The neural dynamics of hierarchical Bayesian causal inference in multisensory perception

Abstract

How do we make inferences about the source of sensory signals? Here, the authors use Bayesian causal modeling and measures of neural activity to show how the brain dynamically codes for and combines sensory signals to draw causal inferences.