ArticleFrontiers in aging neuroscience2024
Reorganized brain functional network topology in stable and progressive mild cognitive impairment.
Article in Frontiers in aging neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Rs-fMRI reveals that taVNS improves cognitive and emotional function in mild cognitive impairment by reconfiguration of "sensory relay-salience-default" cross-network effective connectivity: a randomized, double-blind, sham-controlled trial.Frontiers in neurology · 2026Trial
- Electroacupuncture combined with cognitive rehabilitation outperforms cognitive rehabilitation alone in treating post-stroke cognitive impairment: a randomized controlled trial.Frontiers in neurology · 2025Article
- Hubs, influencers, and communities of executive functions: a task-based fMRI graph analysis.Frontiers in human neuroscience · 2025Article
- Disruption of global brain network topology in amnestic MCI: evidence from multimodal DTI and fMRI.Frontiers in neuroscience · 2025Article
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Authors and funding
9 authors.
Funding
Abstract
aimMild cognitive impairment (MCI) includes two distinct subtypes, namely progressive MCI (pMCI) and stable MCI (sMCI). The objective of this study was to identify the topological reorganization of brain functional networks in patients with pMCI and sMCI. Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) was applied to patients with pMCI, sMCI and healthy controls. Graph theory was applied to study the topological characteristics of the brain's functional networks, examining global and nodal metrics, modularity, and rich-club organization. Analysis of covariance and two sample t-tests were applied to assess differences in topological attributes between patient groups, alongside correlation analysis, which examined the value of changing topological attributes in predicting various clinical outcomes. Results: Significant differences between each group with regard to network metrics were observed. These included clustering coefficients and small-worldness. At the nodal level, several nodes with an abnormal degree centrality and nodal efficiency were detected. In rich club, pMCI and sMCI patients showed declined connectivity compared with HC. Significant differences were observed in the intra- and inter-module connections among the three groups. Particularly noteworthy was the irreplaceable role of the cerebellar module in network interactions. Conclusion: Our study revealed significant differences in network topological properties among sMCI, pMCI and HC patients, which were significantly correlated with cognitive function. Most notably, the cerebellar module played a crucial role in the overall network interactions. In conclusion, these findings could aid in the development of imaging markers used to expedite diagnosis and intervention prior to Alzheimer's disease onset.
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