Contextual effects on smile perception and recognition memory

Understanding Naturalistic Facial Expressions with Deep Learning and Multimodal Large Language Models

This paper provides a comprehensive overview of affective computing systems for facial expression recognition (FER) research in naturalistic contexts. The first section presents an updated account of user-friendly FER toolboxes incorporating state-of-the-art deep learning models and elaborates on their neural architectures, datasets, and performances across domains. These sophisticated FER toolboxes can robustly address a variety of challenges encountered in the wild such as variations in illumination and head pose, which may otherwise impact recognition accuracy. The second section of this paper discusses multimodal large language models (MLLMs) and their potential applications in affective science. MLLMs exhibit human-level capabilities for FER and enable the quantification of various contextual variables to provide context-aware emotion inferences. These advancements have the potential to revolutionize current methodological approaches for studying the contextual influences on emotions, leading to the development of contextualized emotion models.

The reciprocal relationship between smiles and situational contexts

ABSTRACTSmiles provide information about a social partner's affect and intentions during social interaction. Although always encountered within a specific situation, the influence of contextual information on smile evaluation has not been widely investigated. Moreover, little is known about the reciprocal effect of smiles on evaluations of their accompanying situations. In this research, we assessed how different smile types and situational contexts affected participants' social evaluations. In Study 1, 85 participants rated reward, affiliation, and dominance smiles embedded within either enjoyable, polite, or negative (unpleasant) situations. Context had a strong effect on smile ratings, such that smiles in enjoyable situations were rated as more genuine and joyful, as well as indicating less superiority than those in negative situations. In Study 2, 200 participants evaluated the situations that these smiles were perceived within (rather than the smiles themselves). Although situations paired with reward (vs. affiliation) smiles tended to be rated more positively, this effect was absent for negative situations. Ultimately, the findings point toward a reciprocal relationship between smiles and contexts, whereby the face influences evaluations of the situation and vice versa.

More What Duchenne Smiles Do, Less What They Express

We comment on an article by Sheldon et al. from a previous issue of Perspectives (May 2021). They argued that the presence of positive emotion (Hypothesis 1), the intensity of positive emotion (Hypothesis 2), and chronic positive mood (Hypothesis 3) are reliably signaled by the Duchenne smile (DS). We reexamined the cited literature in support of each hypothesis and show that the study findings were mostly inconclusive, irrelevant, incomplete, and/or misread. In fact, there is no single (empirical) article that would unanimously support the idea that DSs function solely as indicators of felt positive affect. Additional evidence is reviewed, suggesting that DSs can be-and often are-displayed deliberately and in the absence of positive feelings. Although DSs may lead to favorable interpersonal perceptions and positive emotional responses in the observer, we propose a functional view that focuses on what facial actions-here specifically DSs-do rather than what they express.