A Bayesian hierarchical framework for modeling brain connectivity for neuroimaging data

DOI10.1111/biom.12433zbMath1419.62322OpenAlexW2113791820WikidataQ31011197 ScholiaQ31011197MaRDI QIDQ5739290

Shuo Chen, Helen S. Mayberg, F. DuBois Bowman

Publication date: 15 July 2016

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4846590

zbMATH Keywords

MCMCBayesian hierarchical modelfunctional connectivitybrain imagingresting-state fMRI

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Biomedical imaging and signal processing (92C55)

Related Items (3)

Estimating large covariance matrix with network topology for high-dimensional biomedical data ⋮ Detection of sparse differential dependent functional brain connectivity ⋮ Detecting and testing altered brain connectivity networks with \(k\)-partite network topology

Cites Work

• Analyzing complex functional brain networks: fusing statistics and network science to understand the brain
• Poisson approximation for dependent trials
• Modeling the Spatial and Temporal Dependence in fMRI Data
• Large-Scale Simultaneous Hypothesis Testing
• A Bayesian Mixture Model for Differential Gene Expression

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