ArticleBiometrics2021
Multimodal neuroimaging data integration and pathway analysis.
Article in Biometrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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.
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Who cites it
13 citing papers in PubMed.
- From microfluidics to nanodelivery: artificial intelligence reshapes neuropharmacology research strategies.Frontiers in pharmacology · 2026Review
- Bayesian thresholded modeling for integrating brain node and network predictors.Biostatistics (Oxford, England) · 2025Article
- A novel strategy for detecting multiple mediators in high-dimensional mediation models.Frontiers in psychiatry · 2025Article
- Article
- Network-Assisted Mediation Analysis with High-Dimensional Neuroimaging Mediators.Proceedings of machine learning research · 2024Article
- Neuroimmune mechanisms connecting violence with internalizing symptoms: A high-dimensional multimodal mediation analysis.Human brain mapping · 2024Article
- Multimodal Omics Approaches to Aging and Age-Related Diseases.Phenomics (Cham, Switzerland) · 2024Review
- Mediation Analysis for High-Dimensional Mediators and Outcomes with an Application to Multimodal Imaging Data.Computational statistics & data analysis · 2023Article
- Statistical Learning Methods for Neuroimaging Data Analysis with Applications.Annual review of biomedical data science · 2023Review
- Article
- Discussion on "distributional independent component analysis for diverse neuroimaging modalities" by Ben Wu, Subhadip Pal, Jian Kang, and Ying Guo.Biometrics · 2022Article
- Multimodal data integration via mediation analysis with high-dimensional exposures and mediators.Human brain mapping · 2022Article
- High-dimensional mediation analysis in survival models.PLoS computational biology · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
With advancements in technology, the collection of multiple types of measurements on a common set of subjects is becoming routine in science. Some notable examples include multimodal neuroimaging studies for the simultaneous investigation of brain structure and function and multi-omics studies for combining genetic and genomic information. Integrative analysis of multimodal data allows scientists to interrogate new mechanistic questions. However, the data collection and generation of integrative hypotheses is outpacing available methodology for joint analysis of multimodal measurements. In this article, we study high-dimensional multimodal data integration in the context of mediation analysis. We aim to understand the roles that different data modalities play as possible mediators in the pathway between an exposure variable and an outcome. We propose a mediation model framework with two data types serving as separate sets of mediators and develop a penalized optimization approach for parameter estimation. We study both the theoretical properties of the estimator through an asymptotic analysis and its finite-sample performance through simulations. We illustrate our method with a multimodal brain pathway analysis having both structural and functional connectivity as mediators in the association between sex and language processing.
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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.