constraint-induced movement therapy; electroencephalography; power analysis; predictors; robot-assisted therapy; stroke; Behavioral Neuroscience; Biological Psychiatry; Psychiatry and Mental health; Neurology; Neuropsychology and Physiological Psychology
Abstract :
[en] [en] BACKGROUND: The mechanism of stroke recovery is related to the reorganization of cerebral activity that can be enhanced by rehabilitation therapy. Two well established treatments are Robot-Assisted Therapy (RT) and Constraint-Induced Movement Therapy (CIMT), however, it is unknown whether there is a difference in the neuroplastic changes induced by these therapies, and if the modifications are related to motor improvement. Therefore, this study aims to identify neurophysiological biomarkers related to motor improvement of participants with chronic stroke that received RT or CIMT, and to test whether there is a difference in neuronal changes induced by these two therapies.
METHODS: This study included participants with chronic stroke that took part in a pilot experiment to compare CIMT vs. RT. Neurophysiological evaluations were performed with electroencephalography (EEG) and transcranial magnetic stimulation (TMS), pre and post rehabilitation therapy. Motor function was measured by the Wolf Motor Function Test (WMFT) and Fugl-Meyer Assessment Upper Limb (FMA-UL).
RESULTS: Twenty-seven participants with chronic stroke completed the present study [mean age of 58.8 years (SD ± 13.6), mean time since stroke of 18.2 months (SD ± 9.6)]. We found that changes in motor threshold (MT) and motor evoked potential (MEP) in the lesioned hemisphere have a positive and negative correlation with WMFT improvement, respectively. The absolute change in alpha peak in the unlesioned hemisphere and the absolute change of the alpha ratio (unlesioned/lesioned hemisphere) is negatively correlated with WMFT improvement. The decrease of EEG power ratio (increase in the lesioned hemisphere and decrease in the unlesioned hemisphere) for high alpha bandwidths is correlated with better improvement in WMFT. The variable "type of treatment (RT or CIMT)" was not significant in the models.
CONCLUSION: Our results suggest that distinct treatments (RT and CIMT) have similar neuroplastic mechanisms of recovery. Moreover, motor improvements in participants with chronic stroke are related to decreases of cortical excitability in the lesioned hemisphere measured with TMS. Furthermore, the balance of both EEG power and EEG alpha peak frequency in the lesioned hemisphere is related to motor improvement.
Disciplines :
Neurosciences & behavior
Author, co-author :
Simis, Marcel; Instituto de Medicina Fisica e Reabilitacao, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil ; Departamento de Medicina Legal, Bioética, Medicina do Trabalho e Medicina Física e Reabilitação, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
Thibaut, Aurore ; Université de Liège - ULiège > GIGA > GIGA Consciousness - Coma Science Group
Imamura, Marta; Instituto de Medicina Fisica e Reabilitacao, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil ; Departamento de Medicina Legal, Bioética, Medicina do Trabalho e Medicina Física e Reabilitação, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
Battistella, Linamara Rizzo; Instituto de Medicina Fisica e Reabilitacao, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil ; Departamento de Medicina Legal, Bioética, Medicina do Trabalho e Medicina Física e Reabilitação, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
Fregni, Felipe; Neuromodulation Center, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, United States
Language :
English
Title :
Neurophysiological biomarkers of motor improvement from Constraint-Induced Movement Therapy and Robot-Assisted Therapy in participants with stroke.
