ArticleNeuroImage2014
Individualized Gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects.
Article in NeuroImage, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed, 92 citations in OpenAlex.
- Identifying neurophenotypes of major depressive disorder through normative model of regional homogeneity.Translational psychiatry · 2026Article
- AI-enabled multimodal neuroimaging for neurotransmitter mapping in normal aging and age-related disease.Frontiers in aging neuroscience · 2026Review
- Estimation of reference curves for brain atrophy and analysis of robustness to machine effects.Scientific reports · 2025Article
- Identifying key brain pathology in bipolar and unipolar depression using a region-specific brain aging trajectories approach: Insights from the Taiwan Aging and Mental Illness Cohort.Psychological medicine · 2025Article
- A generalizable normative deep autoencoder for brain morphological anomaly detection: application to the multi-site StratiBip dataset on bipolar disorder in an external validation framework.Artificial intelligence in medicine · 2025Article
- Smooth Normative Brain Mapping of Three-Dimensional Morphometry Imaging Data Using Skew-Normal Regression.Human brain mapping · 2025Article
- Gray matter volume increase in the retrosplenial/posterior cingulate cortices of blind soccer players.Frontiers in neuroscience · 2025Article
- A generalizable normative deep autoencoder for brain morphological anomaly detection: application to the multi-site StratiBip dataset on bipolar disorder in an external validation framework.bioRxiv : the preprint server for biology · 2024Article
- Individual deviations from normative electroencephalographic connectivity predict antidepressant response.Journal of affective disorders · 2024Article
- Elucidating Multimodal Imaging Patterns in Accelerated Brain Aging: Heterogeneity through a Discriminant Analysis Approach Using the UK Biobank Dataset.Bioengineering (Basel, Switzerland) · 2024Article
- Non-Gaussian normative modelling with hierarchical Bayesian regression.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Age-related vulnerability of the human brain connectome.Molecular psychiatry · 2023Article
- Using normative modeling and machine learning for detecting mild traumatic brain injury from magnetoencephalography data.PLoS computational biology · 2023Article
- Establishing normative data for the evaluation of cognitive performance in Huntington's disease considering the impact of gender, age, language, and education.Journal of neurology · 2023Article
- Mapping human brain charts cross-sectionally and longitudinally.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- The value of arterial spin labelling perfusion MRI in brain age prediction.Human brain mapping · 2023Article
- Normative Modeling using Multimodal Variational Autoencoders to Identify Abnormal Brain Volume Deviations in Alzheimer's Disease.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Predicting aging trajectories of decline in brain volume, cortical thickness and fractional anisotropy in schizophrenia.Schizophrenia (Heidelberg, Germany) · 2023Article
- Independent replication of advanced brain age in mild cognitive impairment and dementia: detection of future cognitive dysfunction.Molecular psychiatry · 2022Article
- Cofluctuation analysis reveals aberrant default mode network patterns in adolescents and youths with autism spectrum disorder.Human brain mapping · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Structural imaging based on MRI is an integral component of the clinical assessment of patients with potential dementia. We here propose an individualized Gaussian process-based inference scheme for clinical decision support in healthy and pathological aging elderly subjects using MRI. The approach aims at quantitative and transparent support for clinicians who aim to detect structural abnormalities in patients at risk of Alzheimer's disease or other types of dementia. Firstly, we introduce a generative model incorporating our knowledge about normative decline of local and global gray matter volume across the brain in elderly. By supposing smooth structural trajectories the models account for the general course of age-related structural decline as well as late-life accelerated loss. Considering healthy subjects' demography and global brain parameters as informative about normal brain aging variability affords individualized predictions in single cases. Using Gaussian process models as a normative reference, we predict new subjects' brain scans and quantify the local gray matter abnormalities in terms of Normative Probability Maps (NPM) and global z-scores. By integrating the observed expectation error and the predictive uncertainty, the local maps and global scores exploit the advantages of Bayesian inference for clinical decisions and provide a valuable extension of diagnostic information about pathological aging. We validate the approach in simulated data and real MRI data. We train the GP framework using 1238 healthy subjects with ages 18-94 years, and predict in 415 independent test subjects diagnosed as healthy controls, Mild Cognitive Impairment and Alzheimer's disease.
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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.