Advertisement

Der Nervenarzt

, Volume 87, Issue 10, pp 1074–1081 | Cite as

Neurofeedback-gestütztes Bewegungsvorstellungstraining zur Rehabilitation nach einem Schlaganfall

  • C. Dettmers
  • N. Braun
  • I. Büsching
  • T. Hassa
  • S. Debener
  • J. Liepert
Leitthema

Zusammenfassung

Mentales Training – Bewegungsbeobachten und insbesondere Bewegungsvorstellung – hat viel akademisches Interesse geweckt. Die funktionelle Äquivalenz von Bewegungsvorstellung und Bewegungsausführung lässt hoffen, dass sich mentales Training zur motorischen Rehabilitation nach einem Schlaganfall nutzen lässt. Mittlerweile stehen randomisierte kontrollierte Studien zur Verfügung, von denen ca. die Hälfte einen Zusatznutzen der Bewegungsvorstellung zeigen konnte, die andere Hälfte hingegen keinen Mehrwert nachwies. Mögliche Gründe für eine mangelnde Umsetzung im Rehabilitationsalltag und Hindernisse auf dem Weg zur Etablierung werden ausführlich diskutiert. Im Anschluss daran werden das Neurofeedback-gestützte Bewegungsvorstellungstraining und Closed-loop-Systeme dargestellt und ihre potenzielle Bedeutung für das motorische Lernen und die Rehabilitation nach einem Schlaganfalls erörtert.

Schlüsselwörter

Bewegunsgvorstellungstraining Mentales Training Motorisches Lernen Closed loop Physiotherapie Randomisiert kontrollierte Studien 

Neurofeedback-based motor imagery training for rehabilitation after stroke

Abstract

Mental training, including motor observation and motor imagery, has awakened much academic interest. The presumed functional equivalence of motor imagery and motor execution has given hope that mental training could be used for motor rehabilitation after a stroke. Results obtained from randomized controlled trials have shown mixed results. Approximately half of the studies demonstrate positive effects of motor imagery training but the rest do not show an additional benefit. Possible reasons why motor imagery training has so far not become established as a robust therapeutic approach are discussed in detail. Moreover, more recent approaches, such as neurofeedback-based motor imagery or closed-loop systems are presented and the potential importance for motor learning and rehabilitation after a stroke is discussed.

Keywords

Motor imagery Mental training  Motor learning Closed loop Physiotherapy Randomized controlled trials 

Notes

Einhaltung ethischer Richtlinien

Interessenkonflikt

C. Dettmers, N. Braun, I. Büsching, T. Hassa, S. Debener und J. Liepert geben an, dass kein Interessenkonflikt besteht.

Dieser Beitrag beinhaltet keine von den Autoren durchgeführten Studien an Menschen oder Tieren.

