Options for Activation of Plastic and Adaptation Processes in the Central Nervous System using Physiotherapy in Multiple Sclerosis Patients
Authors:
K. Řasová 1; M. Procházková 1; I. Ibrahim 2; J. Hlinka 3,4; J. Tintěra 2
Authors‘ workplace:
Klinika rehabilitačního lékařství 3. LF UK a FN Královské Vinohrady, Praha
1; Pracoviště radiodiagnostiky a intervenční radiologie, IKEM, Praha
2; Národní ústav duševního zdraví, Klecany
3; Ústav informatiky, AV ČR, v. v. i., Praha
4
Published in:
Cesk Slov Neurol N 2017; 80/113(2): 150-156
Category:
Review Article
doi:
https://doi.org/10.14735/amcsnn2017150
Podporováno projektem PRVOUK P34, 260277/ SVV/ 2016, IKEM IN 00023001, GA13-23940.
Overview
The incidence of multiple sclerosis world-wide and in the Czech Republic continues to rise. It is one of the most common diseases that disables young people and excludes them from work as well as social life. Pharmacotherapy of this disease is insufficient to suppress progression. A comprehensive approach including physiotherapy is needed to reduce the symptoms of this disease. Current research aims to identify options for the most effective use of physiotherapy in the treatment of multiple sclerosis and is exploring the ways to actively and purposefully influence plastic and adaptive processes of the central nervous system. We discuss this theme in the present review article. We summarize the issue of neuroplasticity in general (and specifically in multiple sclerosis) and discuss the options for displaying plastic and adaptation processes (using functional magnetic resonance imaging in particular). Furthermore, we mention current physiotherapy approaches for multiple sclerosis and their potential impact on neuroplasticity. We summarize the results of our own research that monitors (via various imaging methods) the effect of the Motor Programs Activating Therapy, a new facilitation physiotherapy approach.
Key words:
physiotherapy techniques – central nervous system – neuroplasticity – functional magnetic resonance imaging – diffusion tensor imaging – multiple sclerosis – Motor programs activating therapy
The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.
The Editorial Board declares that the manuscript met the ICMJE “uniform requirements” for biomedical papers.
Sources
1. Flachenecker P. Autoimmune diseases and rehabilitation. Autoimmun Rev 2012;11(3):219– 25. doi: 10.1016/ j.autrev.2011.05.016.
2. Dalgas U, Ingemann-Hansen T, Stenager E. Physical Exercise and MS Recommendations. Int MS J 2009; 16(1):5– 11.
3. Khan F, Pallant JF, Zhang N, et al. Clinical practice improvement approach in multiple sclerosis rehabilitation: a pilot study. Int J Rehabil Res 2010;33(3):238– 47. doi: 10.1097/ MRR.0b013e328338b05f.
4. Lipp I, Tomassini V. Neuroplasticity and motor rehabilitation in multiple sclerosis. Front Neurol 2015;18(6):59. doi: 10.3389/ fneur.2015.00059.
5. Griesbach GS, Hovda DA. Cellular and molecular neuronal plasticity. Handb Clin Neurol 2015;128:681– 90. doi: 10.1016/ B978-0-444-63521-1.00042-X.
6. Waxman SG. Multiple sclerosis as a neuronal disease. Amsterdam: Elsevier 2005.
7. Cifelli A, Matthews PM. Cerebral plasticity in multiple sclerosis: insights from fMRI. Mult Scler 2002;8(3):193– 9.
8. Rakús A. Neuroplasticita. Neurol Praxi 2009;10(2):83– 5.
9. Taláb R. Demyelinizační onemocnění CNS se zaměřením na roztroušenou sklerózu – mezioborový pohled. Postgrad Med 2012;14(9):939– 49.
10. Hemmer B, Archelos JJ, Hartung HP. New concepts in the immunopathogenesis of multiple sclerosis. Nat Rev Neurosci 2002;3(4):291– 301.
11. Řasová K, Havrdová E. Rehabilitace u roztroušené sklerózy mozkomíšní. Neurol Praxi 2005;6(6):306– 9.
