ArticleNeuroImage2011
Functional principal component model for high-dimensional brain imaging.
Article in NeuroImage, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 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.
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Who cites it
29 citing papers in PubMed.
- Variable Selection for Fixed and Random Effects in Multilevel Functional Mixed Effects Models.Statistics in medicine · 2026Article
- Identification of Regions of Interest in Neuroimaging Data With Irregular Boundary Based on Semiparametric Transformation Models and Interval-Censored Outcomes.Statistics in medicine · 2025Article
- Score Test for Functional Markov Process With Image Predictor.Statistics in medicine · 2025Article
- A Latent-Class Model for Time-To-Event Outcomes and High-Dimensional Imaging Data.Statistics in medicine · 2025Article
- Bayesian Estimation of Partial Functional Tobit Censored Quantile Regression Model.Statistics in medicine · 2025Article
- DYNAMIC PREDICTION WITH MULTIVARIATE LONGITUDINAL OUTCOMES AND LONGITUDINAL MAGNETIC RESONANCE IMAGING DATA.The annals of applied statistics · 2025Article
- Supervised Functional Principal Component Analysis Under the Mixture Cure Rate Model: An Application to Alzheimer'S Disease.Statistics in medicine · 2025Article
- Article
- Multi-task Learning with High-Dimensional Noisy Images.Journal of the American Statistical Association · 2024Article
- Supervised two-dimensional functional principal component analysis with time-to-event outcomes and mammogram imaging data.Biometrics · 2023Article
- Multivariate functional mixed model with MRI data: An application to Alzheimer's disease.Statistics in medicine · 2023Article
- Identifying regions of interest in mammogram images.Statistical methods in medical research · 2023Article
- Predicting the onset of breast cancer using mammogram imaging data with irregular boundary.Biostatistics (Oxford, England) · 2023Article
- Principal component analysis of hybrid functional and vector data.Statistics in medicine · 2021Article
- Partial least squares for functional joint models with applications to the Alzheimer's disease neuroimaging initiative study.Biometrics · 2020Article
- Single-shot stereo-polarimetric compressed ultrafast photography for light-speed observation of high-dimensional optical transients with picosecond resolution.Nature communications · 2020Article
- Bayesian Scalar on Image Regression With Nonignorable Nonresponse.Journal of the American Statistical Association · 2020Article
- FGWAS: Functional genome wide association analysis.NeuroImage · 2017Article
- Addressing Confounding in Predictive Models with an Application to Neuroimaging.The international journal of biostatistics · 2016Article
- Lower IgG somatic hypermutation rates during acute dengue virus infection is compatible with a germinal center-independent B cell response.Genome medicine · 2016Article
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
We explore a connection between the singular value decomposition (SVD) and functional principal component analysis (FPCA) models in high-dimensional brain imaging applications. We formally link right singular vectors to principal scores of FPCA. This, combined with the fact that left singular vectors estimate principal components, allows us to deploy the numerical efficiency of SVD to fully estimate the components of FPCA, even for extremely high-dimensional functional objects, such as brain images. As an example, a FPCA model is fit to high-resolution morphometric (RAVENS) images. The main directions of morphometric variation in brain volumes are identified and discussed.
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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.