Motor Imagery Training of Reaching-to-Grasp Movement Supplemented by a Virtual Environment in an Individual With Congenital Bilateral Transverse Upper-Limb Deficiency

Joanna Mencel, Anna Jaskólska, Jarosław Marusiak, Łukasz Kamiński, Marek Kurzyński, Andrzej Wołczowski, Artur Jaskólski, Katarzyna Kisiel-Sajewicz, Joanna Mencel, Anna Jaskólska, Jarosław Marusiak, Łukasz Kamiński, Marek Kurzyński, Andrzej Wołczowski, Artur Jaskólski, Katarzyna Kisiel-Sajewicz

Abstract

This study explored the effect of kinesthetic motor imagery training on reaching-to-grasp movement supplemented by a virtual environment in a patient with congenital bilateral transverse upper-limb deficiency. Based on a theoretical assumption, it is possible to conduct such training in this patient. The aim of this study was to evaluate whether cortical activity related to motor imagery of reaching and motor imagery of grasping of the right upper limb was changed by computer-aided imagery training (CAIT) in a patient who was born without upper limbs compared to a healthy control subject, as characterized by multi-channel electroencephalography (EEG) signals recorded before and 4, 8, and 12 weeks after CAIT. The main task during CAIT was to kinesthetically imagine the execution of reaching-to-grasp movements without any muscle activation, supplemented by computer visualization of movements provided by a special headset. Our experiment showed that CAIT can be conducted in the patient with higher vividness of imagery for reaching than grasping tasks. Our results confirm that CAIT can change brain activation patterns in areas related to motor planning and the execution of reaching and grasping movements, and that the effect was more pronounced in the patient than in the healthy control subject. The results show that CAIT has a different effect on the cortical activity related to the motor imagery of a reaching task than on the cortical activity related to the motor imagery of a grasping task. The change observed in the activation patterns could indicate CAIT-induced neuroplasticity, which could potentially be useful in rehabilitation or brain-computer interface purposes for such patients, especially before and after transplantation. This study was part of a registered experiment (ID: NCT04048083).

Keywords: EEG; amelia; grasping; mental training; neuroplasticity; reaching; transplantation.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2021 Mencel, Jaskólska, Marusiak, Kamiński, Kurzyński, Wołczowski, Jaskólski and Kisiel-Sajewicz.

Figures

Figure 1
Figure 1
Scheme of the experimental protocol consisting of four measurement sessions (PRE, POST4, POST8, and POST12) and 12 weeks of computer-aided imagery training (CAIT).
Figure 2
Figure 2
The mean value of ERP amplitude [*−1 (μV)] related to the motor imagery of reaching for the right upper limb from four channels in: the contralateral prefrontal cortex (above the left hemisphere) – area of standard “F3” channel, ipsilateral prefrontal cortex (above the right hemisphere) – area of standard “F4” channel, and contralateral sensorimotor cortex – area of standard “C3” channel and ipsilateral sensorimotor cortex – area of standard “C4” channel for the patient (black color) and control subject (white color) for sessions before 12 weeks of computer-aided imagery training (PRE) and after intervals of 4 weeks each (POST4, POST8, and POST12).
Figure 3
Figure 3
Topographic maps of electroencephalography (EEG) during motor imagery of reaching (MIR) of the right upper limb for the patient (left) and the control subject (right) for four measurement sessions (PRE, POST4, POST8, and POST12).
Figure 4
Figure 4
The mean value of ERP amplitude [*−1 (μV)] related to motor imagery of grasping of the right hand from four channels in: the contralateral prefrontal cortex (above left hemisphere) – area of standard “F3” channel and ipsilateral prefrontal cortex (above right hemisphere) – area of standard “F4” channel, contralateral sensorimotor cortex – area of standard “C3” channel and ipsilateral sensorimotor cortex – area of standard “C4” channel for the patient (black color) and the control subject (white color) for the session before 12 weeks of computer-aided imagery training (PRE) and after intervals of 4 weeks (POST4, POST8, and POST12).
Figure 5
Figure 5
Topographic maps of EEG during motor imagery of grasping (MIG) of the right hand for the patient (left) and the control subject (right) for four measurement sessions (PRE, POST4, POST8, and POST12).

