Journal of Alzheimer's disease : JAD · 2025
State-dependent functional network connectivity alterations in post-stroke dementia with subcortical lesions.
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Cai Huaying, Zhang Nan, Jiang Yun, Wu Qianwen, Ni Linhui, Han Guocan, Liaocheng Jiaao, Wu Dan, Zhao Zhiyong
Аннотация
BACKGROUND: Recent studies have revealed disrupted dynamic functional network connectivity (dFNC) in stroke or dementia brains. However, it remains unclear how the dFNC was altered in post-stroke dementia (PSD).
OBJECTIVE: This study aimed to explore PSD-specific alterations in the dFNC and their association with clinical assessments.
METHODS: We included 19 normal controls (NC), 16 PSD, and 20 post-stroke non-dementia (PSND) patients who underwent resting-state functional magnetic resonance imaging scan. Independent component analysis, combined with a sliding-window approach, was employed to calculate dFNC. The cognitive performance was assessed by both Mini-Mental State Examination and MiniCog assessments, which were subsequently used for multiple regression analysis to investigate the relationships with dFNC.
RESULTS: We identified 13 meaningful resting-state networks, and the dFNC among them derived four states exhibiting different connection patterns. In state III with strong connections within high-order networks, PSD and PSND both showed increased connectivity between visual network (VN) and high-order networks relative to NC; in state I with weak connections among all networks, PSD showed weaker connectivity between default mode network (DMN) and executive control network and between VN and DMN compared to PSND. Moreover, the dFNC measures showed significant correlations with cognitive assessments of patients.
CONCLUSIONS: Our findings suggest that PSD-specific functional network connectivity (FNC) alterations are state-dependent, and dFNC reveals a coexistence mechanism of functional impairment and compensation in large-scale brain networks, which is not observed in static FNC. This offers a new perspective to understand the neural mechanisms of PSD.
OBJECTIVE: This study aimed to explore PSD-specific alterations in the dFNC and their association with clinical assessments.
METHODS: We included 19 normal controls (NC), 16 PSD, and 20 post-stroke non-dementia (PSND) patients who underwent resting-state functional magnetic resonance imaging scan. Independent component analysis, combined with a sliding-window approach, was employed to calculate dFNC. The cognitive performance was assessed by both Mini-Mental State Examination and MiniCog assessments, which were subsequently used for multiple regression analysis to investigate the relationships with dFNC.
RESULTS: We identified 13 meaningful resting-state networks, and the dFNC among them derived four states exhibiting different connection patterns. In state III with strong connections within high-order networks, PSD and PSND both showed increased connectivity between visual network (VN) and high-order networks relative to NC; in state I with weak connections among all networks, PSD showed weaker connectivity between default mode network (DMN) and executive control network and between VN and DMN compared to PSND. Moreover, the dFNC measures showed significant correlations with cognitive assessments of patients.
CONCLUSIONS: Our findings suggest that PSD-specific functional network connectivity (FNC) alterations are state-dependent, and dFNC reveals a coexistence mechanism of functional impairment and compensation in large-scale brain networks, which is not observed in static FNC. This offers a new perspective to understand the neural mechanisms of PSD.