Investigation of the heterogeneity of post-stroke apathy using resting-state fMRI

Motivation: Post-stroke apathy (PSA) is a highly heterogeneous disorder, which presents obstacles to the effective diagnosis and treatment. Goal(s): We intended to identify distinct subtypes of PSA and revealed the underlying neurological substrates of PSA heterogeneity. Approach: By comparison between stroke patients and normal controls, abnormal alterations of resting-state functional connectivity (RSFC) were determined and correlated with apathy syndrome. PSA subtypes were identified based on the significant canonical correlates using hierarchical clustering. Results: The best clustering scheme was four clusters and we observed significant group differences in graph theoretic metrics. Impact: Various subtypes displayed distinct characteristics in terms of RSFC and graph theoretic metrics. Our study emphasizes the importance of RSFC of neural network in the evaluation of PSA heterogeneity and provides new insights for future research and therapeutic targets.