Skip to main content
SpringerLink
Log in

Foundations and Characteristics of the Use of Motor Imagery and Brain–Computer Interfaces in Rehabilitation in Juvenile Cerebral Palsy

  • Published:
Neuroscience and Behavioral Physiology Aims and scope Submit manuscript

We present here an analysis of the literature on various aspects of the use of motor imagery and brain–computer interface (BCI) technologies in the rehabilitation of children with diagnoses of juvenile cerebral palsy (JCP). We describe compensatory mechanisms for restoration of motor functions in the presence of damage to areas of the motor network of the brain in early life. Approaches to objective monitoring of the ability of children to imagine movements are described and grounds are presented for the possibility of training children with JCP to motor imagery, particularly using BCI; possible factors hindering the use of BCI in children with JCP are discussed. Results from clinical trials of the efficacy of BCI in rehabilitation in JCP are presented. Despite the fact that the number of studies in this area is quite limited, the results of the investigations covered here lead to the conclusion that training to motor imagery using BCI can potentially be used in the rehabilitation of children with JCP and may be quite effective.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Aikardi, Zh., Martin, B., and Kristofer, G., Diseases of the Nervous System in Children, BINOM, Moscow (2013).

    Google Scholar 

  • Ang, K. K., Chua, K. S., Phua, K. S., et al., “A randomized controlled trial of EEG-based motor imagery brain–computer interface robotic rehabilitation for stroke,” Clin. EEG Neurosci., 46, No. 4, 310–320 (2015).

    Article  Google Scholar 

  • Ang, K. K., Guan, C., Chua, K. S. G., et al., “A large clinical study on the ability of stroke patients to use an EEG-based motor imagery brain–computer interface,” Clin. EEG Neurosci., 42, No. 4, 253–258 (2011).

    Article  Google Scholar 

  • Anguelova, G. V., Rombouts, S., van Dijk, J. G., et al., “Increased brain activation during motor imagery suggests central abnormality in neonatal brachial plexus palsy,” Neurosci. Res., 123, 19–26 (2017).

    Article  Google Scholar 

  • Bai, Z., Fong, K. N. K., Zhang, J. J., et al., “Immediate and long-term effects of BCI-based rehabilitation of the upper extremity after stroke: a systematic review and meta-analysis,” J. Neuroeng. Rehabil., 17, No. 1, 57 (2020).

  • Basu, A., Graziadio, S., Smith, M., et al., “Developmental plasticity connects visual cortex to motoneurons after stroke,” Ann. Neurol., 67, No. 1, 132–136 (2010).

    Article  Google Scholar 

  • Bobrov, P. D., Biryukova, E. V., Polyaev, B. A., et al., “Rehabilitation of patients with juvenile cerebral palsy with a hand exoskeleton controlled by a ‘brain–computer’ interface,” Vestn. Ross. Gos. Med. Univ., 2020, No. 4, 34–41 (2020).

    Google Scholar 

  • Butti, N., Montirosso, R., Giusti, L., et al., “Early brain damage affects body schema and person perception abilities in children and adolescents with spastic diplegia,” Neural Plast., 1678984 (2019).

  • Cabral-Sequeira, A. S., Coelho, D. B., and Teixeira, L. A., “Motor imagery training promotes motor learning in adolescents with cerebral palsy: comparison between left and right hemiparesis,” Exp. Brain Res., 234, No. 6, 1515–1524 (2016).

    Article  Google Scholar 

  • Caeyenberghs, K., Tsoupas, J., Wilson, P. H., and Smits-Engelsman, B. C., “Motor imagery development in primary school children,” Dev. Neuropsychol., 34, No. 1, 103–121 (2009a).

    Article  Google Scholar 

  • Caeyenberghs, K., Wilson, P. H., Van Roon, D., et al., “Increasing convergence between imagined and executed movement across development: evidence for the emergence of movement representations,” Dev. Sci., 12, No. 3, 474–483 (2009b).

    Article  Google Scholar 

  • Caria, A., Weber, C., Brotz, D., et al., “Chronic stroke recovery after combined BCI training and physiotherapy: a case report,” Psychophysiology, 48, No. 4, 578–582 (2011).

