Motor imagery is adversely affected by various factors in individuals with multiple sclerosis (MS). However, the impact of MS-related fatigue on motor imagery remains unclear. Our study aimed to compare motor imagery abilities between fatigued and non-fatigued individuals with MS without cognitive impairment.
Methods
This study included 73 individuals with MS, with Expanded Disability Status Scale scores from 0 to 4.5. Participants were divided into 2 groups based on Fatigue Severity Scale scores: ≥4 for Fatigued Group and <4 for Non-fatigued Group. Assessment of motor imagery vividness was done through Kinesthetic and Visual Imagery Questionnaire-20 (KVIQ-20). The Box and Block Test (BBT) and the Timed Up and Go (TUG) were employed for the temporal congruence component.
Results
The mean ages of the Fatigued Group (30.4 ± 9.2 years) and the Non-fatigued Group (31.5 ± 9.8 years) were similar (P = .650). The fatigued Group exhibited significantly lower kinesthetic imagery scores on the KVIQ-20 (P = .028) and significantly lower performance in the BBT (upper extremities) mental chronometry test for both the most affected and least affected sides of the upper extremities (P = .007 and .028, respectively). Additionally, the Fatigued Group showed significantly lower performance in the TUG (lower extremities) mental chronometry test (P = .006).
Conclusion
In fatigued individuals with MS, there is a greater impact on both temporal congruence components and kinesthetic motor imagery abilities. The difference in the temporal congruence component was observed in tests involving both TUG (lower extremities) and BBT (upper extremities), independent of the affected side.
ReichDSLucchinettiCFCalabresiPA.Multiple sclerosis. N Engl J Med. 2018;378:169-180.
2.
Ben-ZachariaAB.Therapeutics for multiple sclerosis symptoms. Mt Sinai J Med. 2011;78(2):176-191.
3.
TacchinoASaioteCBrichettoG, et al. Motor imagery as a function of disease severity in multiple sclerosis: an fMRI study. Front Hum Neurosci. 2018;11:628.
4.
TabriziYMMazhariSNazariMAZangiabadiNSheibaniV.Abnormalities of motor imagery and relationship with depressive symptoms in mildly disabling relapsing-remitting multiple sclerosis. J Neurol Phys Ther. 2014;38(2):111-118.
5.
McAvinueLPRobertsonIH.Measuring motor imagery ability: a review. Eur J Cogn Psychol. 2008;20(2):232-251.
6.
DicksteinRDeutschJE.Motor imagery in physical therapist practice. Phys Ther. 2007;87(7):942-953.
7.
Di RienzoFColletCHoyekNGuillotA. Impact of neurologic deficits on motor imagery: a systematic review of clinical evaluations. Neuropsychol Rev. 2014;24:116-147.
8.
HeremansED’HoogeA MDe BondtSHelsenWFeysP.The relation between cognitive and motor dysfunction and motor imagery ability in patients with multiple sclerosis. Mult Scler. 2012;18(9):1303-1309. doi:10.1177/1352458512437812
9.
AzinMZangiabadiNMoghadas TabriziYIranmaneshFBaneshiMR.Deficiency in mental rotation of upper and lower-limbs in patients with multiple sclerosis and its relation with cognitive functions. Acta Med Iran. 2016;54(8):510-517.
10.
AllaliGLaidetMAssalF, et al. Adapted timed up and go: a rapid clinical test to assess gait and cognition in multiple sclerosis. Eur Neurol. 2012;67(2):116-120. doi:10.1159/000334394
11.
KahramanTSavciSOzdogarAGEDİKZIdimanE.Effects of anxiety on motor imagery ability in patients with multiple sclerosis. Turk J Physiother Rehabi. 2018;29(1):19-26.
12.
PoddaJPedullàLMonti BragadinM, et al. Spatial constraints and cognitive fatigue affect motor imagery of walking in people with multiple sclerosis. Sci Rep. 2020;10(1):21938.
13.
HétuSGrégoireMSaimpontA, et al. The neural network of motor imagery: an ALE meta-analysis. Neurosci Biobehav Rev. 2013;37(5):930-949.
14.
GuillotAColletCNguyenVAMalouinFRichardsCDoyonJ.Brain activity during visual versus kinesthetic imagery: an fMRI study. Hum Brain Map. 2009;30(7):2157-2172.
15.
ChalahMARiachiNAhdabRCréangeALefaucheurJ-PAyacheSS.Fatigue in multiple sclerosis: neural correlates and the role of non-invasive brain stimulation. Front Cell Neurosci. 2015;9:460.
16.
LangleyCMasudaNGodwinSDe MarcoGBruceJ.Dysfunction of basal ganglia functional connectivity associated with subjective and cognitive fatigue in multiple sclerosis. Front Neurosci. 2023;17:1194859.
17.
InduruwaIConstantinescuCSGranB.Fatigue in multiple sclerosis: a brief review. J Neurol Sci. 2012;323(1-2):9-15.
