopathology of multiple sclerosis: an overview. Brain Pathol. 2007;17(2):210–8.CrossRefPubMedGoogle Scholar
  6. 6.
    De Stefano N, Airas L, Grigoriadis N, Mattle HP, O’Riordan J, Oreja-Guevara C, et al. Clinical relevance of brain volume measures in multiple sclerosis. CNS drugs. 2014;28(2):147–56.CrossRefPubMedGoogle Scholar
  7. 7.
    Dobbing J, Sands J. Quantitative growth and development of human brain. Arch Dis Child. 1973;48(10):757–67.CrossRefPubMedCentralPubMedGoogle Scholar
  8. 8.
    Eriksson M, Andersen O, Runmarker B. Long-term follow up of patients with clinically isolated syndromes, relapsing–remitting and secondary progressive multiple sclerosis. Mult Scler. 2003;9(3):260–74.CrossRefPubMedGoogle Scholar
  9. 9.
    Miller DH, Hornabrook RW, Purdie G. The natural history of multiple sclerosis: a regional study with some longitudinal data. J Neurol Neurosurg Psychiatry. 1992;55(5):341–6.CrossRefPubMedCentralPubMedGoogle Scholar
  10. 10.
    Ghassemi R, Narayanan S, Banwell B, Sled JG, Shroff M, Arnold DL, et al. Quantitative determination of regional lesion volume and distribution in children and adults with relapsing–remitting multiple sclerosis. PLoS One. 2014;9(2):e85741.CrossRefPubMedCentralPubMedGoogle Scholar
  11. 11.
    Lublin FD, Reingold SC. Defining the clinical course of multiple sclerosis: results of an international survey. National Multiple Sclerosis Society (USA) Advisory Committee on Clinical Trials of New Agents in Multiple Sclerosis. Neurology. 1996;46(4):907–11.CrossRefPubMedGoogle Scholar
  12. 12.
    Scalfari A, Neuhaus A, Daumer M, Ebers GC, Muraro PA. Age and disability accumulation in multiple sclerosis. Neurology. 2011;77(13):1246–52.CrossRefPubMedCentralPubMedGoogle Scholar
  13. 13.
    Kutzelnigg A, Lucchinetti CF, Stadelmann C, Bruck W, Rauschka H, Bergmann M, et al. Cortical demyelination and diffuse white matter injury in multiple sclerosis. Brain. 2005;128(Pt 11):2705–12.CrossRefPubMedGoogle Scholar
  14. 14.
    Lassmann H, van Horssen J, Mahad D. Progressive multiple sclerosis: pathology and pathogenesis. Nat Rev Neurol. 2012;8(11):647–56.CrossRefPubMedGoogle Scholar
  15. 15.
    Lumsden CE. The neuropathology of multiple sclerosis. In: Vinken PI, Bruyn GW, editors. Handbook of clinical neurology. 9. New York: Elsevier; 1970. p. 217–309.Google Scholar
  16. 16.
    Peterson JW, Bo L, Mork S, Chang A, Trapp BD. Transected neurites, apoptotic neurons, and reduced inflammation in cortical multiple sclerosis lesions. Ann Neurol. 2001;50(3):389–400.CrossRefPubMedGoogle Scholar
  17. 17.
    Choi SR, Howell OW, Carassiti D, Magliozzi R, Gveric D, Muraro PA, et al. Meningeal inflammation plays a role in the pathology of primary progressive multiple sclerosis. Brain. 2012;135(Pt 10):2925–37.CrossRefPubMedGoogle Scholar
  18. 18.
    Howell OW, Reeves CA, Nicholas R, Carassiti D, Radotra B, Gentleman SM, et al. Meningeal inflammation is widespread and linked to cortical pathology in multiple sclerosis. Brain. 2011;134(Pt 9):2755–71.CrossRefPubMedGoogle Scholar
  19. 19.
    Kutzelnigg A, Faber-Rod JC, Bauer J, Lucchinetti CF, Sorensen PS, Laursen H, et al. Widespread demyelination in the cerebellar cortex in multiple sclerosis. Brain Pathol. 2007;17(1):38–44.CrossRefPubMedGoogle Scholar
  20. 20.
    Merkler D, Klinker F, Jurgens T, Glaser R, Paulus W, Brinkmann BG, et al. Propagation of spreading depression inversely correlates with cortical myelin content. Ann Neurol. 2009;66(3):355–65.CrossRefPubMedGoogle Scholar
  21. 21.
