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Found 3 papers, 1 papers with code
Algorithmic Identification of Essential Exogenous Nodes for Causal Sufficiency in Brain Networks
In the investigation of any causal mechanisms, such as the brain's causal networks, the assumption of causal sufficiency plays a critical role.
Discovering Dynamic Effective Connectome of Brain with Bayesian Dynamic DAG Learning
However, learning DEC through these methods still faces two main challenges: one with the fundamental impotence of high-dimensional dynamic DAG discovery methods and the other with the low quality of fMRI data.
Brain Effective Connectome based on fMRI and DTI Data: Bayesian Causal Learning and Assessment
By leveraging the DTI data as prior knowledge, we introduce two Bayesian causal discovery frameworks -- the Bayesian GOLEM (BGOLEM) and Bayesian FGES (BFGES) methods -- that offer significantly more accurate and reliable ECs and address the shortcomings of the existing causal discovery methods in discovering ECs based on only fMRI data.
