ArticleNeuroImage2019
Quantification of structural brain connectivity via a conductance model.
Article in NeuroImage, 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
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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.
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.
- Multimodal connectivity-based cortical segmentation with graph neural networks.Frontiers in neuroscience · 2026Article
- Impact of tractogram filtering and graph creation for structural connectomics in subjects with Parkinson's disease.Frontiers in human neuroscience · 2026Article
- Multimodal Connectivity-based Cortical Segmentation with Graph Neural Networks.bioRxiv : the preprint server for biology · 2025Article
- Exploratory Correlation of The Human Structural Connectome with Non-MRI Variables in Alzheimer's Disease.bioRxiv : the preprint server for biology · 2023Article
- Interstitial Fluid Behavior and Diseases.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Review
- Conductance-Based Structural Brain Connectivity in Aging and Dementia.Brain connectivity · 2021Article
- Diffusion-informed spatial smoothing of fMRI data in white matter using spectral graph filters.NeuroImage · 2021Article
- Single-participant structural similarity matrices lead to greater accuracy in classification of participants than function in autism in MRI.Molecular autism · 2021Article
- COMPENSATORY BRAIN CONNECTION DISCOVERY IN ALZHEIMER'S DISEASE.Proceedings. IEEE International Symposium on Biomedical Imaging · 2020Article
- Fast Correction of Eddy-Current and Susceptibility-Induced Distortions Using Rotation-Invariant Contrasts.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2020Article
- Exploratory correlation of the human structural connectome with non-MRI variables in Alzheimer's disease.Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Connectomics has proved promising in quantifying and understanding the effects of development, aging and an array of diseases on the brain. In this work, we propose a new structural connectivity measure from diffusion MRI that allows us to incorporate direct brain connections, as well as indirect ones that would not be otherwise accounted for by standard techniques and that may be key for the better understanding of function from structure. From our experiments on the Human Connectome Project dataset, we find that our measure of structural connectivity better correlates with functional connectivity than streamline tractography does, meaning that it provides new structural information related to function. Through additional experiments on the ADNI-2 dataset, we demonstrate the ability of this new measure to better discriminate different stages of Alzheimer's disease. Our findings suggest that this measure is useful in the study of the normal brain structure, and for quantifying the effects of disease on the brain structure.
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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.