ArticleCNS neuroscience & therapeutics2024
Abnormal characteristic static and dynamic functional network connectivity in idiopathic normal pressure hydrocephalus.
Article in CNS neuroscience & therapeutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Abnormal functional network connectivity mediates the relationship between depressive symptoms and cognitive decline in late-onset depression.Psychological medicine · 2025Article
- Individual-level cortical morphological network analysis in idiopathic normal pressure hydrocephalus: diagnostic and prognostic insights.Fluids and barriers of the CNS · 2025Article
- Aberrant static and dynamic functional network connectivity in patients with noise-induced hearing loss.Quantitative imaging in medicine and surgery · 2025Article
- Abnormal characteristic static and dynamic functional network connectivity in idiopathic normal pressure hydrocephalus.CNS neuroscience & therapeutics · 2024Article
- Altered regional neural activity and functional connectivity in patients with non-communicating hydrocephalus: a resting-state functional magnetic resonance imaging study.Frontiers in neurology · 2024Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
aimsIdiopathic 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.
methodsTo 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).
resultsThe 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.
conclusionThe dFNC may be a more sensitive biomarker for altered network function in iNPH, providing us with extra information on the mechanisms of iNPH.
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