Literatur

  1. 1.
    Maeda F, Kleiner-Fisman G, Pascual-Leone A (2002) Motor facilitation while observing hand actions: Specificity of the effect and role of observer’s orientation. J Neurophysiol 87(3):1329–1335PubMedGoogle Scholar
  2. 2.
    Stefan K, Cohen LG, Duque J, Mazzocchio R, Celnik P, Sawaki L et al (2005) Formation of a motor memory by action observation. J Neurosci 25(41):9339–9346CrossRefPubMedGoogle Scholar
  3. 3.
    Buccino G, Solodkin A, Small SL (2006) Functions of the mirror neuron system: Implications for neurorehabilitation. Cogn Behav Neurol 19(1):55–63CrossRefPubMedGoogle Scholar
  4. 4.
    Ertelt D, Small S, Solodkin A, Dettmers C, McNamara A, Binkofski F et al (2007) Action observation has a positive impact on rehabilitation of motor deficits after stroke. Neuroimage 36(Suppl 2):T164–T173CrossRefPubMedGoogle Scholar
  5. 5.
    Garrison KA, Aziz-Zadeh L, Wong SW, Liew SL, Winstein CJ (2013) Modulating the motor system by action observation after stroke. Stroke 44(8):2247–2253CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Ertelt D, Hemmelmann C, Dettmers C, Ziegler A, Binkofski F (2012) Observation and execution of upper-limb movements as a tool for rehabilitation of motor deficits in paretic stroke patients: protocol of a randomized clinical trial. BMC Neurol 12:42CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Franceschini M, Ceravolo MG, Agosti M, Cavallini P, Bonassi S, Dall’Armi V et al (2012) Clinical relevance of action observation in upper-limb stroke rehabilitation: a possible role in recovery of functional dexterity. A randomized clinical trial. Neurorehabil Neural Repair 26(5):456–462CrossRefPubMedGoogle Scholar
  8. 8.
    Caspers S, Zilles K, Laird AR, Eickhoff SB (2010) ALE meta-analysis of action observation and imitation in the human brain. Neuroimage 50(3):1148–1167CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Vry MS, Saur D, Rijntjes M, Umarova R, Kellmeyer P, Schnell S et al (2012) Ventral and dorsal fiber systems for imagined and executed movement. Exp Brain Res 219(2):203–216CrossRefPubMedGoogle Scholar
  10. 10.
    Jeannerod M, Decety J (1995) Mental motor imagery: A window into the representational stages of action. Curr Opin Neurobiol 5(6):727–732CrossRefPubMedGoogle Scholar
  11. 11.
    Malouin F, Jackson PL, Richards CL (2013) Towards the integration of mental practice in rehabilitation programs. A critical review. Front Hum Neurosci 7:576CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Liu KP, Chan CC, Lee TM, Hui-Chan CW (2004) Mental imagery for promoting relearning for people after stroke: A randomized controlled trial. Arch Phys Med Rehabil 85(9):1403–1408CrossRefPubMedGoogle Scholar
  13. 13.
    Liu KP, Chan CC, Wong RS, Kwan IW, Yau CS, Li LS et al (2009) A randomized controlled trial of mental imagery augment generalization of learning in acute poststroke patients. Stroke 40(6):2222–2225CrossRefPubMedGoogle Scholar
  14. 14.
    Page SJ, Levine P, Leonard A (2007) Mental practice in chronic stroke: results of a randomized, placebo-controlled trial. Stroke 38(4):1293–1297CrossRefPubMedGoogle Scholar
  15. 15.
    Page SJ, Dunning K, Hermann V, Leonard A, Levine P (2011) Longer versus shorter mental practice sessions for affected upper extremity movement after stroke: A randomized controlled trial. Clin Rehabil 25(7):627–637CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Riccio I, Iolascon G, Barillari MR, Gimigliano R, Gimigliano F (2010) Mental practice is effective in upper limb recovery after stroke: A randomized single-blind cross-over study. Eur J Phys Rehabil Med 46(1):19–25PubMedGoogle Scholar
  17. 17.
    Park JH, Park JH (2016) The effects of game-based virtual reality movement therapy plus mental practice on upper extremity function in chronic stroke patients with hemiparesis: A randomized controlled trial. J Phys Ther Sci 28(3):811–815CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Braun SM, Beurskens AJ, Kleynen M, Oudelaar B, Schols JM, Wade DT (2012) A multicenter randomized controlled trial to compare subacute „treatment as usual“ with and without mental practice among persons with stroke in Dutch nursing homes. J Am Med Dir Assoc 13(1):85.e1–85.e7CrossRefGoogle Scholar
  19. 19.
