Study of Cerebellar Network Dynamics in Post-Stroke Aphasia Patients Based on Resting-State Functional Magnetic Resonance Imaging.

Abstract

Background and purpose: This study investigated dynamic cerebellar networks in post-stroke aphasia patients using resting-state fMRI. We examined intra-cerebellar and cerebellar-cortical dynamic functional connectivity quantified their temporal properties and graph-theoretical topology.

Materials and methods: Seventy-seven right-handed patients with post-stroke aphasia and 79 healthy controls underwent underwent 3T resting-state functional MRI. Dynamic cerebellar functional networks were constructed using the Seitzman-27 cerebellar atlas. A sliding-window approach (30 TR window, 1 TR step) was applied, followed by k-means clustering to identify distinct connectivity states. Graph-theoretical analyses were performed to quantify state-specific network topology. Variability of dynamic functional connectivity between cerebellar and cortical regions was calculated. Partial correlation analyses were conducted to examine relationships between dynamic network measures, lesion volume, and language and cognitive function.

Results: Two cerebellar dynamic functional connectivity states were identified in post-stroke aphasia: a predominant segregated state (78.93%) with widespread reductions in connectivity and decreased clustering coefficient (d = -1.29), characteristic path length (d = -0.62), and Local Efficiency (d = -1.11), but higher Global Efficiency (d = 1.06); and a less frequent integrated state (21.07%) with enhanced connectivity and higher Clustering Coefficient (d = 0.57) and Characteristic Path Length (d = 0.70), but diminished Global Efficiency (d = -1.25) and small-worldness (d = -0.92), small-world index (d = -0.89). Post-stroke aphasia showed reduced variability of dynamic functional connectivity between cerebellar and cortical regions involved in language and cognition (Gaussian random field correction, voxel-level p < 0.001, cluster-level p < 0.05). Lesion volume negatively correlated with Aphasia Quotient, Repetition, Memory, Executive Function, and Attention (p < 0.05). State-specific network metrics and variability measures were associated with language and cognitive performance independently of lesion volume.

Conclusions: Post-stroke aphasia patients exhibited a segregated cerebellar state with reduced intra-cerebellar connectivity and efficiency, and an integrated state with enhanced connectivity and small-world properties, together with reduced variability in cerebellar-cortical connections to language-and cognition-related regions. These state-specific network alterations were linked to distinct behavioral domains independently of lesion volume, highlighting a dissociation between structural constraints and dynamic, lesion-independent plasticity.

Abbreviations: PSA = Post-Stroke Aphasia; DFC = Dynamic Functional Connectivity; FPN = Frontoparietal Network; DMN = Default Mode Network; SMN = Somatomotor Network; Eloc = Local Efficiency; Eg = Global Efficiency; Lp = Characteristic Path Length; DAN = Dorsal Attention Network; FDR = False Discovery Rate.