18.
GreinerJSchoenfeldMALiepertJ.Assessment of mental chronometry (MC) in healthy subjects. Arch Gerontol Geriatr. 2014;58(2):226-230.
19.
BeierMGromischESHughesAJ, et al. Proposed cut scores for tests of the Brief International Cognitive Assessment of Multiple Sclerosis (BICAMS). J Neurol Sci. 2017;381:110-116.
20.
OnerOGTotukODoganİGÇelikDDemirS.Evaluation of neuropsychiatric symptoms in patients with multiple sclerosis. Cukurova Med J. 2022;47(1):208-218.
21.
LerdalA. Fatigue severity scale. In: MagginoF, ed. Encyclopedia of Quality of life and Well-being Research. Springer; 2021:1-5.
22.
KruppLBLaRoccaNGMuir-NashJSteinbergAD.The fatigue severity scale: application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol. 1989;46(10):1121-1123.
23.
LakinLDavisBEBinnsCCCurrieKMRenselMR.Comprehensive approach to management of multiple sclerosis: addressing invisible symptoms—a narrative review. Neurol Ther. 2021;10:75-98.
24.
ArmutluKKorkmazNCKeserI, et al. The validity and reliability of the Fatigue Severity Scale in Turkish multiple sclerosis patients. Int J Rehabil Res. 2007;30(1):81-85.
25.
MalouinFRichardsCLJacksonPLLafleurMFDurandADoyonJ.The Kinesthetic and Visual Imagery Questionnaire (KVIQ) for assessing motor imagery in persons with physical disabilities: a reliability and construct validity study. J Neurol Phys Ther. 2007;31(1):20-29.
26.
DilekBAyhanÇYakutY.Kinestetik ve Görsel İmgeleme Anketi-20’nin Türkçe versiyonunun geçerlik ve güvenirliği. J Exerc Ther Rehabil. 2019;6(3):201-210.
27.
MalouinFRichardsCLDurandADoyonJ.Reliability of mental chronometry for assessing motor imagery ability after stroke. Arch Phys Med Rehabil. 2008;89(2):311-319.
28.
JeannerodMFrakV.Mental imaging of motor activity in humans. Curr Opin Neurobiol. 1999;9(6):735-739.
29.
RezaeianMAssadollahiZAzinHKaeidiAAzinM.Assessment of reliability and validity of the mental chronometry task based on the box and block test in multiple sclerosis patients. Iran Red Crescent Med J. 2021;23:9.
30.
SeebacherBReindlMKahramanT.Factors and strategies affecting motor imagery ability in people with multiple sclerosis: a systematic review. Physiotherapy. 2023;118:64-78.
31.
RüdigerSStuckenschneiderTVogtT, et al. Cognitive impairment is reflected by an increased difference between real and imagined timed up and go test performance. Dement Geriatr Cogn Disord. 2017;44(1-2):55-62. doi:10.1159/000477760
32.
DettmersCBenzMLiepertJRockstrohB.Motor imagery in stroke patients, or plegic patients with spinal cord or peripheral diseases. Acta Neurol Scand. 2012;126(4):238-247.
33.
StinsJFSchneiderIKKooleSLBeekPJ.The influence of motor imagery on postural sway: differential effects of type of body movement and person perspective. Adv Cogn Psychol. 2015;11(3):77-83. doi:10.5709/acp-0173-x
34.
GrangeonMGuillotAColletC.Postural control during visual and kinesthetic motor imagery. Appl Psychophysiol Biofeed. 2011;36:47-56.
35.
ArpinDJHeinrichs-GrahamEGehringerJEZabadRWilsonTWKurzMJ.Altered sensorimotor cortical oscillations in individuals with multiple sclerosis suggests a faulty internal model. Hum Brain Map. 2017;38(8):4009-4018.
36.
PreesterHD. 52A radical phenomenology of the body: subjectivity and sensations in body image and body schema. In: AtariaYTanakaSGallagherS, eds. Body Schema and Body Image: New Directions. Oxford University Press; 2021:52-68.
37.
LiepertJMingersDHeesenCBäumerTWeillerC.Motor cortex excitability and fatigue in multiple sclerosis: a transcranial magnetic stimulation study. Mult Scler J. 2005;11(3):316-321.
38.
KruppLB.Fatigue in multiple sclerosis: definition, pathophysiology and treatment. CNS Drugs. 2003;17:225-234.
39.
KruppLBMcLinskeyNMacAllisterWS. Fatigue in multiple sclerosis. Mult Scler Ther. 2007:805-818.
40.
KosslynSMGanisGThompsonWL.Neural foundations of imagery. Nat Rev Neurosci. 2001;2(9):635-642.
41.
ÖztürkBTaşkıranEDemirS, et al. Prevalence and incidence of multiple sclerosis in Turkey: a nationwide epidemiologic study. Mult Scler J. 2024;30(7):790-799.
