ArticleMedical image analysis2021
A structural enriched functional network: An application to predict brain cognitive performance.
Article in Medical image analysis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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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.
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Who cites it
16 citing papers in PubMed.
- Simulation of realistic brain phantoms for susceptibility tensor imaging.Magma (New York, N.Y.) · 2026Article
- A Multimodal Deep Learning Approach for White Matter Shape Prediction in Diffusion MRI Tractography.Human brain mapping · 2025Article
- The Shape of the Brain's Connections Is Predictive of Cognitive Performance: An Explainable Machine Learning Study.Human brain mapping · 2025Review
- Neural Correlates and Adaptive Mechanisms in Vascular Cognitive Impairment: Exploration of a Structure-Function Coupling Network.CNS neuroscience & therapeutics · 2025Article
- TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance.Medical image analysis · 2024Article
- Comparison of local activation, functional connectivity, and structural connectivity in the N-back task.Frontiers in neuroscience · 2024Article
- TractoSCR: a novel supervised contrastive regression framework for prediction of neurocognitive measures using multi-site harmonized diffusion MRI tractography.Frontiers in neuroscience · 2024Article
- A comprehensive survey of complex brain network representation.Meta-radiology · 2023Article
- Preference matrix guided sparse canonical correlation analysis for mining brain imaging genetic associations in Alzheimer's disease.Methods (San Diego, Calif.) · 2023Article
- Integrative analysis of multi-omics and imaging data with incorporation of biological information via structural Bayesian factor analysis.Briefings in bioinformatics · 2023Article
- TSP-GNN: a novel neuropsychiatric disorder classification framework based on task-specific prior knowledge and graph neural network.Frontiers in neuroscience · 2023Article
- Methodological evaluation of individual cognitive prediction based on the brain white matter structural connectome.Human brain mapping · 2022Article
- Multi-task learning based structured sparse canonical correlation analysis for brain imaging genetics.Medical image analysis · 2022Article
- Interpretable temporal graph neural network for prognostic prediction of Alzheimer's disease using longitudinal neuroimaging data.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2021Article
- Identifying highly heritable brain amyloid phenotypes through mining Alzheimer's imaging and sequencing biobank data.Pacific Symposium on Biocomputing. Pacific Symposium on BiocomputingArticle
- Identifying imaging genetic associations via regional morphometricity estimation.Pacific Symposium on Biocomputing. Pacific Symposium on BiocomputingArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The structure-function coupling in brain networks has emerged as an important research topic in modern neuroscience. The structural network could provide the backbone of the functional network. The integration of the functional network with structural information can help us better understand functional communication in the brain. This paper proposed a method to accurately estimate the brain functional network enriched by the structural network from diffusion magnetic resonance imaging. First, we adopted a simplex regression model with graph-constrained Elastic Net to construct the functional networks enriched by the structural network. Then, we compared the constructed network characteristics of this approach with several state-of-the-art competing functional network models. Furthermore, we evaluated whether the structural enriched functional network model improves the performance for predicting the cognitive-behavioral outcomes. The experiments have been performed on 218 participants from the Human Connectome Project database. The results demonstrated that our network model improves network consistency and its predictive performance compared with several state-of-the-art competing functional network models.
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What Socratic 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 Socratic graph.