The neural dynamics of hierarchical Bayesian causal inference in multisensory perception

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.

Bibliographic Details
Main Authors: Tim Rohe, Ann-Christine Ehlis, Uta Noppeney
Format: Article
Language:English
Published: Nature Publishing Group 2019-04-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-019-09664-2