    Article  Google Scholar 

  • Carr, L. J., Harrison, L. M., Evans, A. L., and Stephens, J. A., “Patterns of central motor reorganization in hemiplegic cerebral palsy,” Brain, 116, Part 5, 1223–1247 (1993).

  • Choudhury, S., Charman, T., Bird, V., and Blakemore, S. J., “Development of action representation during adolescence,” Neuropsychologia, 45, No. 2, 255–262 (2007).

    Article  Google Scholar 

  • Craje, C., Aarts, P., Nijhuis-van der Sanden, M., and Steenbergen, B., “Action planning in typically and atypically developing children (unilateral cerebral palsy),” Res. Dev. Disabil., 31, No. 5, 1039–1046 (2010a).

    Article  Google Scholar 

  • Craje, C., van Elk, M., Beeren, M., et al., “Compromised motor planning and motor imagery in right hemiparetic cerebral palsy,” Res. Dev. Disabil., 31, No. 6, 1313–1322 (2010b).

    Article  Google Scholar 

  • Crognier, L., Skoura, X., Vinter, A., and Papaxanthis, C., “Mental representation of arm motion dynamics in children and adolescents,” PLoS One, 8, No. 8, e73042 (2013).

  • Daly, I., Billinger, M., Laparra-Hernandez, J., et al., “On the control of brain–computer interfaces by users with cerebral palsy,” Clin. Neurophysiol., 124, No. 9, 1787–1797 (2013).

  • Daly, I., Faller, J., Scherer, R., et al., “Exploration of the neural correlates of cerebral palsy for sensorimotor BCI control,” Front. Neuroeng., 7, 20 (2014).

    Article  Google Scholar 

  • Daprati, E., Nico, D., Duval, S., and Lacquaniti, F., “Different motor imagery modes following brain damage,” Cortex, 46, No. 8, 1016–1030 (2010).

    Article  Google Scholar 

  • de Almeida Carvalho Duarte, N., Collange Grecco, L. A., Zanon, N., et al., “Motor cortex plasticity in children with spastic cerebral palsy: A systematic review,” J. Mot. Behav., 49, No. 4, 355–364 (2017).

  • Decety, J. and Jeannerod, M., “Mentally simulated movements in virtual reality: does Fitt’s law hold in motor imagery?” Behav. Brain Res., 72, No. 1–2, 127–134 (1995).

    Article  Google Scholar 

  • Démas, J., Bourguignon, M., Périvier, M., et al., “Mu rhythm: State of the art with special focus on cerebral palsy,” Ann. Phys. Rehabil. Med., (2019).

  • Di Rienzo, F., Collet, C., Hoyek, N., and Guillot, A., “Impact of neurologic deficits on motor imagery: a systematic review of clinical evaluations,” Neuropsychol. Rev., 24, No. 2, 116–147 (2014).

    Article  Google Scholar 

  • Errante, A., Bozzetti, F., Sghedoni, S., et al., “Explicit motor imagery for grasping actions in children with spastic unilateral cerebral palsy,” Front. Neurol., 10, 837 (2019).

    Article  Google Scholar 

  • Fennell, E. B. and Dikel, T. N., “Cognitive and neuropsychological functioning in children with cerebral palsy,” J. Child Neurol., 16, No. 1, 58–63 (2001).

    Article  Google Scholar 

  • Ferrari, A., “From movement to action: a new framework for cerebral palsy,” Eur. J. Phys. Rehabil. Med., 55, No. 6, 852–861 (2019).

    Google Scholar 

  • Frassinetti, F., Fiori, S., D’Angelo, V., et al., “Body knowledge in brain-damaged children: a double-dissociation in self and other’s body processing,” Neuropsychologia, 50, No. 1, 181–188 (2012).

    Article  Google Scholar 

  • Frolov, A. A., Aziatskaya, G. A., Bobrov, P. D., et al., “Electrophysiological brain activity during the control of a motor imagery-based brain–computer interface,” Hum. Physiol., 43, No. 5, 501–511 (2017a).

    Article  Google Scholar 

  • Frolov, A. A., Mokienko, O., Lyukmanov, R., et al., “Post-stroke rehabilitation training with a motor-imagery-based brain–computer interface (bci)-controlled hand exoskeleton: A randomized controlled multicenter trial,” Front. Neurosci., 11, 400 (2017b).