12. Pelletier J, Audoin B, Reuter F, et al. Plasticity in MS: from functional imaging to rehabilitation. Int MS J 2009;16(1):26– 31.
13. Reddy H, Narayanan S, Matthews PM, et al. Relating axonal injury to functional recovery in MS. Neurology 2000;54(1):236– 9.
14. Pantano P, Mainero C, Lenzi D, et al. A longitudinal fMRI study on motor activity in patients with multiple sclerosis. Brain 2005;128(9):2146– 53.
15. Mezzapesa DM, Rocca MA, Rodegher M, et al. Functional cortical changes of the sensorimotor network are associated with clinical recovery in multiple sclerosis. Hum Brain Mapp 2008;29(5):562– 73.
16. Tomassini V, Johansen-Berg H, Jbabdi S, et al. Relating brain damage to brain plasticity in patients with multiple sclerosis. Neurorehabil Neural Repair 2012;26(6):581– 93. doi: 10.1177/ 1545968311433208.
17. Tomassini V, Johansen-Berg H, Leonardi L, et al. Preservation of motor skill learning in patients with multiple sclerosis. Mult Scler 2011;17(1):103– 15. doi: 10.1177/ 1352458510381257.
18. Ibrahim I, Tintera J, Skoch A, et al. Fractional anisotropy and mean diffusivity in the corpus callosum of patients with multiple sclerosis: the effect of physiotherapy. Neuroradiology 2011;53(11):917– 26. doi: 10.1007/ s00234-011-0879-6.
19. Rasova K, Prochazkova M, Tintera J, et al. Motor programme activating therapy influences adaptive brain functions in multiple sclerosis: clinical and MRI study. Int J Rehabil Res 2015;38(1):49– 54. doi: 10.1097/ MRR.0000000000000090.
20. Bonzano L, Tacchino A, Brichetto G, et al. Upper limb motor rehabilitation impacts white matter microstructure in multiple sclerosis. Neuroimage 2014;90:107– 16. doi: 10.1016/ j.neuroimage.2013.12.025.
21. Prosperini L, Fanelli F, Petsas N, et al. Multiple sclerosis: changes in microarchitecture of white matter tracts after training with a video game balance board. Radiology 2014;273(2):529– 38. doi: 10.1148/ radiol.14140168.
22. Schoonheim MM, Geurts JJ, Barkhof F. The limits of functional reorganization in multiple sclerosis. Neurology 2010;74(16):1246– 7. doi: 10.1212/ WNL.0b013e3181db9957.
23. Mesaros S, Rocca MA, Kacar K, et al. Diffusion tensor MRI tractography and cognitive impairment in multiple sclerosis. Neurology 2012;78(13):969– 75. doi: 10.1212/ WNL.0b013e31824d5859.
24. Filippi M, Charil A, Rovaris M, et al. Insights from magnetic resonance imaging. Handb Clin Neurol 2014;122:115– 49. doi: 10.1016/ B978-0-444-52001-2.00006-6.
25. Ibrahim I, Tintěra J. Teoretické základy pokročilých metod magnetické rezonance na poli neurověd. Ces Radiol 2013;67(1):9– 19.
26. Hluštík P, Horák D, Herzig R, et al. Funkční zobrazování mozku pomocí magnetické rezonance v neurologii. Neurol Praxi 2008;9(2):83– 6.
27. Penner IK, Opwis K, Kappos L. Relation between functional brain imaging, cognitive impairment and cognitive rehabilitation in patients with multiple sclerosis. J Neurol 2007;254 (Suppl 2):Ii53– 7.
28. Pantano P, Iannetti GD, Caramia F, et al. Cortical motor reorganization after a single clinical attack of multiple sclerosis. Brain 2002;125(7):1607– 15.
29. Saini S, DeStefano N, Smith S, et al. Altered cerebellar functional connectivity mediates potential adaptive plasticity in patients with multiple sclerosis. J Neurol Neurosurg Psychiatry 2004;75(6):840– 6.