    Poser CM, Brinar VV. Diagnostic criteria for multiple sclerosis. Clin Neurol Neurosurg. 2001;103(1):1–11.CrossRefPubMedGoogle Scholar
  22. 22.
    Rot U, Ledinek AH, Jazbec SS. Clinical, magnetic resonance imaging, cerebrospinal fluid and electrophysiological characteristics of the earliest multiple sclerosis. Clin Neurol Neurosurg. 2008;110(3):233–8.CrossRefPubMedGoogle Scholar
  23. 23.
    Weinshenker BG, Issa M, Baskerville J. Long-term and short-term outcome of multiple sclerosis: a 3-year follow-up study. Arch Neurol. 1996;53(4):353–8.CrossRefPubMedGoogle Scholar
  24. 24.
    Amato MP, Ponziani G. A prospective study on the prognosis of multiple sclerosis. Neurol Sci. 2000;21(4 Suppl 2):S831–8.CrossRefPubMedGoogle Scholar
  25. 25.
    Alusi SH, Glickman S, Aziz TZ, Bain PG. Tremor in multiple sclerosis. J Neurol Neurosurg Psychiatry. 1999;66(2):131–4.CrossRefPubMedCentralPubMedGoogle Scholar
  26. 26.
    Proudlock FA, Gottlob I, Constantinescu CS. Oscillopsia without nystagmus caused by head titubation in a patient with multiple sclerosis. J neuro-ophthalmol : J North Am Neuro-Ophthalmol Soc. 2002;22(2):88–91.CrossRefGoogle Scholar
  27. 27.
    Weinshenker BG, Rice GP, Noseworthy JH, Carriere W, Baskerville J, Ebers GC. The natural history of multiple sclerosis: a geographically based study. 3. Multivariate analysis of predictive factors and models of outcome. Brain. 1991 Apr;114 (Pt 2):1045–56.Google Scholar
  28. 28.
    Twomey JA, Espir ML. Paroxysmal symptoms as the first manifestations of multiple sclerosis. J Neurol Neurosurg Psychiatry. 1980;43(4):296–304.CrossRefPubMedCentralPubMedGoogle Scholar
  29. 29.
    Iorio R, Capone F, Plantone D, Batocchi AP. Paroxysmal ataxia and dysarthria in multiple sclerosis. J clin neurosci : J Neurosurg Soc Australasia. 2014;21(1):174–5.CrossRefGoogle Scholar
  30. 30.
    Waxman SG. Cerebellar dysfunction in multiple sclerosis: evidence for an acquired channelopathy. Prog Brain Res. 2005;148:353–65.PubMedGoogle Scholar
  31. 31.
    Grimaldi G, Manto M. Topography of cerebellar deficits in humans. Cerebellum. 2012;11(2):336–51.CrossRefPubMedGoogle Scholar
  32. 32.
    Manto M, Bower JM, Conforto AB, Delgado-Garcia JM, da Guarda SN, Gerwig M, et al. Consensus paper: roles of the cerebellum in motor control—the diversity of ideas on cerebellar involvement in movement. Cerebellum. 2012;11(2):457–87.CrossRefPubMedCentralPubMedGoogle Scholar
  33. 33.
    Schmahmann JD, Sherman JC. The cerebellar cognitive affective syndrome. Brain. 1998;121(Pt 4):561–79.CrossRefPubMedGoogle Scholar
  34. 34.
    Tedesco AM, Chiricozzi FR, Clausi S, Lupo M, Molinari M, Leggio MG. The cerebellar cognitive profile. Brain. 2011;134(Pt 12):3672–86.CrossRefPubMedGoogle Scholar
  35. 35.
    Stoodley CJ, Schmahmann JD. Evidence for topographic organization in the cerebellum of motor control versus cognitive and affective processing. Cortex. 2010 Jul–Aug;46(7):831–44.Google Scholar
  36. 36.
    Habas C, Kamdar N, Nguyen D, Prater K, Beckmann CF, Menon V, et al. Distinct cerebellar contributions to intrinsic connectivity networks. J Neurosci : Off J Soc Neurosci. 2009;29(26):8586–94.CrossRefGoogle Scholar
  37. 37.
    Middleton FA, Strick PL. Basal ganglia and cerebellar loops: motor and cognitive circuits. Brain Res Brain Res Rev. 2000;31(2–3):236–50.CrossRefPubMedGoogle Scholar
  38. 38.