    Schuster C, Butler J, Andrews B, Kischka U, Ettlin T (2012) Comparison of embedded and added motor imagery training in patients after stroke: Results of a randomised controlled pilot trial. Trials 13:11CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Ietswaart M, Johnston M, Dijkerman HC, Joice S, Scott CL, MacWalter RS et al (2011) Mental practice with motor imagery in stroke recovery: Randomized controlled trial of efficacy. Brain 134(Pt 5):1373–1386CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Timmermans AA, Verbunt JA, van Woerden R, Moennekens M, Pernot DH, Seelen HA (2013) Effect of mental practice on the improvement of function and daily activity performance of the upper extremity in patients with subacute stroke: A randomized clinical trial. J Am Med Dir Assoc 14(3):204–212CrossRefPubMedGoogle Scholar
  22. 22.
    Oostra KM, Oomen A, Vanderstraeten G, Vingerhoets G (2015) Influence of motor imagery training on gait rehabilitation in sub-acute stroke: A randomized controlled trial. J Rehabil Med 47(3):204–209CrossRefPubMedGoogle Scholar
  23. 23.
    Braun S, Kleynen M, van Heel T, Kruithof N, Wade D, Beurskens A (2013) The effects of mental practice in neurological rehabilitation; a systematic review and meta-analysis. Front Hum Neurosci 7:390CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Lohse KR, Lang CE, Boyd LA (2014) Is more better? Using metadata to explore dose-response relationships in stroke rehabilitation. Stroke 45(7):2053–2058CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Wright DJ, Williams J, Holmes PS (2014) Combined action observation and imagery facilitates corticospinal excitability. Front Hum Neurosci 8:951PubMedPubMedCentralGoogle Scholar
  26. 26.
    Wondrusch C, Schuster-Amft C (2013) A standardized motor imagery introduction program (MIIP) for neuro-rehabilitation: Development and evaluation. Front Hum Neurosci 7:477CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Olsson CJ, Nyberg L (2010) Motor imagery: If you can’t do it, you won’t think it. Scand J Med Sci Sports 20(5):711–715CrossRefPubMedGoogle Scholar
  28. 28.
    Welfringer A, Leifert-Fiebach G, Babinsky R, Brandt T (2011) Visuomotor imagery as a new tool in the rehabilitation of neglect: A randomised controlled study of feasibility and efficacy. Disabil Rehabil 33(21–22):2033–2043CrossRefPubMedGoogle Scholar
  29. 29.
    Leifert-Fiebach G, Welfringer A, Babinsky R, Brandt T (2013) Motor imagery training in patients with chronic neglect: A pilot study. NeuroRehabilitation 32(1):43–58PubMedGoogle Scholar
  30. 30.
    Di Rienzo F, Collet C, Hoyek N, Guillot A (2014) Impact of neurologic deficits on motor imagery: A systematic review of clinical evaluations. Neuropsychol Rev 24(2):116–147CrossRefPubMedGoogle Scholar
  31. 31.
    Liepert J, Greiner J, Nedelko V, Dettmers C (2012) Reduced upper limb sensation impairs mental chronometry for motor imagery after stroke: Clinical and electrophysiological findings. Neurorehabil Neural Repair 26(5):470–478CrossRefPubMedGoogle Scholar
  32. 32.
    Dettmers C, Benz M, Liepert J, Rockstroh B (2012) Motor imagery in stroke patients, or plegic patients with spinal cord or peripheral diseases. Acta Neurol Scand 126(4):238–247CrossRefPubMedGoogle Scholar
  33. 33.
    Liepert J, Greiner J, Dettmers C (2014) Motor excitability changes during action observation in stroke patients. J Rehabil Med 46(5):400–405CrossRefPubMedGoogle Scholar
  34. 34.
    Pfurtscheller G, Brunner C, Schlogl A, Lopes da Silva FH (2006) Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks. Neuroimage 31(1):153–159CrossRefPubMedGoogle Scholar
  35. 35.
    Pichiorri F, Morone G, Petti M, Toppi J, Pisotta I, Molinari M et al (2015) Brain-computer interface boosts motor imagery practice during stroke recovery. Ann Neurol 77(5):851–865CrossRefPubMedGoogle Scholar
  36. 36.
    Boe S, Gionfriddo A, Kraeutner S, Tremblay A, Little G, Bardouille T (2014) Laterality of brain activity during motor imagery is modulated by the provision of source level neurofeedback. Neuroimage 101:159–167CrossRefPubMedGoogle Scholar
  37. 37.
    Christ O, Reiner M (2014) Perspectives and possible applications of the rubber hand and virtual hand illusion in non-invasive rehabilitation: Technological improvements and their consequences. Neurosci Biobehav Rev 44:33–44CrossRefPubMedGoogle Scholar
  38. 38.
    Grefkes C, Fink GR (2014) Connectivity-based approaches in stroke and recovery of function. Lancet Neurol 13(2):206–216CrossRefPubMedGoogle Scholar
  39. 39.
    Murase N, Duque J, Mazzocchio R, Cohen LG (2004) Influence of interhemispheric interactions on motor function in chronic stroke. Ann Neurol 55(3):400–409CrossRefPubMedGoogle Scholar
  40. 40.
    Takeuchi N, Oouchida Y, Izumi S (2012) Motor control and neural plasticity through interhemispheric interactions. Neural Plast 2012:823285PubMedPubMedCentralGoogle Scholar
  41. 41.
    Chiew M, LaConte SM, Graham SJ (2012) Investigation of fMRI neurofeedback of differential primary motor cortex activity using kinesthetic motor imagery. Neuroimage 61(1):21–31CrossRefPubMedGoogle Scholar
