ArticleScientific reports2019
A Novel Joint Brain Network Analysis Using Longitudinal Alzheimer's Disease Data.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Hippocampal neural circuit mechanisms in Alzheimer's disease revealed by viral-genetic circuit mapping.Neurobiology of disease · 2025Review
- Multi-GWAS reveals significant genomic regions for Mungbean yellow mosaic India virus resistance in urdbean (Vigna mungo (L.) across multiple environments.Plant cell reports · 2024Article
- Hub overload and failure as a final common pathway in neurological brain network disorders.Network neuroscience (Cambridge, Mass.) · 2024Review
- Multi-task Learning with High-Dimensional Noisy Images.Journal of the American Statistical Association · 2024Article
- Alzheimer's Disease: Insights from Large-Scale Brain Dynamics Models.Brain sciences · 2023Review
- LOCUS: A REGULARIZED BLIND SOURCE SEPARATION METHOD WITH LOW-RANK STRUCTURE FOR INVESTIGATING BRAIN CONNECTIVITY.The annals of applied statistics · 2023Article
- Identification of Alzheimer's Disease Progression Stages Using Topological Measures of Resting-State Functional Connectivity Networks: A Comparative Study.Behavioural neurology · 2022Article
- Functional Connectivity and Complexity in the Phenomenological Model of Mild Cognitive-Impaired Alzheimer's Disease.Frontiers in computational neuroscience · 2022Article
- Memory for the Future: Psychodynamic Approach to Time and Self Through the Default Network.Frontiers in human neuroscience · 2022Article
- Disentangling the Molecular Pathways of Parkinson's Disease using Multiscale Network Modeling.Trends in neurosciences · 2021Review
- Bayesian Joint Modeling of Multiple Brain Functional Networks.Journal of the American Statistical Association · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
There is well-documented evidence of brain network differences between individuals with Alzheimer's disease (AD) and healthy controls (HC). To date, imaging studies investigating brain networks in these populations have typically been cross-sectional, and the reproducibility of such findings is somewhat unclear. In a novel study, we use the longitudinal ADNI data on the whole brain to jointly compute the brain network at baseline and one-year using a state of the art approach that pools information across both time points to yield distinct visit-specific networks for the AD and HC cohorts, resulting in more accurate inferences. We perform a multiscale comparison of the AD and HC networks in terms of global network metrics as well as at the more granular level of resting state networks defined under a whole brain parcellation. Our analysis illustrates a decrease in small-worldedness in the AD group at both the time points and also identifies more local network features and hub nodes that are disrupted due to the progression of AD. We also obtain high reproducibility of the HC network across visits. On the other hand, a separate estimation of the networks at each visit using standard graphical approaches reveals fewer meaningful differences and lower reproducibility.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.