| 제목 |
Functional networks of alpha and low-beta EEG bands are associated with motor impairment in stroke |
| 소속 |
Korea University, Department of Electronics and Information1, Seoul National University Bundang Hospital, Department of Rehabilitation Medicine2, Bundang Rusk Rehabilitation Specialty Hospital, Department of Rehabilitation Medicine3 |
| 저자 |
Miseon shim 1, Ga-Young Choi 1, Nam-Jong Paik2, Chaiyoung Lim3, Han-Jeong Hwang 1†, Won-Seok Kim2*† |
Objective: Disruptions in alpha and low-beta frequency bands have been reported in various diseases involving the central nervous system. We investigated the functional activation and networks of stroke patients in alpha and low-beta frequency bands using electroencephalography (EEG) data measured during both affected and unaffected hand-movement.
Methods: Subjects were recruited from two rehabilitation hospitals from June to December 2019. Thirty-four patients with chronic stroke (>6 months after stroke) were included in this study (15 males; mean age, 60.9; range, 29-80). The motor impairment was evaluated by using Fugl-Meyer assessment (FMA). Movement-related EEG was recorded during the repeated mass grasps. A series of EEG recording procedures is composed of 3 s mass grasp, and 3 - 7 s relax, which was repeated 10 times in a single trial. Before performing the task, the resting-state EEG was recorded for 1 minute (eyes open – 30 s, eyes closed – 30 s). To compute weighted whole-brain network indices based on graph theory, a functional connectivity matrix was computed as an essential prerequisite. Among various functional connectivity indices, in this study, phase locking value (PLV) based on Hilbert Transform was computed for alpha and low-beta bands. Three different weighted network indices were evaluated in this study based on graph theory: i) strength, ii) clustering coefficient, and iii) path length.
Results: In alpha and low-beta frequency bands, both strength and clustering coefficients are significantly reduced during the affected hand-movement task compared to unaffected hand-movement task, whereas significantly enhanced path length was found during the affected hand-movement task compared to the unaffected hand-movement task. Network indices of strength and clustering coefficient have positive correlation with FMA scores. In addition, negative correlation is revealed between path length and FMA scores in both frequency bands.
Conclusions: The EEG parameters for functional networks in alphas and low-beta frequency bands are associated with motor impairments in chronic stroke, suggesting these parameters may be a marker of selective motor control after stroke. |
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