The Reorganization of Cerebellar Functional Network Topology in Post-Stroke Aphasia: A Resting-State fMRI Study

Objective: This study investigated cerebellar functional network topology and connectivity in post-stroke aphasia (PSA) using resting-state fMRI and graph theory. We further explored associations between these alterations and language/cognitive functions to clarify the cerebellum’s role in PSA. Materials and Methods: Seventy-three right-handed PSA patients and 75 matched healthy controls underwent 3T rs-fMRI. A cerebellar functional network was constructed using the Seitzman-27 atlas. Graph theory was applied to assess global/local topological properties and functional connectivity (FC). Correlations with language and cognitive performance were analyzed. Results: Although the cerebellar network in PSA preserved a small-world organization (σ > 1), key metrics (σ, γ, λ, clustering coefficient [Cp], local efficiency [Eloc]) were significantly reduced (p < 0.05), indicating impaired network integration and local processing. Cp and Eloc correlated with multiple cognitive and language domains. Nodal centrality was diminished in the default mode network (DMN), frontoparietal network (FPN), cingulo-opercular network (CON), and dorsal sensorimotor network (SMN [Dor]). Specific nodal metrics correlated with fluency, repetition, and disease duration. FC analysis revealed widespread reductions in intra- and inter-network connectivity, primarily involving FPN and DMN. Conclusion: PSA is characterized by cerebellar network disorganization and extensive FC alterations that are closely linked to language and cognitive impairments. Topological metrics such as Cp and Eloc may serve as biomarkers for assessing functional deficits. These findings highlight the cerebellum’s integrative role in higher-order functions beyond motor control and provide a neurobiological basis for targeted neuromodulation or rehabilitation strategies aimed at restoring cerebellar-cortical connectivity in PSA.