交流情绪强度起着至关重要的生态作用,因为它提供了有关发送者行为的性质和可能性的有价值的信息。如果接收者无法撤退,攻击通常会跟随强烈攻击的信号。4,5人类经常使用面部表情来传达此类信息。6,7,8,9,10,11然而,如何实现这一复杂的信号任务仍然未知。我们使用基于感知的方法解决了这个问题,数据驱动的方法对接收者用来分类六种基本情绪的特定面部运动进行数学建模-“快乐,\"\"惊喜,\"\"恐惧,\"\"厌恶,\"\"愤怒,\"和\"悲伤\"-并在两种不同的文化中判断它们的强度(东亚,西欧;总计n=120)。在这两种文化中,接收器预期的面部表情随着时间的推移动态地表示情绪类别和强度信息,使用多组分组成信号结构。具体来说,情绪增强器比情绪分类器更早或更晚达到峰值,并使用幅度变化表示强度。情感增强器在情感上也比分类器更相似,暗示潜在的广泛的特定信号结构。跨文化分析进一步揭示了可能影响跨文化交流的期望的异同。具体来说,东亚和西欧的接收者对哪些面部运动代表与威胁相关的情绪的高强度有着相似的期望。比如“愤怒”,\"\"厌恶,\"和\"恐惧,“但在那些代表低威胁情绪的人上有所不同,比如快乐和悲伤。一起,我们的结果为复杂的过程提供了新的见解,通过这些过程,面部表情可以通过揭示嵌入在面部表情中的丰富信息来实现复杂的动态信号任务。
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.