BVAR-Connect: A Variational Bayes Approach to Multi-Subject Vector Autoregressive Models for Inference on Brain Connectivity Networks - Kook, Jeong Hwan; Vaughn, Kelly A.; DeMaster, Dana M.; Ewing-Cobbs, Linda; Vannucci, Marina (Neuroinformatics (Totowa, N.J.), 2021)
Keywords: Algorithms; Bayes Theorem; Bayesian analysis; Bioinformatics; Biomedical and Life Sciences; Biomedicine; Brain - physiology; Brain Injuries, Traumatic - diagnostic imaging; Brain Mapping - methods; Causality; Child; Computational Biology/Bioinformatics; Computational neuroscience; Computer Appl. in Life Sciences; Diffusion Tensor Imaging - methods; Functional magnetic resonance imaging; Humans; Image Interpretation, Computer-Assisted - methods; Magnetic resonance imaging; Markov analysis; Markov chains; Mathematical models; Methods; Neural networks; Neuroimaging; Neurology; Neurosciences; Software Original Article; Structure-function relationships; Traumatic brain injury; Resting-state fMRI; Bayesian hierarchical models; Variational inference; Autoregressive models; Multi-Modal imaging; Variable selection