Adeyemo B. O. Simis M. Macea D. D. Fregni F. (2012). Systematic review of parameters of stimulation, clinical trial design characteristics, and motor outcomes in non-invasive brain stimulation in stroke. Front. Psych. 3:88. doi: 10.3389/fpsyt.2012.00088, PMID: 23162477
Ammann C. Spampinato D. Márquez-Ruiz J. (2016). Modulating motor learning through transcranial direct-current stimulation: an integrative view. Front. Psychol. 7:1981. doi: 10.3389/fpsyg.2016.01981, PMID: 28066300
Aronson J. K. Ferner R. E. (2017). Biomarkers—a general review. Curr Protoc Pharmacol. 76, 9.23.1–9.23.17. doi: 10.1002/cpph.19, PMID: 37375087
Bentes C. Peralta A. R. Viana P. Martins H. Morgado C. Casimiro C. et al. (2018). Quantitative EEG and functional outcome following acute ischemic stroke. Clin. Neurophysiol. 129, 1680–1687. doi: 10.1016/j.clinph.2018.05.021, PMID: 29935475
Bertani R. Melegari C. De Cola M. C. Bramanti A. Bramanti P. Calabrò R. S. (2017). Effects of robot-assisted upper limb rehabilitation in stroke patients: a systematic review with meta-analysis. Neurol. Sci. 38, 1561–1569. doi: 10.1007/s10072-017-2995-5, PMID: 28540536
Bertolucci F. Chisari C. Fregni F. (2018). The potential dual role of transcallosal inhibition in post-stroke motor recovery. Restor. Neurol. Neurosci. 36, 83–97. doi: 10.3233/RNN-170778, PMID: 29439366
Bolognini N. Vallar G. Casati C. Latif L. A. El-Nazer R. Williams J. et al. (2011). Neurophysiological and behavioral effects of tDCS combined with constraint-induced movement therapy in poststroke patients. Neurorehabil. Neural Repair 25, 819–829. doi: 10.1177/1545968311411056, PMID: 21803933
Calautti C. Leroy F. Guincestre J. Y. Baron J. C. (2003). Displacement of primary sensorimotor cortex activation after subcortical stroke: a longitudinal PET study with clinical correlation. Neuroimage 19, 1650–1654. doi: 10.1016/S1053-8119(03)00205-2, PMID: 12948719
Chatrian G. E. Petersen M. C. Lazarte J. A. (1959). The blocking of the rolandic wicket rhythm and some central changes related to movement. Electroencephalogr. Clin. Neurophysiol. 11, 497–510. doi: 10.1016/0013-4694(59)90048-3, PMID: 13663823
Delorme A. Makeig S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134, 9–21. doi: 10.1016/j.jneumeth.2003.10.009, PMID: 15102499
Di Lazzaro V. Ziemann U. (2013). The contribution of transcranial magnetic stimulation in the functional evaluation of microcircuits in human motor cortex. Front. Neural Circ. 7:18. doi: 10.3389/fncir.2013.00018, PMID: 23407686
Di Pino G. Pellegrino G. Assenza G. Capone F. Ferreri F. Formica D. et al. (2014). Modulation of brain plasticity in stroke: a novel model for neurorehabilitation. Nat. Rev. Neurol. 10, 597–608. doi: 10.1038/nrneurol.2014.162, PMID: 25201238
Finnigan S. P. Walsh M. Rose S. E. Chalk J. B. (2007). Quantitative EEG indices of sub-acute ischaemic stroke correlate with clinical outcomes. Clin. Neurophysiol. 118, 2525–2532. doi: 10.1016/j.clinph.2007.07.021, PMID: 17889600
Fregni F. Boggio P. S. Valle A. C. Rocha R. R. Duarte J. Ferreira M. J. L. et al. (2006). A sham-controlled trial of a 5-day course of repetitive transcranial magnetic stimulation of the unaffected hemisphere in stroke patients. Stroke 37, 2115–2122. doi: 10.1161/01.STR.0000231390.58967.6b, PMID: 16809569
