ArticleFrontiers in computational neuroscience2022
Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease.
Article in Frontiers in computational neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Neural correlates of subjective cognitive decline in Alzheimer's disease: a systematic review of structural and functional brain changes for early diagnosis and intervention.Frontiers in aging neuroscience · 2025Pooled it
- Multiscale characterization and classification of Alzheimer's disease via integration of brain fingerprint radiomics and graph‑theoretical network metrics.Neuroradiology · 2026Article
- Dynamic functional connectivity and transcriptomic signatures reveal stage-dependent brain network dysfunction in Alzheimer's disease spectrum.Alzheimer's research & therapy · 2025Article
- Topological and geometric signatures of brain network dynamics in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Disrupted morphological brain network organization in subjective cognitive decline and mild cognitive impairment.Brain imaging and behavior · 2024Article
- IMOVE: Protocol for a randomized, controlled 2x2 factorial trial of improvisational movement and social engagement interventions in older adults with early Alzheimer's disease.Contemporary clinical trials communications · 2023Article
- Multimodal magnetic resonance imaging on brain structure and function changes in subjective cognitive decline: a mini-review.Frontiers in aging neuroscience · 2023Review
- Use of machine learning to identify functional connectivity changes in a clinical cohort of patients at risk for dementia.Frontiers in aging neuroscience · 2022Article
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9 authors.
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Abstract
Subjective cognitive decline (SCD) is considered to be the preclinical stage of Alzheimer's disease (AD) and has the potential for the early diagnosis and intervention of AD. It was implicated that CSF-tau, which increases very early in the disease process in AD, has a high sensitivity and specificity to differentiate AD from normal aging, and the highly connected brain regions behaved more tau burden in patients with AD. Thus, a highly connected state measured by dynamic functional connectivity may serve as the early changes of AD. In this study, forty-five normal controls (NC), thirty-six individuals with SCD, and thirty-five patients with AD were enrolled to obtain the resting-state functional magnetic resonance imaging scanning. Sliding windows, Pearson correlation, and clustering analysis were combined to investigate the different levels of information transformation states. Three states, namely, the low state, the middle state, and the high state, were characterized based on the strength of functional connectivity between each pair of brain regions. For the global dynamic functional connectivity analysis, statistically significant differences were found among groups in the three states, and the functional connectivity in the middle state was positively correlated with cognitive scales. Furthermore, the whole brain was parcellated into four networks, namely, default mode network (DMN), cognitive control network (CCN), sensorimotor network (SMN), and occipital-cerebellum network (OCN). For the local network analysis, statistically significant differences in CCN for low state and SMN for middle state and high state were found in normal controls and patients with AD. Meanwhile, the differences were also found in normal controls and individuals with SCD. In addition, the functional connectivity in SMN for high state was positively correlated with cognitive scales. Converging results showed the changes in dynamic functional states in individuals with SCD and patients with AD. In addition, the changes were mainly in the high strength of the functional connectivity state.
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