30. Weiller C, May A, Sach M, et al. Role of functional imaging in neurological disorders. J Magn Reson Imaging 2006;23(6):840– 50.
31. Rybníčková M. Porovnání efektu terapií u nemocných s roztroušenou sklerózou mozkomíšní pomocí funkční magnetické rezonance. Praha, 2012. Diplomová práce. FTVS UK. Vedoucí práce Kamila Řasová.
32. Sidaros A, Engberg AW, Sidaros K, et al. Diffusion tensor imaging during recovery from severe traumatic brain injury and relation to clinical outcome: a longitudinal study. Brain 2008;131(2):559– 72.
33. Eliassen JC, Boespflug EL, Lamy M, et al. Brain--mapping techniques for evaluating poststroke recovery and rehabilitation: a review. Top Stroke Rehabil 2008;15(5):427– 50. doi: 10.1310/ tsr1505-427.
34. Luccichenti G, Sabatini U. Colouring rehabilitation with functional neuroimaging. Funct Neurol 2009;24(4):189– 93.
35. Barkhof F. The clinico-radiological paradox in multiple sclerosis revisited. Curr Opin Neurol 2002;15(3):239– 45.
36. Dobkin BH. Neurobiology of rehabilitation. Ann N Y Acad Sci 2004;1038:148– 70.
37. Matthews PM, Johansen-Berg H, Reddy H. Non-invasive mapping of brain functions and brain recovery: applying lessons from cognitive neuroscience to neurorehabilitation. Restor Neurol Neurosci 2004;22(3– 5):245– 60.
38. Merzenich MM, Sameshima K. Cortical plasticity and memory. Curr Opin Neurobiol 1993;3(2):187– 96.
39. Di Filippo M, Picconi B, Tantucci M, et al. Short-term and long-term plasticity at corticostriatal synapses: implications for learning and memory. Behav BrainRes 2009;199(1):108– 18. doi: 10.1016/ j.bbr.2008.09.025.
40. Daoudal G, Debanne D. Long-term plasticity of intrinsic excitability: learning rules and mechanisms. Learn Mem 2003;10(6):456– 65.
41. Niemann J, Winker T, Gerling J, et al. Changes of slow cortical negative DC-potentials during the acquisition of a complex finger motor task. Exp Brain Res 1991;85(2):417– 22.
42. Colcombe SJ, Erickson KI, Scalf PE, et al. Aerobic exercise training increases brain volume in aging humans. J Gerontol A Biol Scie Med Sci 2006;61(11):1166– 70.
43. Colcombe SJ, Erickson KI, Raz N, et al. Aerobic fitness reduces brain tissue loss in aging humans. J Gerontol A Biol Scie Med Sci 2003;58(2):176– 80.
44. Gondoh Y, Sensui H, Kinomura S, et al. Effects of aerobic exercise training on brain structure and psychological well-being in young adults. J Sports Med Phys Fitness 2009;49(2):129– 35.
45. Prakash RS, Snook EM, Erickson KI, et al. Cardiorespiratory fitness: a predictor of cortical plasticity in multiple sclerosis. Neuroimage 2007;34(3):1238– 44.
46. Rensink M, Schuurmans M, Lindeman E, et al. Task-oriented training in rehabilitation after stroke: systematic review. J Adv Nurs 2009;65(4):737– 54. doi: 10.1111/ j.1365-2648.2008.04925.x.
47. Edgerton VR, Courtine G, Gerasimenko YP, et al. Training locomotor networks. Brain Res Rev 2008;57(1):241– 54.
48. Edgerton VR, Roy RR. Activity-dependent plasticity of spinal locomotion: implications for sensory processing. Exerc Sport Sci Rev 2009;37(4):171– 8. doi: 10.1097/ JES.0b013e3181b7b932.
49. Liepert J, Bauder H, Wolfgang HR, et al. Treatment-induced cortical reorganization after stroke in humans. Stroke 2000;31(6):1210– 6.