Fregni F. El-Hagrassy M. M. Pacheco-Barrios K. Carvalho S. Leite J. Simis M. et al. (2021). Evidence-based guidelines and secondary meta-analysis for the use of transcranial direct current stimulation in neurological and psychiatric disorders. Int. J. Neuropsychopharmacol. 24, 256–313. doi: 10.1093/ijnp/pyaa051, PMID: 32710772
Fugl-Meyer A. R. Jääskö L. Leyman I. Olsson S. Steglind S. (1975). The post-stroke hemiplegic patient. 1. A method for evaluation of physical performance. Scand. J. Rehabil. Med. 7, 13–31. doi: 10.2340/1650197771331, PMID: 1135616
GBD 2016 Neurology Collaborators (2019). Global, regional, and national burden of neurological disorders, 1990-2016: a systematic analysis for the global burden of disease study 2016. Lancet Neurol. 18, 459–480. doi: 10.1016/S1474-4422(18)30499-X, PMID: 30879893
Inamoto T. Ueda M. Ueno K. Shiroma C. Morita R. Naito Y. et al. (2023). Motor-related mu/beta rhythm in older adults: a comprehensive review. Brain Sci. 13:751. doi: 10.3390/brainsci13050751, PMID: 37239223
Lee J. Lee A. Kim H. Shin M. Yun S. M. Jung Y. et al. (2019). Different brain connectivity between responders and nonresponders to dual-mode noninvasive brain stimulation over bilateral primary motor cortices in stroke patients. Neural Plast. 2019:3826495. doi: 10.1155/2019/3826495, PMID: 31093270
Levin M. F. Kleim J. A. Wolf S. L. (2009). What do motor ‘recovery’ and ‘compensation’ mean in patients following stroke? Neurorehabil. Neural Repair 23, 313–319. doi: 10.1177/1545968308328727, PMID: 19118128
Li M. Xu G. Xie J. Chen C. (2018). A review: motor rehabilitation after stroke with control based on human intent. Proc. Inst. Mech. Eng. H 232, 344–360. doi: 10.1177/0954411918755828, PMID: 29409401
Lin K. Hsieh Y. W. Wu C. Y. Chen C. L. Jang Y. Liu J. S. (2009). Minimal detectable change and clinically important difference of the Wolf Motor function test in stroke patients. Neurorehabil. Neural Repair 23, 429–434. doi: 10.1177/1545968308331144, PMID: 19289487
McDonnell M. N. Stinear C. M. (2017). TMS measures of motor cortex function after stroke: a meta-analysis. Brain Stimul. 10, 721–734. doi: 10.1016/j.brs.2017.03.008, PMID: 28385535
Murase N. Duque J. Mazzocchio R. Cohen L. (2004). Influence of interhemispheric interactions on motor function in chronic stroke. Ann. Neurol. 55, 400–409. doi: 10.1002/ana.10848, PMID: 14991818
Page S. J. Levine P. Hade E. (2012). Psychometric properties and administration of the wrist/hand subscales of the Fugl-Meyer assessment in minimally impaired upper extremity hemiparesis in stroke. Arch. Phys. Med. Rehabil. 93, 2373–2376.e5. doi: 10.1016/j.apmr.2012.06.017, PMID: 22759831
Pereira N. D. Michaelsen S. M. Menezes I. S. Ovando A. C. Lima R. C. M. Teixeira-Salmela L. F. (2011). Reliability of the Brazilian version of the wolf motor function test in adults with hemiparesis. Rev. Bras. Fisioter. 15, 257–265. doi: 10.1590/S1413-35552011000300013, PMID: 21829991
Pfurtscheller G. Andrew C. (1999). Event-related changes of band power and coherence: methodology and interpretation. J. Clin. Neurophysiol. 16, 512–519. doi: 10.1097/00004691-199911000-00003, PMID: 10600019
Pineiro R. Pendlebury S. Johansen-Berg H. Matthews P. M. (2001). Functional MRI detects posterior shifts in primary sensorimotor cortex activation after stroke: evidence of local adaptive reorganization? Stroke 32, 1134–1139. doi: 10.1161/01.STR.32.5.1134, PMID: 11340222