    Bobholz JA, Rao SM. Cognitive dysfunction in multiple sclerosis: a review of recent developments. Curr Opin Neurol. 2003;16(3):283–8.CrossRefPubMedGoogle Scholar
  39. 39.
    Valentino P, Cerasa A, Chiriaco C, Nistico R, Pirritano D, Gioia M, et al. Cognitive deficits in multiple sclerosis patients with cerebellar symptoms. Mult Scler. 2009;15(7):854–9.CrossRefPubMedGoogle Scholar
  40. 40.
    Weier K, Penner IK, Magon S, Amann M, Naegelin Y, Andelova M, et al. Cerebellar abnormalities contribute to disability including cognitive impairment in multiple sclerosis. PLoS one. 2014;9(1):e86916.CrossRefPubMedCentralPubMedGoogle Scholar
  41. 41.
    Cerasa A, Passamonti L, Valentino P, Nistico R, Pirritano D, Gioia MC, et al. Cerebellar-parietal dysfunctions in multiple sclerosis patients with cerebellar signs. Exp Neurol. 2012;237(2):418–26.CrossRefPubMedGoogle Scholar
  42. 42.
    Cerasa A, Valentino P, Chiriaco C, Pirritano D, Nistico R, Gioia CM, et al. MR imaging and cognitive correlates of relapsing–remitting multiple sclerosis patients with cerebellar symptoms. J Neurol. 2013;260(5):1358–66.CrossRefPubMedGoogle Scholar
  43. 43.
    Clausi S, Bozzali M, Leggio MG, Di Paola M, Hagberg GE, Caltagirone C, et al. Quantification of gray matter changes in the cerebral cortex after isolated cerebellar damage: a voxel-based morphometry study. Neuroscience. 2009;162(3):827–35.CrossRefPubMedGoogle Scholar
  44. 44.
    Kolasinski J, Stagg CJ, Chance SA, Deluca GC, Esiri MM, Chang EH, et al. A combined post-mortem magnetic resonance imaging and quantitative histological study of multiple sclerosis pathology. Brain. 2012;135(Pt 10):2938–51.CrossRefPubMedCentralPubMedGoogle Scholar
  45. 45.
    Lassmann H. Cortical lesions in multiple sclerosis: inflammation versus neurodegeneration. Brain. 2012;135(Pt 10):2904–5.CrossRefPubMedGoogle Scholar
  46. 46.
    Cerasa A, Gioia MC, Valentino P, Nistico R, Chiriaco C, Pirritano D, et al. Computer-assisted cognitive rehabilitation of attention deficits for multiple sclerosis: a randomized trial with fMRI correlates. Neurorehabil Neural Repair. 2013;27(4):284–95.CrossRefPubMedGoogle Scholar
  47. 47.
    Barwood CH, Murdoch BE, Whelan BM, Lloyd D, Riek S, JD OS, et al. Improved language performance subsequent to low-frequency rTMS in patients with chronic non-fluent aphasia post-stroke. European J neurol : Off J European Federation Neurol Soc. 2011;18(7):935–43.CrossRefGoogle Scholar
  48. 48.
    Barkhof F, Filippi M, Miller DH, Scheltens P, Campi A, Polman CH, et al. Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis. Brain. 1997;120(Pt 11):2059–69.CrossRefPubMedGoogle Scholar
  49. 49.
    Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. 2011;69(2):292–302.CrossRefPubMedCentralPubMedGoogle Scholar
  50. 50.
    Montalban X, Tintore M, Swanton J, Barkhof F, Fazekas F, Filippi M, et al. MRI criteria for MS in patients with clinically isolated syndromes. Neurology. 2010;74(5):427–34.CrossRefPubMedGoogle Scholar
  51. 51.
    Baumhefner RW, Tourtellotte WW, Syndulko K, Waluch V, Ellison GW, Meyers LW, et al. Quantitative multiple sclerosis plaque assessment with magnetic resonance imaging. Its correlation with clinical parameters, evoked potentials, and intra-blood–brain barrier IgG synthesis. Arch Neurol. 1990;47(1):19–26.CrossRefPubMedGoogle Scholar
  52. 52.
    Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983;33(11):1444–52.CrossRefPubMedGoogle Scholar
  53. 53.
    Davie CA, Barker GJ, Webb S, Tofts PS, Thompson AJ, Harding AE, et al. Persistent functional deficit in multiple sclerosis and autosomal dominant cerebellar ataxia is associated with axon loss. Brain. 1995;118(Pt 6):1583–92.CrossRefPubMedGoogle Scholar
  54. 54.
