@proceedings {5155,
	title = {Reasoning about the antecedents of emotions: Bayesian causal inference over an intuitive theory of mind},
	volume = {44},
	year = {2022},
	month = {07/2022},
	pages = {854-861},
	address = {Toronto, CA},
	abstract = {It is commonly believed that expressions visually signal rich diagnostic information to human observers. We studied how observers interpret the dynamic expressions that people spontaneously produced during a real-life high-stakes televised game. We find that human observers are remarkably poor at recovering what events elicited others{\textquoteright} facial and bodily expressions. Beyond simple inaccuracy, people{\textquoteright}s causal reasoning exhibits systematic model-based patterns of errors. We show that latent emotion representations can explain people{\textquoteright}s reasoning about the unseen causes of expressions. A hierarchical Bayesian model simulates which events people infer to be the cause of others{\textquoteright} expressions by comparing the emotions inferred from the expressions against the emotions people were predicted to experience in various situations. This causal model provides a close, parameter-free fit to human causal judgments, suggesting that humans interpret expressions in the context of emotion predictions generated by a causally-structured mental model of other minds.},
	keywords = {Affective Cognition, Bayesian Theory of Mind, Causal Reasoning, Emotion Recognition, Emotion Understanding, intuitive theory},
	url = {https://escholarship.org/uc/item/7sn3w3n2},
	author = {Sean Dae Houlihan and Desmond Ong and Maddie Cusimano and Rebecca Saxe}
}
