Joint Bayesian estimation of voxel activation and inter-regional connectivity in fMRI experiments
DOI10.1007/s11336-020-09727-0zbMath1477.62352OpenAlexW3087147826WikidataQ99573399 ScholiaQ99573399MaRDI QIDQ2065243
Rajarshi Guhaniyogi, Daniel Spencer, Raquel Prado
Publication date: 7 January 2022
Published in: Psychometrika (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11336-020-09727-0
Bayesian inferencegraphical modelingfunctional magnetic resonance imagingPARAFAC decompositionbrain connectivitybrain activationmultiway stick-breaking priortensor response
Bayesian inference (62F15) Biomedical imaging and signal processing (92C55) Applications of statistics to psychology (62P15)
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- Tensor Decompositions and Applications
- A spatiotemporal nonparametric Bayesian model of multi-subject fMRI data
- Regularized 3D functional regression for brain image data via Haar wavelets
- Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem
- Spatial Bayesian variable selection models on functional magnetic resonance imaging time-series data
- The statistical analysis of functional MRI data
- Variable selection using shrinkage priors
- Classification of brain activation via spatial Bayesian variable selection in fMRI regression
- Spike and slab variable selection: frequentist and Bayesian strategies
- Bayesian graphical Lasso models and efficient posterior computation
- A Bayesian Variable Selection Approach Yields Improved Detection of Brain Activation From Complex-Valued fMRI
- The horseshoe estimator for sparse signals
- Multivariate Bayesian Variable Selection and Prediction
- A Bayesian Approach for Estimating Dynamic Functional Network Connectivity in fMRI Data
- Generalized double Pareto shrinkage
- Spatially Varying Coefficient Model for Neuroimaging Data With Jump Discontinuities
- Spatial Bayesian Variable Selection With Application to Functional Magnetic Resonance Imaging
- Tensor Regression with Applications in Neuroimaging Data Analysis
- Interpretation of the Precision Matrix and Its Application in Estimating Sparse Brain Connectivity during Sleep Spindles from Human Electrocorticography Recordings
- Modeling Inter‐Subject Variability in fMRI Activation Location: A Bayesian Hierarchical Spatial Model
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