Alternations in resting-state neural networks in subacute non-fluent aphasia after stroke: A fNIRS study

Background Post-stroke aphasia is a prevalent and often disabling language impairment. Despite its high incidence, the precise neuropathological mechanisms underlying the condition, as well as the neural substrates that support functional recovery, remain incompletely understood. Understanding these mechanisms is essential for developing targeted rehabilitation strategies. Methods In this study, we employed fNIRS to collect the resting data of three groups of subjects. First, Pearson correlation coefficient analysis was used to calculate the functional connectivity of the whole brain, and then graph theory analysis was used to study the changes in the overall and regional characteristics of the three groups of brain networks. Results Compared with the healthy control (HC) group, the aphasia group exhibited significantly reduced whole-brain functional connectivity and a lower global clustering coefficient. Further nodal analysis revealed alterations in both node degree and nodal efficiency within the aphasia group. Notably, the local efficiency of the right-hemisphere homologue of Broca‘s area and the right dorsolateral prefrontal cortex (DLPFC) was significantly higher than that in the HC group. Furthermore, network hub analysis identified the right supplementary motor area (SMA) as a prominent global hub, demonstrating its elevated centrality within the overall network of the aphasia group. Conclusions This study demonstrates that patients with post-stroke non-fluent aphasia in the subacute stage exhibit significant alterations in brain network topology. These findings provide a novel neurophysiological basis for identifying and refining neuroregulatory targets in aphasia rehabilitation.