50. Yen CL, Wang RY, Liao KK, et al. Gait training induced change in corticomotor excitability in patients with chronic stroke. Neurorehabil Neural Repair 2008;22(1):22– 30.
51. Morgen K, Kadom N, Sawaki L, et al. Training-dependent plasticity in patients with multiple sclerosis. Brain 2004;127(11):2506– 17.
52. Vojta V, Annegret P. Vojtův princip. Praha: Grada 2010.
53. Frank C, Kobesova A, Kolar P. Dynamic neuromuscular stabilization & sports rehabilitation. Int J Sports Phys Ther 2013;8(1):62– 73.
54. Čápová J. Terapeutický koncept „Bazální programy a podprogramy“. Ostrava: Repronis 2008.
55. Faissner A, Kettenmann H, Trotter J. A critical reviewof contemporary therapies. Comprehensive HumanPhysiology In: Greger R, Windhorst U, eds. Comprehensive Human Physiology. Berlin: Springer-Verlag 1996: 96– 108.
56. Kolar P, Sulc J, Kyncl M, et al. Stabilizing function of the diaphragm: dynamic MRI and synchronized spirometric assessment. J Appl Physiol 2010;109(4):1064– 71. doi: 10.1152/ japplphysiol.01216.2009.
57. Vele F, Cumpelik J. Yoga-based training for spinal stability. In: Liebenson C, ed. Rehabilitation of the spine: a practitioner’s manual. 2nd ed. London: Lippincott Williams & Wilkins 2007:566– 84.
58. Véle F. Kineziologie pro klinickou praxi. Praha: Grada 1997.
59. Řasová K, Hogenová A. Kulturní a filozofické rozdíly v Evropě se odrážejí v rehabilitační léčbě (fyzioterapii) neurologicky nemocných II. Rehabil Fyz Lek 2013;20(3):168– 72.
60. Rasova K, Brandejsky P, Tintera J, et al. Bimanuální sekvenční motorická úloha u roztroušené sklerózy mozkomíšní v obraze funkční magnetické rezonance: vliv fyzioterapeutických technik – pilotní studie. Cesk Slov Neurol N 2009;72(4):350– 8.
61. Rasova K, Krasensky J, Havrdova E, et al. 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 2005;19(2):170– 81.
62. Small SL, Noll DC, Genovese C, et al. Cerebellar hemispheric activation ipsilateral to the paretic hand correlates with functional recovery after stroke. Brain 2002;125(7):1544– 57.
63. Leonard C. The neuroscience of motor learning. In: Leonard C, ed. The neuroscience of human movement. St. Louis: Mosby 1998:203– 29.
64. Baron JC, Cohen LG, Cramer SC, et al. Neuroimaging in stroke recovery: a position paper from the First International Workshop on Neuroimaging and Stroke Recovery. Cerebrovasc Dis 2004;18(3):260– 7.
65. Lassonde M, Sauerwein HC, Lepore F. Extent and limits of callosal plasticity: presence of disconnection symptoms in callosal agenesis. Neuropsychologia 1995;33(8):989– 1007.
66. Manson SC, Palace J, Frank JA, et al. Loss of interhemispheric inhibition in patients with multiple sclerosis is related to corpus callosum atrophy. Exp Brain Res 2006;174(4):728– 33.
67. Cader S, Cifelli A, Abu-Omar Y, et al. Reduced brain functional reserve and altered functional connectivity in patients with multiple sclerosis. Brain 2006;129(2):527– 37.
68. Pelletier J, Habib M, Lyon-Caen O, et al. Functional and magnetic resonance imaging correlates of callosal involvement in multiple sclerosis. Arch Neurol 1993;50(10):1077– 82.
69. Pelletier J, Suchet L, Witjas T, et al. A longitudinal study of callosal atrophy and interhemispheric dysfunction in relapsing-remitting multiple sclerosis. Arch Neurol 2001;58(1):105– 11.
70. Cader S, Palace J, Matthews PM. Cholinergic agonism alters cognitive processing and enhances brain functional connectivity in patients with multiple sclerosis. J Psychopharmacol 2009;23(6):686– 96.
