Electrophysiological connectivity markers of preserved language functions in post-stroke aphasia

作者：Priyanka P. Shah‐Basak, Gayatri Sivaratnam, Selina Teti, Tiffany Deschamps, Aneta Kielar, Regina Jokel, Jed A. Meltzer · 发表于：NeuroImage Clinical · 年份：2022 · DOI：10.1016/j.nicl.2022.103036 · 被引用次数：14 · 研究领域：Neurobiology of Language and Bilingualism、EEG and Brain-Computer Interfaces、Functional Brain Connectivity Studies

Post-stroke aphasia is a consequence of localized stroke-related damage as well as global disturbances in a highly interactive and bilaterally-distributed language network. Aphasia is increasingly accepted as a network disorder and it should be treated as such when examining the reorganization and recovery mechanisms after stroke. In the current study, we sought to investigate reorganized patterns of electrophysiological connectivity, derived from resting-state magnetoencephalography (rsMEG), in post-stroke chronic (>6 months after onset) aphasia. We implemented amplitude envelope correlations (AEC), a metric of connectivity commonly used to describe slower aspects of interregional communication in resting-state electrophysiological data. The main focus was on identifying the oscillatory frequency bands and frequency-specific spatial topology of connections associated with preserved language abilities after stroke. RsMEG was recorded for 5 min in 21 chronic stroke survivors with aphasia and in 20 matched healthy controls. Source-level MEG activity was reconstructed and summarized within 72 atlas-defined brain regions (or nodes). A 72 × 72 leakage-corrected connectivity (of AEC) matrix was obtained for frequencies from theta to low-gamma (4-50 Hz). Connectivity was compared between groups, and, the correlations between connectivity and subscale scores from the Western Aphasia Battery (WAB) were evaluated in the stroke group, using partial least squares analyses. Posthoc multip...