Spectral Resting-State EEG (rsEEG) in Chronic Aphasia Is Reliable, Sensitive, and Correlates With Functional Behavior.
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ABSTRACT:
SUBMITTER: Dalton SGH
PROVIDER: S-EPMC8010195 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Linguistic deficits are frequent symptoms among stroke survivors. The neural mechanism of post-stroke aphasia (PSA) was incompletely understood. Recently, resting-state functional magnetic resonance imaging (rs-fMRI) was widely used among several neuropsychological disorders. However, previous rs-fMRI studies of PSA were limited to very small sample size and the absence of reproducibility with different neuroimaging indexes. The present study performed comparisons with static and dynamic amplitude of low-frequency fluctuations (ALFF) and functional connectivity (FC) based on modest sample size (40 PSA and 37 healthy controls). Compared with controls, PSA showed significantly increased static ALFF predominantly in the bilateral supplementary motor area (SMA) and right hippocampus-parahippocampus (R HIP-ParaHip) and decreased static ALFF in right cerebellum. The increased dynamic ALFF in SMA and decreased dynamic ALFF in right cerebellum were also found in PSA. The static and dynamic ALFF in right cerebellum was positively correlated with spontaneous speech. The FC between the SMA and R HIP-ParaHip was significantly stronger in patients than controls and positively correlated with ALFF in bilateral SMA. In addition, the FC between the R HIP-ParaHip and the right temporal was also enhanced in patients and negatively correlated with repetition, naming, and comprehension score. These findings revealed consistently abnormal intrinsic neural activity in SMA and cerebellum, which may underlie linguistic deficits in PSA.
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Project description:Aphasia is characterized by the disability of spontaneous conversation, listening, understanding, retelling, naming, reading, or writing. However, the neural mechanisms of language damage after stroke are still under discussion. This study aimed to investigate the global and nodal characterization of the functional networks in patients with aphasic stroke based on resting-state functional MRI (fMRI). Twenty-four right-handed patients with aphasia after stroke and 19 healthy controls (HC) underwent a 3-TfMRI scan. A whole-brain large-scale functional connectivity network was then constructed based on Power's atlas of 264 functional regions of interest, and the global and nodal topological properties of these networks were analyzed using graph theory approaches. The results showed that patients with aphasia had decreased in small-worldness (sigma), normalized clustering coefficient (gamma), and local efficiency (E loc) values. Furthermore, E loc was positively correlated with language ability, retelling, naming, and listening comprehension in patients with aphasia. Patients with aphasia also had decreased nodal degree and decreased nodal efficiency in the left postcentral gyrus, central opercular cortex, and insular cortex. Our results suggest that the global and local topology attributes were altered by injury in patients with aphasic stroke. We argue that the local efficiency of brain networks might be used as a potential indicator of basic speech function in patients with aphasia.
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