Rossini P. M. Caltagirone C. Castriota-Scanderbeg A. Cicinelli P. Del Gratta C. Demartin M. et al. (1998). Hand motor cortical area reorganization in stroke: a study with fMRI, MEG and TCS maps. Neuroreport 9, 2141–2146. doi: 10.1097/00001756-199806220-00043, PMID: 9674609
Rosso C. Perlbarg V. Valabregue R. Obadia M. Kemlin-Méchin C. Moulton E. et al. (2017). Anatomical and functional correlates of cortical motor threshold of the dominant hand. Brain Stimul. 10, 952–958. doi: 10.1016/j.brs.2017.05.005, PMID: 28551318
Sheorajpanday R. V. A. Nagels G. Weeren A. J. T. M. van Putten M. J. A. M. De Deyn P. P. (2009). Reproducibility and clinical relevance of quantitative EEG parameters in cerebral ischemia: a basic approach. Clin. Neurophysiol. 120, 845–855. doi: 10.1016/j.clinph.2009.02.171, PMID: 19375386
Simis M. Di Lazzaro V. Kirton A. Pennisi G. Bella R. Kim Y. H. et al. (2016). Neurophysiological measurements of affected and unaffected motor cortex from a cross-sectional, multi-center individual stroke patient data analysis study. Neurophysiol. Clin. 46, 53–61. doi: 10.1016/j.neucli.2016.01.003, PMID: 26970808
Simis M. Doruk D. Imamura M. Anghinah R. Morales-Quezada L. Fregni F. et al. (2016). Neurophysiologic predictors of motor function in stroke. Restor. Neurol. Neurosci. 34, 45–54. doi: 10.3233/RNN-150550, PMID: 26518670
Simis M. Imamura M. Sampaio de Melo P. Marduy A. Battistella L. Fregni F. (2021). Deficit of inhibition as a marker of neuroplasticity (DEFINE study) in rehabilitation: a longitudinal cohort study protocol. Front. Neurol. 12:695406. doi: 10.3389/fneur.2021.695406
Simis M. Uygur-Kucukseymen E. Pacheco-Barrios K. Battistella L. R. Fregni F. (2020). Beta-band oscillations as a biomarker of gait recovery in spinal cord injury patients: a quantitative electroencephalography analysis. Clin. Neurophysiol. 131, 1806–1814. doi: 10.1016/j.clinph.2020.04.166, PMID: 32540720
Terranova T. T. Simis M. Santos A. C. A. Alfieri F. M. Imamura M. Fregni F. et al. (2021). Robot-assisted therapy and constraint-induced movement therapy for motor recovery in stroke: results from a randomized clinical trial. Front. Neurorobot. 15:684019. doi: 10.3389/fnbot.2021.684019
Thibaut A. Simis M. Battistella L. R. Fanciullacci C. Bertolucci F. Huerta-Gutierrez R. et al. (2017). Using brain oscillations and corticospinal excitability to understand and predict post-stroke motor function. Front. Neurol. 8:187. doi: 10.3389/fneur.2017.00187, PMID: 28539912
Thrane G. Friborg O. Anke A. Indredavik B. (2014). A meta-analysis of constraint-induced movement therapy after stroke. J. Rehabil. Med. 46, 833–842. doi: 10.2340/16501977-1859, PMID: 25182341
Xu J. Branscheidt M. Schambra H. Steiner L. Widmer M. Diedrichsen J. et al. (2019). Rethinking interhemispheric imbalance as a target for stroke neurorehabilitation. Ann. Neurol. 85, 502–513. doi: 10.1002/ana.25452, PMID: 30805956
Yin S. Liu Y. Ding M. (2016). Amplitude of sensorimotor mu rhythm is correlated with BOLD from multiple brain regions: a simultaneous EEG-fMRI study. Front. Hum. Neurosci. 10:364. doi: 10.3389/fnhum.2016.00364, PMID: 27499736
Ziemann U. Lönnecker S. Steinhoff B. J. Paulus W. (1996). The effect of lorazepam on the motor cortical excitability in man. Exp. Brain Res. 109, 127–135. doi: 10.1007/BF00228633, PMID: 8740215