    Freedman MS, Comi G, De Stefano N, Barkhof F, Polman CH, Uitdehaag BMJ, et al. Moving toward earlier treatment of multiple sclerosis: findings from a decade of clinical trials and implications for clinical practice. Multiple Sclerosis Rel Dis. 2014;3(2):147–55.CrossRefGoogle Scholar
  55. 55.
    Bermel RA, Bakshi R. The measurement and clinical relevance of brain atrophy in multiple sclerosis. Lancet Neurol. 2006;5(2):158–70.CrossRefPubMedGoogle Scholar
  56. 56.
    Weier K, Fonov V, Lavoie K, Doyon J, Collins DL. Rapid automatic segmentation of the human cerebellum and its lobules (RASCAL)—implementation and application of the patch-based label-fusion technique with a template library to segment the human cerebellum. Hum Brain Mapp. 2014;28.Google Scholar
  57. 57.
    Park MT, Pipitone J, Baer LH, Winterburn JL, Shah Y, Chavez S, et al. Derivation of high-resolution MRI atlases of the human cerebellum at 3T and segmentation using multiple automatically generated templates. Neuroimage. 2014;95:217–31.CrossRefPubMedGoogle Scholar
  58. 58.
    Tjoa CW, Benedict RH, Weinstock-Guttman B, Fabiano AJ, Bakshi R. MRI T2 hypointensity of the dentate nucleus is related to ambulatory impairment in multiple sclerosis. J Neurol Sci. 2005;234(1–2):17–24.CrossRefPubMedGoogle Scholar
  59. 59.
    Maschke M, Weber J, Dimitrova A, Bonnet U, Bohrenkamper J, Sturm S, et al. Age-related changes of the dentate nuclei in normal adults as revealed by 3D fast low angle shot (FLASH) echo sequence magnetic resonance imaging. J Neurol. 2004;251(6):740–6.CrossRefPubMedGoogle Scholar
  60. 60.
    Roccatagliata L, Vuolo L, Bonzano L, Pichiecchio A, Mancardi GL. Multiple sclerosis: hyperintense dentate nucleus on unenhanced T1-weighted MR images is associated with the secondary progressive subtype. Radiology. 2009;251(2):503–10.CrossRefPubMedGoogle Scholar
  61. 61.
    Anderson VM, Fisniku LK, Altmann DR, Thompson AJ, Miller DH. MRI measures show significant cerebellar gray matter volume loss in multiple sclerosis and are associated with cerebellar dysfunction. Mult Scler. 2009;15(7):811–7.CrossRefPubMedGoogle Scholar
  62. 62.
    Weier K, Beck A, Magon S, Amann M, Naegelin Y, Penner IK, et al. Evaluation of a new approach for semi-automatic segmentation of the cerebellum in patients with multiple sclerosis. J Neurol. 2012;259(12):2673–80.CrossRefPubMedGoogle Scholar
  63. 63.
    Calabrese M, Mattisi I, Rinaldi F, Favaretto A, Atzori M, Bernardi V, et al. Magnetic resonance evidence of cerebellar cortical pathology in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2010;81(4):401–4.CrossRefPubMedGoogle Scholar
  64. 64.
    Ramasamy DP, Benedict RH, Cox JL, Fritz D, Abdelrahman N, Hussein S, et al. Extent of cerebellum, subcortical and cortical atrophy in patients with MS: a case–control study. J Neurol Sci. 2009;282(1–2):47–54.CrossRefPubMedGoogle Scholar
  65. 65.
    Mesaros S, Rovaris M, Pagani E, Pulizzi A, Caputo D, Ghezzi A, et al. A magnetic resonance imaging voxel-based morphometry study of regional gray matter atrophy in patients with benign multiple sclerosis. Arch Neurol. 2008;65(9):1223–30.CrossRefPubMedGoogle Scholar
  66. 66.
    Henry RG, Shieh M, Okuda DT, Evangelista A, Gorno-Tempini ML, Pelletier D. Regional grey matter atrophy in clinically isolated syndromes at presentation. J Neurol Neurosurg Psychiatry. 2008;79(11):1236–44.CrossRefPubMedGoogle Scholar
  67. 67.
    Damasceno A, Damasceno BP, Cendes F. The clinical impact of cerebellar grey matter pathology in multiple sclerosis. PLoS One. 2014;9(5):e96193.CrossRefPubMedCentralPubMedGoogle Scholar
  68. 68.
