Journal of Medicine in Scientific Research (Jan 2019)
Movement-related cortical potential in patients with acute stroke
Abstract
Aim To identify the pattern and side of brain plasticity following acute stroke in patients who recovered and assess motor upper limb function using motor-related cortical potentials. Patients and methods Eleven patients diagnosed with acute ischemic stroke were recruited from in patients and stroke clinic within Ain Shams University Hospital. They were assessed after 2 or more weeks from stroke onset and showed power in finger flexors and extensors of two or more according to Medical Research Council; their motor recovery was assessed by using Fugal–Meyer scale. A high-density 64-channel electroencephalogram connected to an event-related potential software detector is used to record motor-related cortical potential by asking the patient to press on a bottom for an average of 130 presses with a free interval of 3–5 s between each press using the index finger of the paretic hand. Motor potential epoch component was filtered and analyzed regarding amplitude and latency using event-related potential lab within a MATLAB software programmed for analyzing event-related potentials with particular attention to lateralized readiness potentials along cortical areas of interest. Results A total of 11 adult patients completed the study. Three (75%) patients with right-side weakness had potential from the intact side, and one (25%) patients had potential from the lesion side. Six (86%) patients with left-side weakness had potential from the intact side, and one (14%) patients had potential from the lesion side. There was a weak nonassociation between the source of potential and the side of weakness (Cramer's V = 0.13, P = 0.65). Conclusion This study investigated brain activity changes during movement intention and execution of index movement using comprehensive EEG analysis method, which combined indicator mammalian ependymin-related proteins (MERPs) and choroidal neovascularization (CNV) time-frequency mapping. EEG changes in time and time-frequency domains showed different topographical features and might provide comprehensive information for studying movement disorders such as those in a poststroke patient.
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