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

Abstract

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 minutes 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 gamma (4–128 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.

EEG reveals brain network alterations in chronic aphasia during natural speech listening

“…Our results may seem in contrast with previous studies reporting either stronger connectivity (Snyder et al, 2021) or alteration in alpha-and beta-band networks (P. Shah-Basak et al, 2022) in chronic aphasia. This inconsistency is likely to be due to the chosen measure of connectivity strength, i.e., WPLI vs amplitude or power envelope correlation, and possibly the experimental paradigm, i.e.…”

“…Interestingly, similar findings in chronic aphasia were not reported when amplitude correlation was used as connectivity metric (P. Shah-Basak et al, 2022). In fact, a positive correlation between the alpha-and beta-band network connectivity with fluency score was found, whilst no significant results emerged in other frequency bands.…”

“…In the delta-band, the detected component comprised a cluster over the left temporo-parietal region, likely involving the language area, as well as frontal inter-hemispheric connectivity. Previous research reported a correlation between decrease of cortical activity and speech fluency, whilst there is still contrasting evidence from the network perspective (Fridriksson et al, 2012(Fridriksson et al, , 2015P. Shah-Basak et al, 2022;Woodhead et al, 2017).…”

“…According to resting-state M/EEG-based graph theory studies, the functional brain connectome in acute aphasia features alterations in its geometrical properties, which include reduced network segregation in delta-and theta-band networks at the acute stage compared to healthy condition (Caliandro et al, 2017), and an association between node degree of Broca area and subsequent language improvement (Nicolo et al, 2015). At the chronic stage, patients show left-hemispheric reduction of connectivity strength in alpha-and beta-bands, with an increase in a local low-gamma band subnetwork compared with healthy people (P. Shah-Basak et al, 2022;Snyder et al, 2021).…”

“…Furthermore, left-hemispheric alpha and centro-frontal beta connectivity are reportedly associated with alteration of speech processing (P. Shah-Basak et al, 2022). Despite a certain number of studies involving specific tasks or resting state paradigms, there is a lack of research on the functional network correlates of perception and processing of natural speech in PWA.…”