    Anderson VM, Wheeler-Kingshott CA, Abdel-Aziz K, Miller DH, Toosy A, Thompson AJ, et al. A comprehensive assessment of cerebellar damage in multiple sclerosis using diffusion tractography and volumetric analysis. Mult Scler. 2011;17(9):1079–87.CrossRefPubMedCentralPubMedGoogle Scholar
  69. 69.
    Prosperini L, Sbardella E, Raz E, Cercignani M, Tona F, Bozzali M, et al. Multiple sclerosis: white and gray matter damage associated with balance deficit detected at static posturography. Radiology. 2013;268(1):181–9.CrossRefPubMedGoogle Scholar
  70. 70.
    Preziosa P, Rocca MA, Mesaros S, Pagani E, Drulovic J, Stosic-Opincal T, et al. Relationship between damage to the cerebellar peduncles and clinical disability in multiple sclerosis. Radiology. 2014;271(3):822–30.CrossRefPubMedGoogle Scholar
  71. 71.
    Bozzali M, Spano B, Parker GJ, Giulietti G, Castelli M, Basile B, et al. Anatomical brain connectivity can assess cognitive dysfunction in multiple sclerosis. Mult Scler. 2013;19(9):1161–8.CrossRefPubMedGoogle Scholar
  72. 72.
    Dogonowski AM, Andersen KW, Madsen KH, Sorensen PS, Paulson OB, Blinkenberg M, et al. Multiple sclerosis impairs regional functional connectivity in the cerebellum. Neuro Image Clin. 2013;4:130–8.Google Scholar
  73. 73.
    Saini S, DeStefano N, Smith S, Guidi L, Amato MP, Federico A, et al. Altered cerebellar functional connectivity mediates potential adaptive plasticity in patients with multiple sclerosis. J Neurol Neurosurg Psychiatry. 2004;75(6):840–6.CrossRefPubMedCentralPubMedGoogle Scholar
  74. 74.
    Rocca MA, Bonnet MC, Meani A, Valsasina P, Colombo B, Comi G, et al. Differential cerebellar functional interactions during an interference task across multiple sclerosis phenotypes. Radiology. 2012;265(3):864–73.CrossRefPubMedGoogle Scholar
  75. 75.
    Rocca MA, Absinta M, Valsasina P, Ciccarelli O, Marino S, Rovira A, et al. Abnormal connectivity of the sensorimotor network in patients with MS: a multicenter fMRI study. Hum Brain Mapp. 2009;30(8):2412–25.CrossRefPubMedGoogle Scholar
  76. 76.
    Rocca MA, Pagani E, Absinta M, Valsasina P, Falini A, Scotti G, et al. Altered functional and structural connectivities in patients with MS: a 3-T study. Neurology. 2007;69(23):2136–45.CrossRefPubMedGoogle Scholar
  77. 77.
    Loitfelder M, Filippi M, Rocca M, Valsasina P, Ropele S, Jehna M, et al. Abnormalities of resting state functional connectivity are related to sustained attention deficits in MS. PLoS one. 2012;7(8):e42862.CrossRefPubMedCentralPubMedGoogle Scholar
  78. 78.
    Renoux C, Vukusic S, Mikaeloff Y, Edan G, Clanet M, Dubois B, et al. Natural history of multiple sclerosis with childhood onset. N Engl J Med. 2007;356(25):2603–13.CrossRefPubMedGoogle Scholar
  79. 79.
    Verhey LH, Shroff M, Banwell B. Pediatric multiple sclerosis: pathobiological, clinical, and magnetic resonance imaging features. Neuroimaging Clin N Am. 2013;23(2):227–43.CrossRefPubMedGoogle Scholar
  80. 80.
    Banwell B, Ghezzi A, Bar-Or A, Mikaeloff Y, Tardieu M. Multiple sclerosis in children: clinical diagnosis, therapeutic strategies, and future directions. Lancet Neurol. 2007;6(10):887–902.CrossRefPubMedGoogle Scholar
  81. 81.
    Chitnis T. Paediatric MS, is the same disease as adult MS: no. Mult Scler. 2013;19(10):1255–6.CrossRefPubMedGoogle Scholar
  82. 82.
    Trojano M, Paolicelli D, Bellacosa A, Fuiani A, Cataldi S, Di Monte E. Atypical forms of multiple sclerosis or different phases of a same disease? Neurol Sci. 2004;25 Suppl 4:S323–5.CrossRefPubMedGoogle Scholar
  83. 83.
