ArticleFrontiers in neuroscience2016
Using Individualized Brain Network for Analyzing Structural Covariance of the Cerebral Cortex in Alzheimer's Patients.
Article in Frontiers in neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed, 44 citations in OpenAlex.
- Global organisation of structural covariance networks derived from parcellated cortical surface area in atypical populations.bioRxiv : the preprint server for biology · 2025Article
- Article
- Altered grey matter structural covariance in chronic moderate-severe traumatic brain injury.Scientific reports · 2024Article
- Brain structural covariance network features are robust markers of early heavy alcohol use.Addiction (Abingdon, England) · 2024Article
- Aberrant individual structure covariance network in patients with mesial temporal lobe epilepsy.Frontiers in neuroscience · 2024Article
- Morphological connectivity differences in Alzheimer's disease correlate with gene transcription and cell-type.Human brain mapping · 2023Article
- Article
- Associations of white matter hyperintensities with networks of gray matter blood flow and volume in midlife adults: A coronary artery risk development in young adults magnetic resonance imaging substudy.Human brain mapping · 2022Article
- Gray matter network properties show distinct associations with CSF p-tau 181 levels and amyloid status in individuals without dementia.Aging brain · 2022Article
- Tau-related grey matter network breakdown across the Alzheimer's disease continuum.Alzheimer's research & therapy · 2021Article
- Gray matter structural networks related toeNeurologicalSci · 2021Article
- Biomarker Extraction Based on Subspace Learning for the Prediction of Mild Cognitive Impairment Conversion.BioMed research international · 2021Article
- Regional radiomics similarity networks (R2SNs) in the human brain: Reproducibility, small-world properties and a biological basis.Network neuroscience (Cambridge, Mass.) · 2021Article
- Single-subject grey matter network trajectories over the disease course of autosomal dominant Alzheimer's disease.Brain communications · 2020Article
- Gender-Related and Hemispheric Effects in Cortical Thickness-Based Hemispheric Brain Morphological Network.BioMed research international · 2020Article
- Classification of Early and Late Mild Cognitive Impairment Using Functional Brain Network of Resting-State fMRI.Frontiers in psychiatry · 2019Article
- Brain Connectivity Based Prediction of Alzheimer's Disease in Patients With Mild Cognitive Impairment Based on Multi-Modal Images.Frontiers in human neuroscience · 2019Article
- Gray Matter Network Disruptions and Regional Amyloid Beta in Cognitively Normal Adults.Frontiers in aging neuroscience · 2018Article
- Impaired Efficiency and Resilience of Structural Network in Spinocerebellar Ataxia Type 3.Frontiers in neuroscience · 2018Article
- Functional and structural connectome properties in the 5XFAD transgenic mouse model of Alzheimer's disease.Network neuroscience (Cambridge, Mass.) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
Cortical thinning patterns in Alzheimer's disease (AD) have been widely reported through conventional regional analysis. In addition, the coordinated variance of cortical thickness in different brain regions has been investigated both at the individual and group network levels. In this study, we aim to investigate network architectural characteristics of a structural covariance network (SCN) in AD, and further to show that the structural covariance connectivity becomes disorganized across the brain regions in AD, while the normal control (NC) subjects maintain more clustered and consistent coordination in cortical atrophy variations. We generated SCNs directly from T1-weighted MR images of individual patients using surface-based cortical thickness data, with structural connectivity defined as similarity in cortical thickness within different brain regions. Individual SCNs were constructed using morphometric data from the Samsung Medical Center (SMC) dataset. The structural covariance connectivity showed higher clustering than randomly generated networks, as well as similar minimum path lengths, indicating that the SCNs are "small world." There were significant difference between NC and AD group in characteristic path lengths (z = -2.97, p < 0.01) and small-worldness values (z = 4.05, p < 0.01). Clustering coefficients in AD was smaller than that of NC but there was no significant difference (z = 1.81, not significant). We further observed that the AD patients had significantly disrupted structural connectivity. We also show that the coordinated variance of cortical thickness is distributed more randomly from one region to other regions in AD patients when compared to NC subjects. Our proposed SCN may provide surface-based measures for understanding interaction between two brain regions with co-atrophy of the cerebral cortex due to normal aging or AD. We applied our method to the AD Neuroimaging Initiative (ADNI) data to show consistency in results with the SMC dataset.
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.