References

    1. Allami N., Brovelli A., Hamzaoui M., Regragui F., Paulignan Y., Boussaoud D. (2014). Neurophysiological correlates of visuo-motor learning through mental and physical practice. Neuropsychologia 55, 6–14. 10.1016/j.neuropsychologia.2013.12.017, PMID:
    1. Avanzino L., Gueugneau N., Bisio A., Ruggeri P., Papaxanthis C., Bove M. (2015). Motor cortical plasticity induced by motor learning through mental practice. Front. Behav. Neurosci. 9:105. 10.3389/fnbeh.2015.00105, PMID:
    1. Ballesteros S., Voelcker-Rehage C., Bherer L. (2018). Editorial: cognitive and brain plasticity induced by physical exercise, cognitive training, video games, and combined interventions. Front. Hum. Neurosci. 12:169. 10.3389/fnhum.2018.00169, PMID:
    1. Binkofski F., Amunts K., Stephan K. M., Posse S., Schormann T., Freund H. J., et al. . (2001). Broca’s region subserves imagery of motion: a combined cytoarchitectonic and fMRI study. Hum. Brain Mapp. 11, 273–285. 10.1002/1097-0193(200012)11:4<273::aid-hbm40>;2-0, PMID:
    1. Brugger P., Kollias S. S., Muri R., Crelier G., Hepp-Reymond M. C., Regard M. (2000). Beyond re-membering: phantom sensations of congenitally absent limbs. PNAS 97, 6167–6172. 10.1073/pnas.100510697, PMID:
    1. Cabral-Sequeira A. S., Coelho D. B., Teixeira L. A. (2016). Motor imagery training promotes motor learning in adolescents with cerebral palsy: comparison between left and right hemiparesis. Exp. Brain Res. 234, 1515–1524. 10.1007/s00221-016-4554-3, PMID:
    1. Cicchetti D. V. (1994). Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychol. Assess. 6, 284–290. 10.1037/1040-3590.6.4.284
    1. Decety J., Perani D., Jeannerod M., Bettinardi V., Tadary B., Woods R., et al. . (1994). Mapping motor representations with PET. Nature 371, 600–602. 10.1038/371600a0, PMID:
    1. 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, 116–147. 10.1007/s11065-014-9257-6, PMID:
    1. Drickstein R., Dunsky A., Marcovitz E. (2004). Motor imagery for gait rehabilitation in post-stroke hemiparesis. Phys. Ther. 84, 1167–1177. 10.1093/ptj/84.12.1167, PMID:
    1. Ersland L., Rosen G., Lundervold A., Smievoll A. I., Tillung T., Sundberg H., et al. . (1996). Phantom limb “fingertapping” causes primary motor cortex activation: an fMRI study. Neuroreport 8, 207–210. 10.1097/00001756-199612200-00042, PMID:
    1. Fadiga L., Buccino G., Craighero L., Fogassi L., Gallese V., Pavesi G. (1999). Corticospinal excitability is specifically modulated by motor imagery: a magnetic stimulation study. Neuropsychologia 37, 147–158. 10.1016/s0028-3932(98)00089-x, PMID:
    1. Flor H., Elbert T., Mühlnickel W., Pantev C., Wienbruch C., Taub E. (1998). Cortical reorganization and phantom phenomena in congenital and traumatic upper-extremity amputees. Exp. Brain Res. 119, 205–212. 10.1007/s002210050334
    1. Gallagher S., Butterworth G. E., Lew A., Cole J. (1998). Hand-mouth coordination, congenital absence of limb and evidence for innate body schemas. Brain Cogn. 38, 53–65. 10.1006/brcg.1998.1020, PMID:
    1. Gerardin E., Sirigu A., Lehericy S., Poline J. B., Gaymard B., Marsault C., et al. . (2000). Partially overlapping neural networks for real and imagined hand movements. Cereb. Cortex 10, 1093–1104. 10.1093/cercor/10.11.1093, PMID:
    1. Glover S., Wall M. B., Smith A. T. (2012). Distinct cortical networks support the planning and online control of reaching-to-grasp in human. Eur. J. Neurosci. 35, 909–915. 10.1111/j.1460-9568.2012.08018.x, PMID:
    1. Guillot A., Collet C. (2005). Contribution from neurophysiological and psychological methods to the study of motor imagery. Brain Res. Rev. 50, 387–397. 10.1016/j.brainresrev.2005.09.004
    1. Guillot A., Debarnot U. (2019). Benefits of motor imagery for human space flight: a brief review of current knowledge and future applications. Front. Physiol. 10:396. 10.3389/fphys.2019.00396, PMID:
    1. Guterstam A., Petkova V. I., Ehrsson H. H. (2011). The illusion of owning a third arm. PLoS One 6:e17208. 10.1371/journal.pone.0017208, PMID:
