Abstract
Background:
Impaired movement after stroke is closely associated with altered brain functions, and thus the investigation on neural substrates of patients with stroke can pave a way for not only understanding the underlying mechanisms of neuropathological traits, but also providing an innovative solution for stroke rehabilitation. The objective of this study was to precisely investigate altered brain functions in terms of power spectral and brain network analyses.
Methods:
Altered brain function was investigated by using electroencephalography (EEG) measured while 34 patients with chronic stroke performed movement tasks with the affected and unaffected hands. The relationships between functional brain network indices and Fugl-Meyer Assessment (FMA) scores were also investigated.
Results:
A stronger low-beta event-related desynchronization was found in the contralesional hemisphere for both affected and unaffected movement tasks compared with that of the ipsilesional hemisphere. More efficient whole-brain networks (increased strength and clustering coefficient, and prolonged path length) in the low-beta frequency band were revealed when moving the unaffected hand compared with when moving the affected hand. In addition, the brain network indices of the contralesional hemisphere indicated higher efficiency and cost-effectiveness than those of the ipsilesional hemisphere in both the alpha and low-beta frequency bands. Moreover, the alpha network indices (strength, clustering coefficient, path length, and small-worldness) were significantly correlated with the FMA scores.
Conclusions:
Efficient functional brain network indices are associated with better motor outcomes in patients with stroke and could be useful biomarkers to monitor stroke recovery during rehabilitation.
Impact statement
Even though understanding neuropathological mechanisms in patients with stroke can assist motor rehabilitation, their neuropathological traits have not been fully explored in previous studies. The present study discovered the distinct disruptions of functional brain networks by using electroencephalography data measured during the affected hand movement, and the altered functional networks were significantly correlated with Fugl-Meyer Assessment scores. Our experimental results can provide an in-depth understanding of the neuropathology for patients with stroke, implying that the distinct functional network indices can be potentially used as biomarkers to objectively monitor the degree of motor impairments for patients with stroke during motor rehabilitation.
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