| Literature DB >> 36185473 |
Yongxin Li1, Zeyun Yu2, Ping Wu2, Jiaxu Chen1.
Abstract
Stroke can be viewed as an acute disruption of an individual's connectome caused by a focal or widespread loss of blood flow. Although individuals exhibit connectivity changes in multiple functional networks after stroke, the neural mechanisms that underlie the longitudinal reorganization of the connectivity patterns are still unclear. The study aimed to determine whether brain network connectivity patterns after stroke can predict longitudinal behavioral outcomes. Nineteen patients with stroke with subcortical lesions underwent two sessions of resting-state functional magnetic resonance imaging scanning at a 1-month interval. By independent component analysis, the functional connectivity within and between multiple brain networks (including the default mode network, the dorsal attention network, the limbic network, the visual network, and the frontoparietal network) was disrupted after stroke and partial recovery at the second time point. Additionally, regression analyses revealed that the connectivity between the limbic and dorsal attention networks at the first time point showed sufficient reliability in predicting the clinical scores (Fugl-Meyer Assessment and Neurological Deficit Scores) at the second time point. The overall findings suggest that functional coupling between the dorsal attention and limbic networks after stroke can be regarded as a biomarker to predict longitudinal clinical outcomes in motor function and the degree of neurological functional deficit. Overall, the present study provided a novel opportunity to improve prognostic ability after subcortical strokes.Entities:
Keywords: functional MRI; functional network connectivity; independent component analysis; recovery prediction; subcortical stroke
Year: 2022 PMID: 36185473 PMCID: PMC9520312 DOI: 10.3389/fnagi.2022.933567
Source DB: PubMed Journal: Front Aging Neurosci ISSN: 1663-4365 Impact factor: 5.702