71. Erickson KI, Colcombe SJ, Wadhwa R, et al. Training-induced plasticity in older adults: effects of training on hemispheric asymmetry. Neurobiol Aging 2007;28(2):272– 83.
72. Erickson KI, Colcombe SJ, Wadhwa R, et al. Training-induced functional activation changes in dual-task processing: an FMRI study. Cereb Cortex 2007;17(1):192– 204.
73. Aramaki Y, Honda M, Sadato N. Suppression of the non-dominant motor cortex during bimanual symmetric finger movement: a functional magnetic resonance imaging study. Neuroscience 2006;141(4):2147– 53.
74. Rosazza C, Minati L. Resting-state brain networks: literature review and clinical applications. Neurol Sci 2011;32(5):773– 85. doi: 10.1007/ s10072-011-0636-y.
75. Ramnani N, Behrens TE, Penny W, et al. New approaches for exploring anatomical and functional connectivity in the human brain. Biol Psychiatry 2004;56(9):613– 9.
76. Friston KJ, Harrison L, Penny W. Dynamic causal modelling. Neuroimage 2003;19(4):1273– 302.
77. Rybníčková M. Porovnání efektu terapií u nemocných s roztroušenou sklerozou mozkomíšní pomocí funkční magnetické rezonance. Praha, 2015. Autoreferát dizertační práce. 3. LF UK. Vedoucí práce Kamila Řasová.
78. Leavitt VM, Wylie G, Genova HM, et al. Altered effective connectivity during performance of an information processing speed task in multiple sclerosis. Mult Scler 2012;18(4):409– 17. doi: 10.1177/ 1352458511423651.
79. Finke C, Schlichting J, Papazoglou S, et al. Altered basal ganglia functional connectivity in multiple sclerosis patients with fatigue. Mult Scler 2014;21(7):925– 34. doi: 10.1177/ 1352458514555784.
80. Lenzi D, Conte A, Mainero C, et al. Effect of corpus callosum damage on ipsilateral motor activation in patients with multiple sclerosis: a functional and anatomical study. Hum Brain Mapp 2007;28(7):636– 44.
81. Evangelou N, Konz D, Esiri MM, et al. Regional axonal loss in the corpus callosum correlates with cerebral white matter lesion volume and distribution in multiple sclerosis. Brain 2000;123(9):1845– 9.
82. Ge Y, Law M, Grossman RI. Applications of diffusion tensor MR imaging in multiple sclerosis. Ann N Y Acad Sci 2005;1064:202– 19.
83. Roosendaal SD, Geurts JJ, Vrenken H, et al. Regional DTI differences in multiple sclerosis patients. Neuroimage 2009;44(4):1397– 403. doi: 10.1016/ j.neuroimage.2008.10.026.
84. Cassol E, Ranjeva JP, Ibarrola D, et al. Diffusion tensor imaging in multiple sclerosis: a tool for monitoring changes in normal-appearing white matter. Mult Scler 2004;10(2):188– 96.
85. Song SK, Yoshino J, Le TQ, et al. Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage 2005;26(1):132– 40.
86. Song SK, Sun SW, Ramsbottom MJ, et al. Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. Neuroimage 2002;17(3):1429– 36.
87. Hlinka J, Alexakis C, Hardman JG, et al. Is sedation-induced BOLD fMRI low-frequency fluctuation increase mediated by increased motion? MAGMA 2010;23:367– 74.
88. Ling J, Merideth F, Caprihan A, et al. Head injury or head motion? Assessment and quantification of motion artifacts in diffusion tensor imaging studies. Hum Brain Mapp 2012;33(1):50– 62.
Labels
Paediatric neurology Neurosurgery NeurologyArticle was published in
Czech and Slovak Neurology and Neurosurgery
2017 Issue 2
Most read in this issue
- Ulnar Nerve
- Stroke Incidence in Europe – a Systematic Review
- Anti-NMDAR Encephalitis in Children – a Case Report
- Toxic Effects of Pesticides