ArticleHuman brain mapping2014
Connectome-scale assessments of structural and functional connectivity in MCI.
Article in Human brain mapping, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 3 of them syntheses that pooled it.
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
46 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: A systematic review.Human brain mapping · 2021Pooled it
- Reproducible Evaluation of Diffusion MRI Features for Automatic Classification of Patients with Alzheimer's Disease.Neuroinformatics · 2021Pooled it
- Discovering hierarchical common brain networks via multimodal deep belief network.Medical image analysis · 2019Pooled it
- Integrating Time and Frequency Domain Features of fMRI Time Series for Alzheimer's Disease Classification Using Graph Neural Networks.Interdisciplinary sciences, computational life sciences · 2026Article
- Diagnostic classification of children and adolescents with high-functioning autism spectrum disorder based on brain functional network characteristics of the dense individualized and common connectivity-based cortical landmark model.Frontiers in psychiatry · 2026Article
- Core-Periphery Principle Guided State Space Model for Functional Connectome Classification.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2026Article
- A Unified Continuous Staging Framework for Alzheimer's Disease and Lewy Body Dementia via Hierarchical Anatomical Features.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2026Article
- CLASSIFFICATION OF MILD COGNITIVE IMPAIRMENT BASED ON DYNAMIC FUNCTIONAL CONNECTIVITY USING SPATIO-TEMPORAL TRANSFORMER.Proceedings. IEEE International Symposium on Biomedical Imaging · 2025Article
- Compensation versus deterioration across functional networks in amnestic mild cognitive impairment subtypes.GeroScience · 2025Article
- Multimodal fusion model for diagnosing mild cognitive impairment in unilateral middle cerebral artery steno-occlusive disease.Frontiers in aging neuroscience · 2025Article
- Accurate module induced brain network construction for mild cognitive impairment identification with functional MRI.Frontiers in aging neuroscience · 2023Article
- Predicting brain structural network using functional connectivity.Medical image analysis · 2022Article
- Support vector machine learning and diffusion-derived structural networks predict amyloid quantity and cognition in adults with Down's syndrome.Neurobiology of aging · 2022Article
- Multi-Hypergraph Learning-Based Brain Functional Connectivity Analysis in fMRI Data.IEEE transactions on medical imaging · 2020Article
- Inter-Network High-Order Functional Connectivity (IN-HOFC) and its Alteration in Patients with Mild Cognitive Impairment.Neuroinformatics · 2019Article
- Differentiating Alzheimer's Disease from Dementia with Lewy Bodies Using a Deep Learning Technique Based on Structural Brain Connectivity.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2019Article
- A cross-disorder connectome landscape of brain dysconnectivity.Nature reviews. Neuroscience · 2019Review
- Diagnosis and prognosis of Alzheimer's disease using brain morphometry and white matter connectomes.NeuroImage. Clinical · 2019Article
- Visualizing modules of coordinated structural brain atrophy during the course of conversion to Alzheimer's disease by applying methodology from gene co-expression analysis.NeuroImage. Clinical · 2019Article
- Automatic Recognition of fMRI-Derived Functional Networks Using 3-D Convolutional Neural Networks.IEEE transactions on bio-medical engineering · 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.
Funding
Abstract
Mild cognitive impairment (MCI) has received increasing attention not only because of its potential as a precursor for Alzheimer's disease but also as a predictor of conversion to other neurodegenerative diseases. Although MCI has been defined clinically, accurate and efficient diagnosis is still challenging. Although neuroimaging techniques hold promise, compared to commonly used biomarkers including amyloid plaques, tau protein levels and brain tissue atrophy, neuroimaging biomarkers are less well validated. In this article, we propose a connectomes-scale assessment of structural and functional connectivity in MCI via two independent multimodal DTI/fMRI datasets. We first used DTI-derived structural profiles to explore and tailor the most common and consistent landmarks, then applied them in a whole-brain functional connectivity analysis. The next step fused the results from two independent datasets together and resulted in a set of functional connectomes with the most differentiation power, hence named as "connectome signatures." Our results indicate that these "connectome signatures" have significantly high MCI-vs-controls classification accuracy, at more than 95%. Interestingly, through functional meta-analysis, we found that the majority of "connectome signatures" are mainly derived from the interactions among different functional networks, for example, cognition-perception and cognition-action domains, rather than from within a single network. Our work provides support for using functional "connectome signatures" as neuroimaging biomarkers of MCI.
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.