    1. Hanakawa T., Immisch I., Toma K., Dimyan A. M., Van Gelderen P., Hallett M. (2003). Functional properties of brain areas associated with motor execution and imagery. J. Neurophysiol. 89, 989–1002. 10.1152/jn.00132.2002, PMID:
    1. Harris J. E., Hebert A. (2015). Utilization of motor imagery in upper limb rehabilitation: a systematic scoping review. Clin. Rehabil. 29, 1092–1107. 10.1177/0269215514566248, PMID:
    1. Hétu S., Grégoire M., Saimpont A., Coll M. P., Eugène F., Michon P. E., et al. . (2013). The neural network of motor imagery: an ALE meta-analysis. Neurosci. Biobehav. Rev. 37, 930–949. 10.1016/j.neubiorev.2013.03.017, PMID:
    1. Hoshiyama M., Kakigi R., Berg P., Koyama S., Kitamura Y., Shimojo M., et al. (1997). Identification of motor and sensory brain activities during unilateral finger movement: spatiotemporal source analysis of movement-associated magnetic fields. Exp. Brain Res. 115, 6–14. 10.1007/PL00005685, PMID:
    1. Ietswaart M., Johnston M., Dijkerman H. C., Joice S., Scott C. L., MacWalter R. S., et al. . (2011). Mental practice with motor imagery in stroke recovery: randomized controlled trial of efficacy. Brain 134, 1373–1386. 10.1093/brain/awr077, PMID:
    1. Jeannerod M. (1994). Mental imagery in the motor context. Neuropsychologia 33, 1419–1432.
    1. Jeannerod M., Decety J. (1995). Mental motor imagery: a window into the representational stages of action. Curr. Opin. Neurobiol. 5, 727–732. 10.1016/0959-4388(95)80099-9, PMID:
    1. Kandel E. R., Schwartz J. H., Jessell T. M. (2000). Principles of neural science. New York: McGraw-Hill, Health Professions Division.
    1. Kasess C. H., Windischberger C., Cunnington R., Lanzenberger R., Pezawas L., Moser R. (2008). The suppressive influence of SMA on MI in motor imagery revealed by fMRI and dynamic causal modeling. NeuroImage 40, 828–837. 10.1016/j.neuroimage.2007.11.040, PMID:
    1. Kurzynski M., Jaskolska A., Marusiak J., Wolczowski A., Bierut P., Szumowski L., et al. . (2017). Computer-aided training sensorimotor cortex functions in humans before the upper limb transplantation using virtual reality and sensory feedback. Comput. Biol. Med. 87, 311–321. 10.1016/j.compbiomed.2017.06.010, PMID:
    1. Lotze M., Flor H., Grodd W., Larbig W., Birbaumer N. (2001). Phantom movements and pain. An fMRI study in upper limb amputees. Brain 124, 2268–2277. 10.1093/brain/124.11.2268, PMID:
    1. Marins T., Rodrigues E. C., Bortolini T., Melo B., Moll J., Tovar-Moll F. (2019). Structural and functional connectivity changes in response to short-term neurofeedback training with motor imagery. NeuroImage 194, 283–290. 10.1016/j.neuroimage.2019.03.027, PMID:
    1. Melzack R., Israel R., Lacroix R., Schultz G. (1997). Phantom limbs in people with congenital limb deficiency or amputation in early childhood. Brain 120, 1603–1620. 10.1093/brain/120.9.1603, PMID:
    1. Merzenich M. M., Van Vleet T. M., Nahum M. (2014). Brain plasticity-based therapeutics. Front. Hum. Neurosci. 8:385. 10.3389/fnhum.2014.00385, PMID:
    1. Mizuguchi N., Sakamoto M., Muraoka T., Nakagawa K., Kanazawa S., Nakata H., et al. . (2011). The modulation of corticospinal excitability during motor imagery of actions with objects. PLoS One 6:e26006. 10.1371/journal.pone.0026006, PMID:
    1. Mokienko O. A., Chervyakov A. V., Kulikova S. N., Bobrov P. D., Chernikova L. A., Frolov A. A., et al. . (2013). Increased motor cortex excitability during motor imagery in brain-computer interface in trained subjects. Front. Comput. Neurosci. 7:168. 10.3389/fncom.2013.00168, PMID:
    1. Montoya P., Larbig W., Grulke N., Flor H., Taub E., Birbaumer N. (1997). The relationship of phantom limb pain to other phantom limb phenomena in upper extremity amputees. Pain. 72, 87–93. 10.1016/s0304-3959(97)00004-3
    1. Mulder T. (2007). Motor imagery and action observation: cognitive tools for rehabilitation. J. Neural Transm. 114, 1265–1278. 10.1007/s00702-007-0763-z, PMID:
    1. Oostenveld R., Praamstra P. (2001). The five percent electrode system for high-resolution EEG and ERP measurements. Clin. Neurophysiol. 112, 713–719. 10.1016/S1388-2457(00)00527-7, PMID:
