Meta-analysis of functional neuroimaging data using Bayesian nonparametric binary regression

DOI10.1214/11-AOAS523zbMath1243.62123arXiv1206.6674OpenAlexW2125284947MaRDI QIDQ439162

Yu Ryan Yue, Martin A. Lindquist, Ji Meng Loh

Publication date: 1 August 2012

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1206.6674

zbMATH Keywords

Markov chain Monte Carlodata augmentationfMRImeta-analysisbinary responseGaussian Markov random fieldsspatially adaptive smoothing

Mathematics Subject Classification ID

Random fields; image analysis (62M40) Nonparametric regression and quantile regression (62G08) Bayesian inference (62F15) Neural biology (92C20) Biomedical imaging and signal processing (92C55) Numerical analysis or methods applied to Markov chains (65C40)

Related Items

The coordinate-based meta-analysis of neuroimaging data ⋮ A Bayesian hierarchical spatial point process model for multi-type neuroimaging meta-analysis ⋮ Spatial Bayesian variable selection and grouping for high-dimensional scalar-on-image regression ⋮ Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data

Uses Software

• GMRFLib

Cites Work

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• Adaptive spatial smoothing of fMRI images
• Nonparametric binary regression using a Gaussian process prior
• The statistical analysis of fMRI data
• Bayesian nonparametric binary regression via random tessellations
• Smoothing spline ANOVA for exponential families, with application to the Wisconsin epidemiological study of diabetic retinopathy. (The 1994 Neyman Memorial Lecture)
• Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
• Bayesian Semiparametric Intensity Estimation for Inhomogeneous Spatial Point Processes
• The horseshoe estimator for sparse signals
• Markov chain Monte Carlo in conditionally Gaussian state space models
• A Bayesian Approach to Robust Binary Nonparametric Regression
• Local Regression and Likelihood
• 10.1162/15324430152748236
• Generalized Nonlinear Modeling With Multivariate Free-Knot Regression Splines
• Bayesian Measures of Model Complexity and Fit
• Gaussian Markov Random Fields
• Meta Analysis of Functional Neuroimaging Data via Bayesian Spatial Point Processes
• Bayesian Analysis of Binary and Polychotomous Response Data
• Objective Bayesian Inference for the Half-Normal and Half-tDistributions
• Bayesian auxiliary variable models for binary and multinomial regression
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)