Journal of Neurology

, Volume 265, Issue 6, pp 1393–1401 | Cite as

Effects of motor rehabilitation on mobility and brain plasticity in multiple sclerosis: a structural and functional MRI study

  • Eleonora Tavazzi
  • Niels Bergsland
  • Davide Cattaneo
  • Elisa Gervasoni
  • Maria Marcella Laganà
  • Ottavia Dipasquale
  • Cristina Grosso
  • Francesca Lea Saibene
  • Francesca Baglio
  • Marco Rovaris
Original Communication



Rehabilitation seems to promote brain plasticity, but objective measures of efficacy are lacking and there is a limited understanding of the mechanisms underlying functional recovery.


To study functional and structural brain changes induced by gait rehabilitation.


We enrolled MS inpatients (EDSS 4.5–6.5) undergoing a 4-week neurorehabilitation. Several clinical measures were obtained, including: 2-min walk test (2MWT), dynamic gait index (DGI), Berg balance scale (BBS). Furthermore, motor-task functional MRI (fMRI) of plantar dorsiflexion, resting state fMRI, and regional diffusion tensor imaging (DTI) metrics were obtained. All the assessments were performed at baseline (T0), after the end of the rehabilitation period (T1) and 3 months later (T2).


Twenty-nine patients were enrolled at T0, 26 at T1, and 16 completed all timepoints. At T1, there was a significant improvement of 2MWT, DGI, and BBS scores, along with a reduced extent of the widespread activation related to the motor task at the fMRI and an increased functional connectivity in the precentral and post-central gyrus, bilaterally. None of these changes were maintained at T2.


Our findings show a short-term beneficial effect of motor rehabilitation on gait performances in MS, accompanied by brain functional reorganization in the sensory-motor network.


Multiple sclerosis Rehabilitation Plasticity fMRI DTI 



This study was supported by a grant from Fondazione Italiana Sclerosi Multipla (FISM) (Grant # 2013/R/26).

Compliance with ethical standards

Conflicts of interest

All authors report no disclosures.

Ethical statement

The study has been approved by the local ethics committee and has, therefore, been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.

Informed consent

All the subjects recruited in the study gave their written informed consent prior to their inclusion in the study.

Supplementary material

415_2018_8859_MOESM1_ESM.docx (15 kb)
Supplementary material 1 (DOCX 14 kb)


