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Motor imagery vividness and symptom severity in Parkinson's disease
Author(s) -
Readman Megan Rose,
Crawford Trevor J.,
Linkenauger Sally A.,
Bek Judith,
Poliakoff Ellen
Publication year - 2023
Publication title -
journal of neuropsychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.85
H-Index - 37
eISSN - 1748-6653
pISSN - 1748-6645
DOI - 10.1111/jnp.12293
Subject(s) - motor imagery , psychology , motor symptoms , physical medicine and rehabilitation , parkinson's disease , mental image , rehabilitation , audiology , disease , electroencephalography , cognition , neuroscience , medicine , brain–computer interface , pathology
Motor imagery (MI), the mental simulation of movement in the absence of overt motor output, has demonstrated potential as a technique to support rehabilitation of movement in neurological conditions such as Parkinson's disease (PD). Existing evidence suggests that MI is largely preserved in PD, but previous studies have typically examined global measures of MI and have not considered the potential impact of individual differences in symptom presentation on MI. The present study investigated the influence of severity of overall motor symptoms, bradykinesia and tremor on MI vividness scores in 44 individuals with mild to moderate idiopathic PD. Linear mixed effects modelling revealed that imagery modality and the severity of left side bradykinesia significantly influenced MI vividness ratings. Consistent with previous findings, participants rated visual motor imagery (VMI) to be more vivid than kinesthetic motor imagery (KMI). Greater severity of left side bradykinesia (but not right side bradykinesia) predicted increased vividness of KMI, while tremor severity and overall motor symptom severity did not predict vividness of MI. The specificity of the effect of bradykinesia to the left side may reflect greater premorbid vividness for the dominant (right) side or increased attention to more effortful movements on the left side of the body resulting in more vivid motor imagery.