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

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 r...

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Autores principales: Shah-Basak, Priyanka, Sivaratnam, Gayatri, Teti, Selina, Deschamps, Tiffany, Kielar, Aneta, Jokel, Regina, Meltzer, Jed A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9111985/
https://www.ncbi.nlm.nih.gov/pubmed/35561556
http://dx.doi.org/10.1016/j.nicl.2022.103036
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author Shah-Basak, Priyanka
Sivaratnam, Gayatri
Teti, Selina
Deschamps, Tiffany
Kielar, Aneta
Jokel, Regina
Meltzer, Jed A.
author_facet Shah-Basak, Priyanka
Sivaratnam, Gayatri
Teti, Selina
Deschamps, Tiffany
Kielar, Aneta
Jokel, Regina
Meltzer, Jed A.
author_sort Shah-Basak, Priyanka
collection PubMed
description 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 multiple regression analyses were also conducted on a graph theory measure of node strengths, derived from significant connectivity results, to control for node-wise properties (local spectral power and lesion sizes) and demographic and stroke-related variables. Connectivity among the left hemisphere regions, i.e. those ipsilateral to the stroke lesion, was greatly reduced in stroke survivors with aphasia compared to matched healthy controls in the alpha (8–13 Hz; p = 0.011) and beta (15–30 Hz; p = 0.001) bands. The spatial topology of hypoconnectivity in the alpha vs. beta bands was distinct, revealing a greater involvement of ventral frontal, temporal and parietal areas in alpha, and dorsal frontal and parietal areas in beta. The node strengths from alpha and beta group differences remained significant after controlling for nodal spectral power. AEC correlations with WAB subscales of object naming and fluency were significant. Greater alpha connectivity was associated with better naming performance (p = 0.045), and greater connectivity in both the alpha (p = 0.033) and beta (p = 0.007) bands was associated with better speech fluency performance. The spatial topology was distinct between these frequency bands. The node strengths remained significant after controlling for age, time post stroke onset, nodal spectral power and nodal lesion sizes. Our findings provide important insights into the electrophysiological connectivity profiles (frequency and spatial topology) potentially underpinning preserved language abilities in stroke survivors with aphasia.
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spelling pubmed-91119852022-05-18 Electrophysiological connectivity markers of preserved language functions in post-stroke aphasia Shah-Basak, Priyanka Sivaratnam, Gayatri Teti, Selina Deschamps, Tiffany Kielar, Aneta Jokel, Regina Meltzer, Jed A. Neuroimage Clin Regular Article 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 multiple regression analyses were also conducted on a graph theory measure of node strengths, derived from significant connectivity results, to control for node-wise properties (local spectral power and lesion sizes) and demographic and stroke-related variables. Connectivity among the left hemisphere regions, i.e. those ipsilateral to the stroke lesion, was greatly reduced in stroke survivors with aphasia compared to matched healthy controls in the alpha (8–13 Hz; p = 0.011) and beta (15–30 Hz; p = 0.001) bands. The spatial topology of hypoconnectivity in the alpha vs. beta bands was distinct, revealing a greater involvement of ventral frontal, temporal and parietal areas in alpha, and dorsal frontal and parietal areas in beta. The node strengths from alpha and beta group differences remained significant after controlling for nodal spectral power. AEC correlations with WAB subscales of object naming and fluency were significant. Greater alpha connectivity was associated with better naming performance (p = 0.045), and greater connectivity in both the alpha (p = 0.033) and beta (p = 0.007) bands was associated with better speech fluency performance. The spatial topology was distinct between these frequency bands. The node strengths remained significant after controlling for age, time post stroke onset, nodal spectral power and nodal lesion sizes. Our findings provide important insights into the electrophysiological connectivity profiles (frequency and spatial topology) potentially underpinning preserved language abilities in stroke survivors with aphasia. Elsevier 2022-05-07 /pmc/articles/PMC9111985/ /pubmed/35561556 http://dx.doi.org/10.1016/j.nicl.2022.103036 Text en © 2022 Published by Elsevier Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Shah-Basak, Priyanka
Sivaratnam, Gayatri
Teti, Selina
Deschamps, Tiffany
Kielar, Aneta
Jokel, Regina
Meltzer, Jed A.
Electrophysiological connectivity markers of preserved language functions in post-stroke aphasia
title Electrophysiological connectivity markers of preserved language functions in post-stroke aphasia
title_full Electrophysiological connectivity markers of preserved language functions in post-stroke aphasia
title_fullStr Electrophysiological connectivity markers of preserved language functions in post-stroke aphasia
title_full_unstemmed Electrophysiological connectivity markers of preserved language functions in post-stroke aphasia
title_short Electrophysiological connectivity markers of preserved language functions in post-stroke aphasia
title_sort electrophysiological connectivity markers of preserved language functions in post-stroke aphasia
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9111985/
https://www.ncbi.nlm.nih.gov/pubmed/35561556
http://dx.doi.org/10.1016/j.nicl.2022.103036
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