Bayesian vector autoregressive model for multi‐subject effective connectivity inference using multi‐modal neuroimaging data

• Published in: Human brain mapping Vol. 38; no. 3; pp. 1311 - 1332
• Main Authors: Chiang, Sharon, Guindani, Michele, Yeh, Hsiang J., Haneef, Zulfi, Stern, John M., Vannucci, Marina
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.03.2017; John Wiley and Sons Inc
• Subjects: Adult; Bayes Theorem; Bayesian hierarchical model; Brain - diagnostic imaging; Brain Mapping; Computer Simulation; Epilepsy, Temporal Lobe - diagnostic imaging; Female; functional magnetic resonance imaging (fMRI); Humans; Magnetic Resonance Imaging; Male; Models, Neurological; spatial prior; structural MRI; variable selection; vector autoregressive (VAR) model; functional magnetic resonance imaging (fMRI); Bayesian hierarchical model; structural MRI; variable selection; spatial prior; vector autoregressive (VAR) model

In this article a multi‐subject vector autoregressive (VAR) modeling approach was proposed for inference on effective connectivity based on resting‐state functional MRI data. Their framework uses a Bayesian variable selection approach to allow for simultaneous inference on effective connectivity at...