ArticleNeuroImage. Clinical2019
Multiparametric graph theoretical analysis reveals altered structural and functional network topology in Alzheimer's disease.
Article in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 34 citations in OpenAlex.
- Effects of computerized cognitive training on structure‒function coupling and topology of multiple brain networks in people with mild cognitive impairment: a randomized controlled trial.Alzheimer's research & therapy · 2023Trial
- Associations between structural brain alterations and dysfunction across cognitive domains in cerebral small vessel disease: A systematic review and meta-analysis.Neuroimage. Reports · 2026Review
- Local brain connectome parameters across the spectrum of clinical cognitive decline.Frontiers in neuroscience · 2026Article
- Revealing heterogeneity in mild cognitive impairment based on individualized structural covariance network.Alzheimer's research & therapy · 2025Article
- Exploring the changes in functional connectivity of the limbic system in Patients with amnestic mild cognitive impairment treated by acupuncture based on fMRI.Frontiers in neurology · 2025Article
- Article
- Novel Alzheimer's disease subtypes based on functional brain connectivity in human connectome project.Scientific reports · 2024Article
- Functional network centrality indicates interactions between APOE4 and age across the clinical spectrum of Alzheimer's Disease.NeuroImage. Clinical · 2024Article
- Local Brain Network Alterations and Olfactory Impairment in Alzheimer's Disease: An fMRI and Graph-Based Study.Brain sciences · 2023Article
- Support vector machine learning and diffusion-derived structural networks predict amyloid quantity and cognition in adults with Down's syndrome.Neurobiology of aging · 2022Article
- Brain Small-Worldness Properties and Perceived Fatigue in Mild Cognitive Impairment.The journals of gerontology. Series A, Biological sciences and medical sciences · 2022Article
- Cerebral Metabolic Network in Patients With Anti-Frontiers in neuroscience · 2022Article
- Brain Functional Network Analysis of Patients with Primary Angle-Closure Glaucoma.Disease markers · 2022Article
- Topological Abnormalities of Pallido-Thalamo-Cortical Circuit in Functional Brain Network of Patients With Nonchemotherapy With Non-small Cell Lung Cancer.Frontiers in neurology · 2022Article
- Early memory deficits and extensive brain network disorganization in theAging brain · 2022Article
- Persistence of information flow: A multiscale characterization of human brain.Network neuroscience (Cambridge, Mass.) · 2021Article
- Altered Volume and Structural Connectivity of the Hippocampus in Alzheimer's Disease and Amnestic Mild Cognitive Impairment.Frontiers in aging neuroscience · 2021Article
- Altered Topological Properties of Grey Matter Structural Covariance Networks in Complete Thoracic Spinal Cord Injury Patients: A Graph Theoretical Network Analysis.Neural plasticity · 2021Article
- Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation.An international journal on information fusion · 2020Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Alzheimer's disease (AD), an irreversible neurodegenerative disease, is the most common type of dementia in elderly people. This present study incorporated multiple structural and functional connectivity metrics into a graph theoretical analysis framework and investigated alterations in brain network topology in patients with mild cognitive impairment (MCI) and AD. By using this multiparametric analysis, we expected different connectivity metrics may reflect additional or complementary information regarding the topological changes in brain networks in MCI or AD. In our study, a total of 73 subjects participated in this study and underwent the magnetic resonance imaging scans. For the structural network, we compared commonly used connectivity metrics, including fractional anisotropy and normalized streamline count, with multiple diffusivity-based metrics. We compared Pearson correlation and covariance by investigating their sensitivities to functional network topology. Significant disruption of structural network topology in MCI and AD was found predominantly in regions within the limbic system, prefrontal and occipital regions, in addition to widespread alterations of local efficiency. At a global scale, our results showed that the disruption of the structural network was consistent across different edge definitions and global network metrics from the MCI to AD stages. Significant changes in connectivity and tract-specific diffusivity were also found in several limbic connections. Our findings suggest that tract-specific metrics (e.g., fractional anisotropy and diffusivity) provide more sensitive and interpretable measurements than does metrics based on streamline count. Besides, the use of inversed radial diffusivity provided additional information for understanding alterations in network topology caused by AD progression and its possible origins. Use of this proposed multiparametric network analysis framework may facilitate early MCI diagnosis and AD prevention.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.