    Gorman MP, Healy BC, Polgar-Turcsanyi M, Chitnis T. Increased relapse rate in pediatric-onset compared with adult-onset multiple sclerosis. Arch Neurol. 2009;66(1):54–9.CrossRefPubMedGoogle Scholar
  84. 84.
    Huppke B, Ellenberger D, Rosewich H, Friede T, Gartner J, Huppke P. Clinical presentation of pediatric multiple sclerosis before puberty. European J Neurol : J European Federation of Neurol Soc. 2014;21(3):441–6.CrossRefGoogle Scholar
  85. 85.
    Fay AJ, Mowry EM, Strober J, Waubant E. Relapse severity and recovery in early pediatric multiple sclerosis. Mult Scler. 2012;18(7):1008–12.CrossRefPubMedGoogle Scholar
  86. 86.
    Koziol LF, Budding D, Andreasen N, D’Arrigo S, Bulgheroni S, Imamizu H, et al. Consensus paper: the cerebellum’s role in movement and cognition. Cerebellum. 2014;13(1):151–77.CrossRefPubMedCentralPubMedGoogle Scholar
  87. 87.
    Amato MP, Goretti B, Ghezzi A, Lori S, Zipoli V, Moiola L, et al. Cognitive and psychosocial features in childhood and juvenile MS: two-year follow-up. Neurology. 2010;75(13):1134–40.CrossRefPubMedGoogle Scholar
  88. 88.
    Till C, Ghassemi R, Aubert-Broche B, Kerbrat A, Collins DL, Narayanan S, et al. MRI correlates of cognitive impairment in childhood-onset multiple sclerosis. Neuropsychology. 2011;25(3):319–32.CrossRefPubMedGoogle Scholar
  89. 89.
    Waubant E, Chabas D, Okuda DT, Glenn O, Mowry E, Henry RG, et al. Difference in disease burden and activity in pediatric patients on brain magnetic resonance imaging at time of multiple sclerosis onset vs adults. Arch Neurol. 2009;66(8):967–71.CrossRefPubMedGoogle Scholar
  90. 90.
    Rocca MA, Valsasina P, Absinta M, Moiola L, Ghezzi A, Veggiotti P, et al. Intranetwork and internetwork functional connectivity abnormalities in pediatric multiple sclerosis. Hum Brain Mapp. 2014 Feb 7.Google Scholar
  91. 91.
    Wedeen VJ, Wang RP, Schmahmann JD, Benner T, Tseng WY, Dai G, et al. Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers. Neuroimage. 2008;41(4):1267–77.CrossRefPubMedGoogle Scholar
  92. 92.
    Granziera C, Schmahmann JD, Hadjikhani N, Meyer H, Meuli R, Wedeen V, et al. Diffusion spectrum imaging shows the structural basis of functional cerebellar circuits in the human cerebellum in vivo. PLoS One. 2009;4(4):e5101.CrossRefPubMedCentralPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Katrin Weier
    • 1
    • 2
    Email author
  • Brenda Banwell
    • 3
  • Antonio Cerasa
    • 4
  • D. Louis Collins
    • 1
    • 5
  • Anne-Marie Dogonowski
    • 6
  • Hans Lassmann
    • 7
  • Aldo Quattrone
    • 8
  • Mohammad A. Sahraian
    • 9
  • Hartwig R. Siebner
    • 10
  • Till Sprenger
    • 2
    • 11
  1. 1.McConnell Brain Imaging Center, Montreal Neurological Hospital and InstituteMcGill UniversityMontrealCanada
  2. 2.Department of NeurologyUniversity Hospital BaselBaselSwitzerland
  3. 3.Children’s Hospital of PhiladelphiaUniversity of PennsylvaniaPhiladelphiaUSA
  4. 4.IBFM, National Research CouncilCatanzaroItaly
  5. 5.Department of Biomedical EngineeringMcGill UniversityMontrealCanada
  6. 6.Danish Research Center for Magnetic ResonanceCopenhagen University Hospital HvidovreHvidovreDenmark
  7. 7.Center for Brain ResearchMedical University of ViennaViennaAustria
  8. 8.Institute of NeurologyUniversity “Magna Graecia”, GermanetoGermanetoItaly
  9. 9.MS Research Center, Neuroscience InstituteTehran University of Medical SciencesTehranIran
  10. 10.Department of NeurologyCopenhagen University Hospital BispebjergCopenhagenDenmark
  11. 11.Medical Image Analysis Center (MIAC) AGUniversity Hospital BaselBaselSwitzerland

Personalised recommendations