  1. 1.
    Ontaneda D, Thompson AJ, Fox RJ, Cohen JA (2017) Progressive multiple sclerosis: prospects for disease therapy, repair, and restoration of function. Lancet 389(10076):1357–1366CrossRefPubMedGoogle Scholar
  2. 2.
    Khan F, Turner-Stokes L, Ng L, Kilpatrick T (2007) Multidisciplinary rehabilitation for adults with multiple sclerosis. Cochrane Database Syst Rev 2:CD006036Google Scholar
  3. 3.
    Motl RW, Sandroff BM, Kwakkel G, Dalgas U, Feinstein A, Heesen C et al (2017) Exercise in patients with multiple sclerosis. Lancet Neurol. 16(10):848–856CrossRefPubMedGoogle Scholar
  4. 4.
    Reddy H, Narayanan S, Arnoutelis R, Jenkinson M, Antel J, Matthews PM et al (2000) Evidence for adaptive functional changes in the cerebral cortex with axonal injury from multiple sclerosis. Brain 123(Pt 11):2314–2320CrossRefPubMedGoogle Scholar
  5. 5.
    Lee M, Reddy H, Johansen-Berg H, Pendlebury S, Jenkinson M, Smith S et al (2000) The motor cortex shows adaptive functional changes to brain injury from multiple sclerosis. Ann Neurol 47(5):606–613CrossRefPubMedGoogle Scholar
  6. 6.
    Rocca MA, Colombo B, Falini A, Ghezzi A, Martinelli V, Scotti G et al (2005) Cortical adaptation in patients with MS: a cross-sectional functional MRI study of disease phenotypes. Lancet Neurol 4(10):618–626CrossRefPubMedGoogle Scholar
  7. 7.
    Mezzapesa DM, Rocca MA, Rodegher M, Comi G, Filippi M (2008) Functional cortical changes of the sensorimotor network are associated with clinical recovery in multiple sclerosis. Hum Brain Mapp 29(5):562–573CrossRefPubMedGoogle Scholar
  8. 8.
    Tomassini V, Matthews PM, Thompson AJ, Fuglo D, Geurts JJ, Johansen-Berg H et al (2012) Neuroplasticity and functional recovery in multiple sclerosis. Nat Rev Neurol 8(11):635–646CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Prosperini L, Piattella MC, Gianni C, Pantano P (2015) Functional and structural brain plasticity enhanced by motor and cognitive rehabilitation in multiple sclerosis. Neural Plast 2015:481574CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    De Giglio L, Tona F, De Luca F, Petsas N, Prosperini L, Bianchi V et al (2016) Multiple sclerosis: changes in thalamic resting-state functional connectivity induced by a home-based cognitive rehabilitation program. Radiology 280(1):202–211CrossRefPubMedGoogle Scholar
  11. 11.
    Chiaravalloti ND, Wylie G, Leavitt V, Deluca J (2012) Increased cerebral activation after behavioral treatment for memory deficits in MS. J Neurol 259(7):1337–1346CrossRefPubMedGoogle Scholar
  12. 12.
    Cerasa A, Gioia MC, Valentino P, Nistico R, Chiriaco C, Pirritano D et al (2013) Computer-assisted cognitive rehabilitation of attention deficits for multiple sclerosis: a randomized trial with fMRI correlates. Neurorehabil Neural Repair 27(4):284–295CrossRefPubMedGoogle Scholar
  13. 13.
    Parisi L, Rocca MA, Valsasina P, Panicari L, Mattioli F, Filippi M (2014) Cognitive rehabilitation correlates with the functional connectivity of the anterior cingulate cortex in patients with multiple sclerosis. Brain Imaging Behav 8(3):387–393CrossRefPubMedGoogle Scholar
  14. 14.
    Parisi L, Rocca MA, Mattioli F, Copetti M, Capra R, Valsasina P et al (2014) Changes of brain resting state functional connectivity predict the persistence of cognitive rehabilitation effects in patients with multiple sclerosis. Mult Scler 20(6):686–694CrossRefPubMedGoogle Scholar
  15. 15.
    Rasova K, Prochazkova M, Tintera J, Ibrahim I, Zimova D, Stetkarova I (2015) Motor programme activating therapy influences adaptive brain functions in multiple sclerosis: clinical and MRI study. Int J Rehabil Res 38(1):49–54CrossRefPubMedGoogle Scholar
  16. 16.
    Rasova K, Krasensky J, Havrdova E, Obenberger J, Seidel Z, Dolezal O et al (2005) Is it possible to actively and purposely make use of plasticity and adaptability in the neurorehabilitation treatment of multiple sclerosis patients? A pilot project. Clin Rehabil 19(2):170–181CrossRefPubMedGoogle Scholar
  17. 17.
    Tomassini V, Johansen-Berg H, Jbabdi S, Wise RG, Pozzilli C, Palace J et al (2012) Relating brain damage to brain plasticity in patients with multiple sclerosis. Neurorehabil Neural Repair 26(6):581–593CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Ibrahim I, Tintera J, Skoch A, Jiru F, Hlustik P, Martinkova P et al (2011) Fractional anisotropy and mean diffusivity in the corpus callosum of patients with multiple sclerosis: the effect of physiotherapy. Neuroradiology 53(11):917–926CrossRefPubMedGoogle Scholar
  19. 19.
