Facial dynamics as indicators of trustworthiness and cooperative behavior.

Detecting cooperative partners in situations that have financial stakes is crucial to successful social exchange. The authors tested whether humans are sensitive to subtle facial dynamics of counterparts when deciding whether to trust and cooperate. Participants played a 2-person trust game before which the facial dynamics of the other player were manipulated using brief (     

Affect bursts: Dynamic patterns of facial expression.

[Correction Notice: An erratum for this article was reported in Vol 11(4) of Emotion (see record 2011-18271-001). There were several errors in Table 1, and in Table 4 spaces were omitted from the rows between data for anger, fear, sadness, joy, and relief. All versions of this article have been corrected, and the corrections to Table 1 are provided in the erratum.] Affect bursts consist of spontaneous and short emotional expressions in which facial, vocal, and gestural components are highly synchronized. Although the vocal characteristics have been examined in several recent studies, the facial modality remains largely unexplored. This study investigated the facial correlates of affect bursts that expressed five different emotions: anger, fear, sadness, joy, and relief. Detailed analysis of 59 facial actions with the Facial Action Coding System revealed a reasonable degree of emotion differentiation for individual action units (AUs). However, less convergence was shown for specific AU combinations for a limited number of prototypes. Moreover, expression of facial actions peaked in a cumulative-sequential fashion with significant differences in their sequential appearance between emotions. When testing for the classification of facial expressions within a dimensional approach, facial actions differed significantly as a function of the valence and arousal level of the five emotions, thereby allowing further distinction between joy and relief. The findings cast doubt on the existence of fixed patterns of facial responses for each emotion, resulting in unique facial prototypes. Rather, the results suggest that each emotion can be portrayed by several different expressions that share multiple facial actions. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

"Affect bursts: Dynamic patterns of facial expressions": Correction to Krumhuber and Scherer (2011).

Reports an error in "Affect bursts: Dynamic patterns of facial expression" by Eva G. Krumhuber and Klaus R. Scherer (Emotion, 2011, np). There were several errors in Table 1, and in Table 4 spaces were omitted from the rows between data for anger, fear, sadness, joy, and relief. All versions of this article have been corrected, and the corrections to Table 1 are provided in the erratum. (The following abstract of the original article appeared in record 2011-12872-001.) Affect bursts consist of spontaneous and short emotional expressions in which facial, vocal, and gestural components are highly synchronized. Although the vocal characteristics have been examined in several recent studies, the facial modality remains largely unexplored. This study investigated the facial correlates of affect bursts that expressed five different emotions: anger, fear, sadness, joy, and relief. Detailed analysis of 59 facial actions with the Facial Action Coding System revealed a reasonable degree of emotion differentiation for individual action units (AUs). However, less convergence was shown for specific AU combinations for a limited number of prototypes. Moreover, expression of facial actions peaked in a cumulative-sequential fashion with significant differences in their sequential appearance between emotions. When testing for the classification of facial expressions within a dimensional approach, facial actions differed significantly as a function of the valence and arousal level of the five emotions, thereby allowing further distinction between joy and relief. The findings cast doubt on the existence of fixed patterns of facial responses for each emotion, resulting in unique facial prototypes. Rather, the results suggest that each emotion can be portrayed by several different expressions that share multiple facial actions. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Beyond smile dynamics: Mimicry and beliefs in judgments of smiles.

The judgment that a smile is based on “true,” usually positive, feelings affects social interaction. However, the processes underlying the interpretation of a smile as being more or less genuine are not well understood. The aim of the present research was to test predictions of the Simulation of Smiles Model (SIMS) proposed by Niedenthal, Mermillod, Maringer, and Hess (2010). In addition to the perceptual features that can guide the judgment of a smile as genuine, the model identifies the conditions that the judgments rely on: (a) the embodiment of the facial expression and its corresponding state, and (b) beliefs about the situations in which genuine smiles are most often expressed. Results of two studies are consistent with the model in that they confirm the hypotheses that facial mimicry provides feedback that is used to judge the meaning of a smile, and that beliefs about the situations in which a smile occurs guides such judgments when mimicry is inhibited. (PsycINFO Database Record (c) 2011 APA, all rights reserved)