    Article  Google Scholar 

  • Funk, M., Brugger, P., and Wilkening, F., “Motor processes in children’s imagery: the case of mental rotation of hands,” Dev. Sci., 8, No. 5, 402–408 (2005).

    Article  Google Scholar 

  • Grezes, J. and Decety, J., “Functional anatomy of execution, mental simulation, observation, and verb generation of actions: a meta-analysis,” Hum. Brain Mapp., 12, No. 1, 1–19 (2001).

    Article  Google Scholar 

  • Hétu, S., Grégoire, M., Saimpont, A., et al., “The neural network of motor imagery: an ALE meta-analysis,” Neurosci. Biobehav. Rev., 37, No. 5, 930–949 (2013).

    Article  Google Scholar 

  • Iosa, M., Zoccolillo, L., Montesi, M., et al., “The brain’s sense of walking: a study on the intertwine between locomotor imagery and internal locomotor models in healthy adults, typically developing children and children with cerebral palsy,” Front. Hum. Neurosci., 8, 859 (2014).

    Article  Google Scholar 

  • Jang, S. H., You, S. H., Hallett, M., et al., “Cortical reorganization and associated functional motor recovery after virtual reality in patients with chronic stroke: an experimenter-blind preliminary study,” Arch. Phys. Med. Rehabil., 86, No. 11, 2218–2223 (2005).

    Article  Google Scholar 

  • Jenks, K. M., de Moor, J., and van Lieshout, E. C., “Arithmetic difficulties in children with cerebral palsy are related to executive function and working memory,” J. Child Psychol. Psychiatry, 50, No. 7, 824–833 (2009).

    Article  Google Scholar 

  • Jongsma, M. L., Baas, C. M., Sangen, A. F., et al., “Children with unilateral cerebral palsy show diminished implicit motor imagery with the affected hand,” Dev. Med. Child Neurol., 58, No. 3, 277–284 (2016).

    Article  Google Scholar 

  • Kim, T. W. and Lee, B. H., “Clinical usefulness of brain–computer interface-controlled functional electrical stimulation for improving brain activity in children with spastic cerebral palsy: a pilot randomized controlled trial,” J. Phys. Ther. Sci., 28, No. 9, 2491–2494 (2016).

    Article  Google Scholar 

  • Kimberley, T. J., Khandekar, G., Skraba, L. L., et al., “Neural substrates for motor imagery in severe hemiparesis,” Neurorehabil. Neural Repair, 20, No. 2, 268–277 (2006).

    Article  Google Scholar 

  • Kondur, A. A., Kotov, S. V., Turbina, L. G., et al., “Features of the use of a noninvasive brain–computer interface + hand exoskeleton in clinical practice in patients after stroke,” in: 14th Int. Interdisciplinary Conf. “Neuroscience for Medicine and Psychology” (2018).

  • Kübler, A. and Birbaumer, N., “Brain–computer interfaces and communication in paralysis: Extinction of goal directed thinking in completely paralysed patients?” Clin. Neurophysiol., 119, No. 11, 2658–2666 (2008).

    Article  Google Scholar 

  • Kułak, W. and Sobaniec, W., “Cerebral palsy in children in north-eastern Poland,” J. Pediatr. Neurol., 2, No. 2, 79–84 (2004).

  • Kułak, W. and Sobaniec, W., “Spectral analysis and coherence EEG in children with cerebral palsy diplegia spastica,” Przegl. Lek., 60, 1–5 (2003).

    Google Scholar 

  • Larina, N., Korsunskaya, L., and Vlasenko, S., “The ‘Exorcist-2’ system in upper limb rehabilitation in juvenile cerebral palsy using a noninvasive ‘brain–computer’ interface,” Nervno-Mysh. Bol., 9, No. 4, 44–50 (2019).

    Google Scholar 

  • Larina, N., Nacharova, M., Korsunskaya, L., et al., “Changes in EEG patterns in the α-frequency band following BCI-based therapy in children with cerebral palsy,” Bull. RSMU, 4, 15–20 (2020).