  42. 42.
    Mihara M, Hattori N, Hatakenaka M, Yagura H, Kawano T, Hino T et al (2013) Near-infrared spectroscopy-mediated neurofeedback enhances efficacy of motor imagery-based training in poststroke victims: A pilot study. Stroke 44(4):1091–1098CrossRefPubMedGoogle Scholar
  43. 43.
    Pfurtscheller G, Lopes da Silva FH (1999) Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol 110(11):1842–1857CrossRefPubMedGoogle Scholar
  44. 44.
    McFarland DJ, Miner LA, Vaughan TM, Wolpaw JR (2000) Mu and beta rhythm topographies during motor imagery and actual movements. Brain Topogr 12(3):177–186CrossRefPubMedGoogle Scholar
  45. 45.
    Lotte F, Larrue F, Muhl C (2013) Flaws in current human training protocols for spontaneous Brain-Computer Interfaces: Lessons learned from instructional design. Front Hum Neurosci 7:568CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Zich C, Debener S, Kranczioch C, Bleichner MG, Gutberlet I, De Vos M (2015) Real-time EEG feedback during simultaneous EEG-fMRI identifies the cortical signature of motor imagery. Neuroimage 114:438–447CrossRefPubMedGoogle Scholar
  47. 47.
    Wilson M (2002) Six views of embodied cognition. Psychon Bull Rev 9(4):625–636CrossRefPubMedGoogle Scholar
  48. 48.
    Botvinick M, Cohen J (1998) Rubber hands „feel“ touch that eyes see. Nature 391(6669):756CrossRefPubMedGoogle Scholar
  49. 49.
    Tsakiris M (2010) My body in the brain: A neurocognitive model of body-ownership. Neuropsychologia 48(3):703–712CrossRefPubMedGoogle Scholar
  50. 50.
    Perez-Marcos D, Slater M, Sanchez-Vives MV (2009) Inducing a virtual hand ownership illusion through a brain-computer interface. Neuroreport 20(6):589–594CrossRefPubMedGoogle Scholar
  51. 51.
    Alimardani M, Nishio S, Ishiguro H (2013) Humanlike robot hands controlled by brain activity arouse illusion of ownership in operators. Sci Rep 3:2396CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Ono T, Kimura A, Ushiba J (2013) Daily training with realistic visual feedback improves reproducibility of event-related desynchronisation following hand motor imagery. Clin Neurophysiol 124(9):1779–1786CrossRefPubMedGoogle Scholar
  53. 53.
    Caspar EA, De Beir A, Magalhaes De Saldanha Da Gama PA, Yernaux F, Cleeremans A, Vanderborght B (2015) New frontiers in the rubber hand experiment: when a robotic hand becomes one’s own. Behav Res Methods 47(3):744–755CrossRefPubMedGoogle Scholar
  54. 54.
    Spychala N, Bongartz E, Braun N, Debener S (2016) Towards free robotic hand control with EEG motor imagery. Mind, Brain and Body Smposium, Berlin.Google Scholar
  55. 55.
    Ramachandran VS, Altschuler EL (2009) The use of visual feedback, in particular mirror visual feedback, in restoring brain function. Brain 132(Pt 7):1693–1710CrossRefPubMedGoogle Scholar
  56. 56.
    Klomjai W, Lackmy-Vallee A, Roche N, Pradat-Diehl P, Marchand-Pauvert V, Katz R (2015) Repetitive transcranial magnetic stimulation and transcranial direct current stimulation in motor rehabilitation after stroke: An update. Ann Phys Rehabil Med 58(4):220–224CrossRefPubMedGoogle Scholar
  57. 57.
    Zrenner C, Ziemann U (2015) Therapeutic applications of closed-loop brain stimulation. Success and expectations. Nervenarzt 86(12):1523–1527CrossRefPubMedGoogle Scholar
  58. 58.
    Kraus D, Naros G, Bauer R, Leao MT, Ziemann U, Gharabaghi A (2016) Brain-robot interface driven plasticity: Distributed modulation of corticospinal excitability. Neuroimage 125:522–532CrossRefPubMedGoogle Scholar
  59. 59.
    Brauchle D, Vukelic M, Bauer R, Gharabaghi A (2015) Brain state-dependent robotic reaching movement with a multi-joint arm exoskeleton: Combining brain-machine interfacing and robotic rehabilitation. Front Hum Neurosci 9:564CrossRefPubMedPubMedCentralGoogle Scholar
  60. 60.
    Ono T, Mukaino M, Ushiba J (2013) Functional recovery in upper limb function in stroke survivors by using brain-computer interface A single case A‑B-A-B design. Conf Proc IEEE Eng Med Biol Soc 2013:265–268PubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • C. Dettmers
    • 1
  • N. Braun
    • 2
  • I. Büsching
    • 3
  • T. Hassa
    • 3
    • 4
  • S. Debener
    • 2
  • J. Liepert
    • 3
  1. 1.Kliniken Schmieder KonstanzKonstanzDeutschland
  2. 2.Abteilung für Neuropsychologie, Department für Psychologie, Fakultät VI – Medizin und GesundheitswissenschaftenUniversität OldenburgOldenburgDeutschland
  3. 3.Kliniken Schmieder AllensbachAllensbachDeutschland
  4. 4.Lurija InstitutKonstanzDeutschland

Personalised recommendations