    1. Ortner R., Irimia D. C., Scharinger J., Guger C. (2012). A motor imagery based brain-computer interface for stroke rehabilitation. Stud. Health Technol. Inform. 181, 319–323. 10.3233/978-1-61499-121-2-319, PMID:
    1. Pilgramm S., de Haas B., Helm F., Zentgraf K., Stark R., Munzert J., et al. . (2016). Motor imagery of hand actions: decoding the content of motor imagery from brain activity in frontal and parietal motor areas. Hum. Brain Mapp. 37, 81–93. 10.1002/hbm.23015, PMID:
    1. Ramachandran V. S., Altschuler E. L. (2009). The use of visual feedback, in particular mirror visual feedback, in restoring brain function. Brain 132, 1693–1710. 10.1093/brain/awp135, PMID:
    1. Ranganathan V. K., Siemionow V., Liu J. Z., Sahgal V., Yue G. H. (2004). From mental power to muscle power-gaining strength by using the mind. Neuropsychiatrie 42, 944–956. 10.1016/j.neuropsychologia.2003.11.018, PMID:
    1. Reilly K. T., Sirigu A. (2011). Motor cortex representation of the upper-limb in individuals born without a hand. PLoS One 6:e18100. 10.1371/journal.pone.0018100, PMID:
    1. Saadah E. S., Melzack R. (1994). Phantom limb experiences in congenital limb-deficient adults. Cortex 30, 479–485. 10.1016/S0010-9452(13)80343-7, PMID:
    1. Scherg M. (1992). Functional imaging and localization of electromagnetic brain activity. Brain Topogr. 5, 103–111. 10.1007/BF01129037, PMID:
    1. Scherg M., Berg P. (1996). New concepts of brain source imaging and localization. Electroencephalogr. Clin. Neurophysiol. Suppl. 46, 127–137. PMID:
    1. Scherg M., Berg P., Nakasato N., Beniczky S. (2019). Taking the EEG back into the brain: the power of multiple discrete sources. Front. Neurol. 10:855. 10.3389/fneur.2019.00855, PMID:
    1. Schuster C., Hilfiker R., Amft O., Scheidhauer A., Andrews B., Butler J., et al. . (2011). Best practice for motor imagery: a systematic literature review on motor imagery training elements in five different disciplines. BMC Med. 9:75. 10.1186/1741-7015-9-75, PMID:
    1. Sober S. J., Sabes P. N. (2003). Multisensory integration during motor planning. J. Neurosci. 23, 6982–6992. 10.1523/JNEUROSCI.23-18-06982.2003, PMID:
    1. Sobierajewicz J., Przekoracka-Krawczyk A., Jaśkowski W., Verwey W., van der Lubbe R. (2016). The influence of motor imagery on the learning of a fine hand motor skill. Exp. Brain Res. 235, 305–320. 10.1007/s00221-016-4794-2, PMID:
    1. Solodkin A., Hlustik P., Chen E. E. (2004). Small SL. Fine modulation in network activation during motor execution and motor imagery. Cereb. Cortex 14, 1246–1255. 10.1093/cercor/bhh086, PMID:
    1. Stephan K. M., Fink G. R., Passingham R. E., Silbersweig D., Ceballos-Baumann A. O., Frith C. D., et al. . (1995). Functional anatomy of the mental representation of upper extremity movements in healthy subjects. J. Neurophysiol. 73, 373–386. 10.1152/jn.1995.73.1.373, PMID:
    1. Striem-Amit E., Vannuscorps G., Caramazza A. (2017). Sensorimotor-independent development of hands and tools selectivity in the visual cortex. PNAS 114, 4787–4792. 10.1073/pnas.1620289114, PMID:
    1. Teo W. P., Chew E. (2014). Is motor-imagery brain-computer interface feasible in stroke rehabilitation? PM R 6, 723–728. 10.1016/j.pmrj.2014.01.006, PMID:
    1. Vannuscorps G., Wurm M. F., Striem-Amit E., Caramazza A. (2018). Large-scale organization of the hand action observation network in individuals born without hands. Cereb. Cortex 29, 3434–3444. 10.1093/cercor/bhy212, PMID:
    1. Williams S. E., Cumming J., Ntoumanis N., Nordin-Bates S. M., Ramsey R., Hall C. (2002). Further validation and development of the movement imagery questionnaire. J. Sport Exerc. Psychol. 34, 621–646. 10.1123/jsep.34.5.621, PMID:
    1. Zabicki A., de Haas B., Zentgraf K., Stark R., Munzert J., Krüger B. (2019). Subjective vividness of motor imagery has a neural signature in human premotor and parietal cortex. NeuroImage 197, 273–283. 10.1016/j.neuroimage.2019.04.073, PMID:

Source: PubMed

3
Sottoscrivi