    Google Scholar 

  • Li, Y., Nam, C. S., Shadden, B. B., and Johnson, S. L., “A P300-based brain–computer interface: Effects of interface type and screen size,” Int. J. Hum. Component. Interaction, 27, No. 1, 52–68 (2010).

    Article  Google Scholar 

  • Lust, J. M., Wilson, P. H., and Steenbergen, B., “Motor imagery difficulties in children with Cerebral Palsy: A specific or general deficit?” Res. Dev. Disabil., 57, 102–111 (2016).

    Article  Google Scholar 

  • Maegaki, Y., Maeoka, Y., Ishii, S., et al., “Central motor reorganization in cerebral palsy patients with bilateral cerebral lesions,” Pediatr. Res., 45, No. 4 Part 1, 559–567 (1999).

  • Mokienko, O., Chernikova, L., Frolov, A., and Bobrov, P., “Motor imagery and its practical application,” Zh. Vyssh. Nerv. Deyat., 63, No. 2, 195–204 (2013).

    Google Scholar 

  • Molina, M., Kudlinski, C., Guilbert, J., et al., “Motor imagery for walking: a comparison between cerebral palsy adolescents with hemiplegia and diplegia,” Res. Dev. Disabil., 37, 95–101 (2015).

    Article  Google Scholar 

  • Molina, M., Tijus, C., and Jouen, F., “The emergence of motor imagery in children,” J. Exp. Child Psychol., 99, No. 3, 196–209 (2008).

    Article  Google Scholar 

  • Mutch, L., Alberman, E., Hagberg, B., et al., “Cerebral palsy epidemiology: where are we now and where are we going?” Dev. Med. Child Neurol., 34, No. 6, 547–551 (1992).

    Article  Google Scholar 

  • Nam, C. S., Woo, J., and Bahn, S., “Severe motor disability affects functional cortical integration in the context of brain–computer interface (BCI) use,” Ergonomics, 55, No. 5, 581–591 (2012).

    Article  Google Scholar 

  • Odding, E., Roebroeck, M. E., and Stam, H. J., “The epidemiology of cerebral palsy: incidence, impairments and risk factors,” Disabil. Rehabil., 28, No. 4, 183–191 (2006).

    Article  Google Scholar 

  • Ono, T., Shindo, K., Kawashima, K., et al., “Brain–computer interface with somatosensory feedback improves functional recovery from severe hemiplegia due to chronic stroke,” Front. Neuroeng., 7, 19 (2014).

    Article  Google Scholar 

  • Ono, T., Tomita, Y., Inose, M., et al., “Multimodal sensory feedback associated with motor attempts alters BOLD responses to paralyzed hand movement in chronic stroke patients,” Brain Topogr., 28, No. 2, 340–351 (2015).

    Article  Google Scholar 

  • Parsons, L. M., “Temporal and kinematic properties of motor behavior reflected in mentally simulated action,” J. Exp. Psychol. Hum. Percept. Perform., 20, No. 4, 709–730 (1994).

    Article  Google Scholar 

  • Ramos-Murguialday, A., Broetz, D., Rea, M., et al., “Brain–machine interface in chronic stroke rehabilitation: a controlled study,” Ann. Neurol., 74, No. 1, 100–108 (2013).

    Article  Google Scholar 

  • Rehme, A. K., Eickhoff, S. B., Rottschy, C., et al., “Activation likelihood estimation meta-analysis of motor-related neural activity after stroke,” NeuroImage, 59, No. 3, 2771–2782 (2012).

    Article  Google Scholar 

  • Reid, L. B., Rose, S. E., and Boyd, R. N., “Rehabilitation and neuroplasticity in children with unilateral cerebral palsy,” Nat. Rev. Neurol., 11, No. 7, 390–400 (2015).

    Article  Google Scholar 

  • Shenton, J. T., Schwoebel, J., and Coslett, H. B., “Mental motor imagery and the body schema: evidence for proprioceptive dominance,” Neurosci. Lett., 370, No. 1, 19–24 (2004).

    Article  Google Scholar 

  • Shin, Y. K., Lee, D. R., Hwang, H. J., et al., “A novel EEG-based brain mapping to determine cortical activation patterns in normal children and children with cerebral palsy during motor imagery tasks,” Neurorehabilitation, 31, No. 4, 349–355 (2012).