    Bonzano L, Tacchino A, Brichetto G, Roccatagliata L, Dessypris A, Feraco P et al (2014) Upper limb motor rehabilitation impacts white matter microstructure in multiple sclerosis. Neuroimage 90:107–116CrossRefPubMedGoogle Scholar
  20. 20.
    Prosperini L, Fanelli F, Petsas N, Sbardella E, Tona F, Raz E et al (2014) Multiple sclerosis: changes in microarchitecture of white matter tracts after training with a video game balance board. Radiology 273(2):529–538CrossRefPubMedGoogle Scholar
  21. 21.
    Salimi-Khorshidi G, Douaud G, Beckmann CF, Glasser MF, Griffanti L, Smith SM (2014) Automatic denoising of functional MRI data: combining independent component analysis and hierarchical fusion of classifiers. Neuroimage 90:449–468CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Filippini N, MacIntosh BJ, Hough MG, Goodwin GM, Frisoni GB, Smith SM et al (2009) Distinct patterns of brain activity in young carriers of the APOE-epsilon4 allele. Proc Natl Acad Sci USA. 106(17):7209–7214CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Bergsland N, Lagana MM, Tavazzi E, Caffini M, Tortorella P, Baglio F et al (2015) Corticospinal tract integrity is related to primary motor cortex thinning in relapsing–remitting multiple sclerosis. Mult Scler 21(14):1771–1780CrossRefPubMedGoogle Scholar
  24. 24.
    Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE et al (2006) Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31(4):1487–1505CrossRefPubMedGoogle Scholar
  25. 25.
    Rocca MA, Gavazzi C, Mezzapesa DM, Falini A, Colombo B, Mascalchi M et al (2003) A functional magnetic resonance imaging study of patients with secondary progressive multiple sclerosis. Neuroimage 19(4):1770–1777CrossRefPubMedGoogle Scholar
  26. 26.
    Barkhof F (2002) The clinico-radiological paradox in multiple sclerosis revisited. Curr Opin Neurol 15(3):239–245CrossRefPubMedGoogle Scholar
  27. 27.
    Filippi M, Preziosa P, Rocca MA (2017) Brain mapping in multiple sclerosis: lessons learned about the human brain. Neuroimage.
  28. 28.
    Groppo E, Baglio F, Cattaneo D, Tavazzi E, Bergsland N, Di Tella S et al (2017) Multidisciplinary rehabilitation is efficacious and induces neural plasticity in multiple sclerosis even when complicated by progressive multifocal leukoencephalopathy. Front Neurol 8:491CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Morgen K, Kadom N, Sawaki L, Tessitore A, Ohayon J, McFarland H et al (2004) Training-dependent plasticity in patients with multiple sclerosis. Brain 127(Pt 11):2506–2517CrossRefPubMedGoogle Scholar
  30. 30.
    Boutiere C, Rey C, Zaaraoui W, Le Troter A, Rico A, Crespy L et al (2017) Improvement of spasticity following intermittent theta burst stimulation in multiple sclerosis is associated with modulation of resting-state functional connectivity of the primary motor cortices. Mult Scler 23(6):855–863CrossRefPubMedGoogle Scholar
  31. 31.
    Motl RW, McAuley E, Snook EM (2005) Physical activity and multiple sclerosis: a meta-analysis. Mult Scler 11(4):459–463CrossRefPubMedGoogle Scholar
  32. 32.
    Draganski B, Gaser C, Busch V, Schuierer G, Bogdahn U, May A (2004) Neuroplasticity: changes in grey matter induced by training. Nature 427(6972):311–312CrossRefPubMedGoogle Scholar
  33. 33.
    Boyke J, Driemeyer J, Gaser C, Buchel C, May A (2008) Training-induced brain structure changes in the elderly. J Neurosci 28(28):7031–7035CrossRefPubMedGoogle Scholar
  34. 34.
    Filippi M, Ceccarelli A, Pagani E, Gatti R, Rossi A, Stefanelli L et al (2010) Motor learning in healthy humans is associated to gray matter changes: a tensor-based morphometry study. PLoS ONE 5(4):e10198CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Pardini M, Bonzano L, Bergamino M, Bommarito G, Feraco P, Murugavel A et al (2015) Cingulum bundle alterations underlie subjective fatigue in multiple sclerosis. Mult Scler 21(4):442–447CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Eleonora Tavazzi
    • 1
  • Niels Bergsland
    • 1
    • 2
  • Davide Cattaneo
    • 1
  • Elisa Gervasoni
    • 1
  • Maria Marcella Laganà
    • 1
  • Ottavia Dipasquale
    • 1
    • 3
  • Cristina Grosso
    • 1
  • Francesca Lea Saibene
    • 1
  • Francesca Baglio
    • 1
  • Marco Rovaris
    • 1
  1. 1.Scientific Institute Santa Maria Nascente, Don C. Gnocchi Foundation ONLUSMilanItaly
  2. 2.Department of Neurology, School of Medicine and Biomedical Sciences, Buffalo Neuroimaging Analysis CenterUniversity at Buffalo, State University of New YorkBuffaloUSA
  3. 3.Department of Neuroimaging, Institute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK

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