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Communicating emotional intensity plays a vital ecological role because it provides valuable information about the nature and likelihood of the sender's behavior. 1,2,3 For example, attack often follows signals of intense aggression if receivers fail to retreat. 4,5 Humans regularly use facial expressions to communicate such information. 6,7,8,9,10,11 Yet how this complex signaling task is achieved remains unknown. We addressed this question using a perception-based, data-driven method to mathematically model the specific facial movements that receivers use to classify the six basic emotions—"happy," "surprise," "fear," "disgust," "anger," and "sad"—and judge their intensity in two distinct cultures (East Asian, Western European; total n = 120). In both cultures, receivers expected facial expressions to dynamically represent emotion category and intensity information over time, using a multi-component compositional signaling structure. Specifically, emotion intensifiers peaked earlier or later than emotion classifiers and represented intensity using amplitude variations. Emotion intensifiers are also more similar across emotions than classifiers are, suggesting a latent broad-plus-specific signaling structure. Cross-cultural analysis further revealed similarities and differences in expectations that could impact cross-cultural communication. Specifically, East Asian and Western European receivers have similar expectations about which facial movements represent high intensity for threat-related emotions, such as "anger," "disgust," and "fear," but differ on those that represent low threat emotions, such as happiness and sadness. Together, our results provide new insights into the intricate processes by which facial expressions can achieve complex dynamic signaling tasks by revealing the rich information embedded in facial expressions. [Display omitted] • Emotion categories and intensity are represented by specific facial movements • Emotion classifier facial movements are highly distinct; intensifiers are not • Emotion classifiers and intensifiers have distinct temporal signatures • Cultural variance in facial signals may impact cross-cultural communication Chen et al. examine how facial expressions dynamically represent emotion category and intensity information. Using a perception-based data-driven method and information-theoretic analyses, they reveal, in two distinct cultures, that facial expressions represent emotion and intensity information using a specific compositional dynamic structure. [ABSTRACT FROM AUTHOR]

Human facial expressions are complex, multi-component signals that can communicate rich information about emotions, 1–5 including specific categories, such as "anger," and broader dimensions, such as "negative valence, high arousal." 6–8 An enduring question is how this complex signaling is achieved. Communication theory predicts that multi-component signals could transmit each type of emotion information—i.e., specific categories and broader dimensions—via the same or different facial signal components, with implications for elucidating the system and ontology of facial expression communication. 9 We addressed this question using a communication-systems-based method that agnostically generates facial expressions and uses the receiver's perceptions to model the specific facial signal components that represent emotion category and dimensional information to them. 10–12 First, we derived the facial expressions that elicit the perception of emotion categories (i.e., the six classic emotions 13 plus 19 complex emotions 3) and dimensions (i.e., valence and arousal) separately, in 60 individual participants. Comparison of these facial signals showed that they share subsets of components, suggesting that specific latent signals jointly represent—i.e., multiplex—categorical and dimensional information. Further examination revealed these specific latent signals and the joint information they represent. Our results—based on white Western participants, same-ethnicity face stimuli, and commonly used English emotion terms—show that facial expressions can jointly represent specific emotion categories and broad dimensions to perceivers via multiplexed facial signal components. Our results provide insights into the ontology and system of facial expression communication and a new information-theoretic framework that can characterize its complexities. [Display omitted] • Examined facial signals of broad-plus-specific emotion categories and dimensions • Used data-driven, perception-based modeling and information-theoretic analyses • Disentangled facial signals that multiplex broad-plus-specific emotion information • Provides insights into facial expression ontology and new methodological framework Liu et al. examine how facial expressions signal broad-plus-specific emotion category and dimensional information. Using a perception-based facial-signal-modeling technique and information-theoretic analyses, they find a latent set of facial signals that can multiplex categorical and dimensional information and a subset uniquely signaling either. [ABSTRACT FROM AUTHOR]