    Article  Google Scholar 

  • Souto, D. O., Cruz, T. K. F., Fontes P. L. B., and Haase, V., G., “Motor imagery in children with unilateral cerebral palsy: a case–control study,” Dev. Med. Child Neurol., 62, No. 12, 1396–1405 (2020).

  • Spruijt, S., Jouen, F., Molina, M., et al., “Assessment of motor imagery in cerebral palsy via mental chronometry: the case of walking,” Res. Dev. Disabil., 34, No. 11, 4154–4160 (2013).

    Article  Google Scholar 

  • Spruijt, S., van der Kamp, J., and Steenbergen, B., “Current insights in the development of children’s motor imagery ability,” Front. Psychol., 6, 787 (2015).

    Article  Google Scholar 

  • Staudt, M., Grodd, W., Gerloff, C., et al., “Two types of ipsilateral reorganization in congenital hemiparesis: a TMS and fMRI study,” Brain, 125, No. 10, 2222–2237 (2002).

    Article  Google Scholar 

  • Steenbergen, B. and Gordon, A. M., “Activity limitation in hemiplegic cerebral palsy: evidence for disorders in motor planning,” Dev. Med. Child. Neurol., 48, No. 9, 780–783 (2006).

    Article  Google Scholar 

  • Steenbergen, B., Jongbloed-Pereboom, M., Spruijt, S., and Gordon, A. M., “Impaired motor planning and motor imagery in children with unilateral spastic cerebral palsy: challenges for the future of pediatric rehabilitation,” Dev. Med. Child. Neurol., 55, Suppl. 4, 43–46 (2013).

    Article  Google Scholar 

  • Straub, K. and Obrzut, J. E., “Effects of cerebral palsy on neuropsychological function,” J. Dev. Phys. Disabil., 21, No. 2, 153 (2009).

  • Taherian, S., Selitskiy, D., Pau, J., et al., “Training to use a commercial brain–computer interface as access technology: a case study,” Disabil. Rehabil. Assist. Technol., 11, No. 4, 345–350 (2016).

    Google Scholar 

  • Thickbroom, G. W., Byrnes, M. L., Archer, S. A., et al., “Differences in sensory and motor cortical organization following brain injury early in life,” Ann. Neurol., 49, No. 3, 320–327 (2001).

    Article  Google Scholar 

  • van Elk, M., Craje, C., Beeren, M. E., et al., “Neural evidence for compromised motor imagery in right hemiparetic cerebral palsy,” Front. Neurol., 1, 150 (2010).

    Google Scholar 

  • Vuckovic, A., Pineda, J. A., LaMarca, K., et al., “Interaction of BCI with the underlying neurological conditions in patients: pros and cons,” Front. Neuroeng., 7, 42 (2014).

    Article  Google Scholar 

  • Wilson, P. H., Adams, I. L., Caeyenberghs, K., et al., “Motor imagery training enhances motor skill in children with DCD: A replication study,” Res. Dev. Disabil., 57, 54–62 (2016).

    Article  Google Scholar 

  • Wilson, P. H., Thomas, P. R., and Maruff, P., “Motor imagery training ameliorates motor clumsiness in children,” J. Child Neurol., 17, No. 7, 491–498 (2002).

    Article  Google Scholar 

  • Wittenberg, G. F., “Motor mapping in cerebral palsy,” Dev. Med. Child. Neurol., 51, Suppl. 4, 134–139 (2009).

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Moscow, Russia

    I. R. Fedotova & P. D. Bobrov

  2. Pirogov Russian National Research Medical University, Moscow, Russia

    P. D. Bobrov

Authors
  1. I. R. Fedotova
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P. D. Bobrov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to P. D. Bobrov.

Additional information

Translated from Zhurnal Vysshei Nervnoi Deyatel’nosti imeni I. P. Pavlova, Vol. 72, No. 1, pp. 87–99, January–February, 2022.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fedotova, I.R., Bobrov, P.D. Foundations and Characteristics of the Use of Motor Imagery and Brain–Computer Interfaces in Rehabilitation in Juvenile Cerebral Palsy. Neurosci Behav Physi 52, 1052–1060 (2022). https://doi.org/10.1007/s11055-022-01333-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11055-022-01333-0

Keywords

Search

Navigation