ArticleBrain communications2025
Determinants of brain network resilience after stroke.
Article in Brain communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Strokes lead to widespread network changes that are associated with functional deficits and subsequent recovery. Beyond function, we hypothesize in this study that stroke-induced reorganization of brain connectivity increases network resilience against recurrent events, as an adaptive mechanism to limit the functional consequences of a new lesion. We used a dataset of 75 first-time stroke patients with resting-state functional connectivity assessed at 3 time-points within 1 year of stroke to determine whether brain networks of stroke patients become more resistant to recurrent lesions. We defined resilience as the ability of brain networks to maintain their core integrative and modular properties following recurrent attacks. Because recurrent strokes are unpredictable in the clinical setting, we probed resilience by comparing whole-brain global efficiency and modularity before and after virtual strokes, which consisted in removing network nodes that overlapped with clinical stroke lesion masks. Global efficiency was chosen as a graph metric to represent network integration, whereas modularity was used as an indicator of the network's modular structure. Both in terms of global efficiency and modularity, we observed greater resilience in patients than in controls. Resilience of global efficiency was greater in patients at 2 weeks and 3 months post primary stroke, whereas resilience of modularity was increased up to 1 year post stroke. We further considered architectural specificities of brain networks that may be associated with resilience, focusing on the distribution of nodal participation coefficient. We found that nodes with high participation coefficient in controls, so called hubs, had lower participation coefficient in stroke patients. Finally, we found that specific patient and primary lesion characteristics were associated with resilience. For instance, we observed increased resilience of global efficiency in younger patients and in those with high scores on the National Institutes of Health Stroke Scale, whereas resilience of modularity was associated with older age. Importantly, there was no association between resilience and primary stroke lesion size. Our results unveil potential connectivity mechanisms of network resilience after stroke that could be targeted by future therapeutic strategies to limit the impact of recurrent lesions.
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