ArticleBrain sciences2019
Estimation of Brain Functional Connectivity in Patients with Mild Cognitive Impairment.
Article in Brain sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Convergent Functional Changes of Default Mode Network in Mild Cognitive Impairment Using Activation Likelihood Estimation.Frontiers in aging neuroscience · 2021Pooled it
- Genetic risk of Alzheimer's disease is associated with loss of brain network segregation in midlife.Communications biology · 2026Article
- Altered Default Mode Network Connectivity in Mild Cognitive Impairment: Insights from Resting-State fMRI Studies.Current Alzheimer research · 2025Review
- Ambient Assisted Living: Scoping Review of Artificial Intelligence Models, Domains, Technology, and Concerns.Journal of medical Internet research · 2022Article
- Brain Knows Who Is on the Same Wavelength: Resting-State Connectivity Can Predict Compatibility of a Female-Male Relationship.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Network change point detection in resting-state functional connectivity dynamics of mild cognitive impairment patients.International journal of clinical and health psychology : IJCHPArticle
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Mild cognitive impairment is defined as greater cognitive decline than expected for a person at a particular age and is sometimes considered a stage between healthy aging and Alzheimer's disease or other dementia syndromes. It is known that functional connectivity patterns change in people with this diagnosis. We studied functional connectivity patterns and functional segregation in a resting-state fMRI paradigm comparing 10 MCI patients and 10 healthy controls matched by education level, age and sex. Ninety ROIs from the automated anatomical labeling (AAL) atlas were selected for functional connectivity analysis. A correlation matrix was created for each group, and a third matrix with the correlation coefficient differences between the two matrices was created. Functional segregation was analyzed with the 3-cycle method, which is novel in studies of this topic. Finally, cluster analyses were also performed. Our results showed that the two correlation matrices were visually similar but had many differences related to different cognitive functions. Differences were especially apparent in the anterior default mode network (DMN), while the visual resting-state network (RSN) showed no differences between groups. Differences in connectivity patterns in the anterior DMN should be studied more extensively to fully understand its role in the differentiation of healthy aging and an MCI diagnosis.
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Registered trials
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