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DOI 10.1111/cns.14178

Медицинская библиотека · CNS neuroscience & therapeutics · 2023

Abnormal characteristic static and dynamic functional network connectivity in idiopathic normal pressure hydrocephalus.

Huang Wenjun, Fang Xuhao, Li Shihong, Mao Renling, Ye Chuntao, Liu Wei, Deng Yao, Lin Guangwu

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

AIMS: Idiopathic Normal pressure hydrocephalus (iNPH) is a neurodegenerative disease characterized by gait disturbance, dementia, and urinary dysfunction. The neural network mechanisms underlying this phenomenon is currently unknown.

METHODS

To investigate the resting-state functional connectivity (rs-FC) abnormalities of iNPH-related brain connectivity from static and dynamic perspectives and the correlation of these abnormalities with clinical symptoms before and 3-month after shunt. We investigated both static and dynamic functional network connectivity (sFNC and dFNC, respectively) in 33 iNPH patients and 23 healthy controls (HCs).

RESULTS

The sFNC and dFNC of networks were generally decreased in iNPH patients. The reduction in sFNC within the default mode network (DMN) and between the somatomotor network (SMN) and visual network (VN) were related to symptoms. The temporal properties of dFNC and its temporal variability in state-4 were sensitive to the identification of iNPH and were correlated with symptoms. The temporal variability in the dorsal attention network (DAN) increased, and the average instantaneous FC was altered among networks in iNPH. These features were partially associated with clinical symptoms.

CONCLUSION

The dFNC may be a more sensitive biomarker for altered network function in iNPH, providing us with extra information on the mechanisms of iNPH.

Для цитирования: Huang Wenjun, Fang Xuhao, Li Shihong, Mao Renling, Ye Chuntao, Liu Wei, Deng Yao, Lin Guangwu. Abnormal characteristic static and dynamic functional network connectivity in idiopathic normal pressure hydrocephalus.. CNS neuroscience & therapeutics. 2023. DOI: 10.1111/cns.14178.

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