ArticleHuman brain mapping2023
Predicting sex, age, general cognition and mental health with machine learning on brain structural connectomes.
Article in Human brain mapping, 2023. 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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Who cites it
16 citing papers in PubMed.
- Multimodal MRI prediction of cognitive functioning across the lifespan: separating between-person differences from within-person changes.GeroScience · 2026Article
- General cognitive function and the brain's structural connectome.bioRxiv : the preprint server for biology · 2026Article
- White Matter Bundle Reconstruction From Single-Shell Diffusion Magnetic Resonance Imaging: Test-Retest Reliability and Predictive Capability Across Orientation Distribution Function Reconstruction Methods.Human brain mapping · 2025Article
- Using deep learning to predict internalizing problems from brain structure in youth.Translational psychiatry · 2025Article
- Relative Strength Variability Measures for Brain Structural Connectomes and Their Relationship With Cognitive Functioning.Human brain mapping · 2025Article
- Using deep learning to predict internalizing problems from brain structure in youth.bioRxiv : the preprint server for biology · 2025Article
- Weak and unstable prediction of personality from the structural connectome.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Brain network fingerprints of Alzheimer's disease risk factors in mouse models with humanized APOE alleles.Magnetic resonance imaging · 2024Article
- Article
- APOE, Immune Factors, Sex, and Diet Interact to Shape Brain Networks in Mouse Models of Aging.bioRxiv : the preprint server for biology · 2024Article
- TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance.Medical image analysis · 2024Article
- Differential predictability of cognitive profiles from brain structure in older males and females.GeroScience · 2024Article
- Prediction of cognitive performance differences in older age from multimodal neuroimaging data.GeroScience · 2024Article
- Classification accuracy of structural and functional connectomes across different depressive phenotypes.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Shared and distinct structural brain networks related to childhood maltreatment and social support: connectome-based predictive modeling.Molecular psychiatry · 2023Article
- Predicting sex, age, general cognition and mental health with machine learning on brain structural connectomes.Human brain mapping · 2023Article
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Authors and funding
10 authors.
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Abstract
There is an increasing expectation that advanced, computationally expensive machine learning (ML) techniques, when applied to large population-wide neuroimaging datasets, will help to uncover key differences in the human brain in health and disease. We take a comprehensive approach to explore how multiple aspects of brain structural connectivity can predict sex, age, general cognitive function and general psychopathology, testing different ML algorithms from deep learning (DL) model (BrainNetCNN) to classical ML methods. We modelled N = 8183 structural connectomes from UK Biobank using six different structural network weightings obtained from diffusion MRI. Streamline count generally provided the highest prediction accuracies in all prediction tasks. DL did not improve on prediction accuracies from simpler linear models. Further, high correlations between gradient attribution coefficients from DL and model coefficients from linear models suggested the models ranked the importance of features in similar ways, which indirectly suggested the similarity in models' strategies for making predictive decision to some extent. This highlights that model complexity is unlikely to improve detection of associations between structural connectomes and complex phenotypes with the current sample size.
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