Predictive coding for the actions and emotions of others and its deficits in autism spectrum disorders
Christian Keysers, Giorgia Silani, Valeria Gazzola
Abstract
Traditionally, the neural basis of social perception has been studied by showing participants brief examples of the actions or emotions of others presented in randomized order to prevent participants from anticipating what others do and feel. This approach is optimal to isolate the importance of information flow from lower to higher cortical areas. The degree to which feedback connections and Bayesian hierarchical predictive coding contribute to how mammals process more complex social stimuli has been less explored, and will be the focus of this review. We illustrate paradigms that start to capture how participants predict the actions and emotions of others under more ecological conditions, and discuss the brain activity measurement methods suitable to reveal the importance of feedback connections in these predictions. Together, these efforts draw a richer picture of social cognition in which predictive coding and feedback connections play significant roles. We further discuss how the notion of predicting coding is influencing how we think of autism spectrum disorder. • Observing predictible actions triggers feedback predictions from premotor cortex. • Feedback attenuates visual responses to predicted actions into prediction errors • Frontal midline structures learn to predict the rewards and punishments to others. • Prevent harm to others depends cingulate predictive signals about the pain of others. • Predictive coding may help understand the heterogeneity of autism spectrum disorders.