Facial expressions are of eminent importance for social interaction as they convey information about other individuals' emotions and social intentions. According to the predominant "basic emotion" approach, the perception of emotion in faces is based on the rapid, automatic categorization of prototypical, universal expressions. Consequently, the perception of facial expressions has typically been investigated using isolated, de-contextualized, static pictures of facial expressions that maximize the distinction between categories. However, in everyday life, an individual's face is not perceived in isolation, but almost always appears within a situational context, which may arise from other people, the physical environment surrounding the face, as well as multichannel information from the sender. Furthermore, situational context may be provided by the perceiver, including already present social information gained from affective learning and implicit processing biases such as race bias. Thus, the perception of facial expressions is presumably always influenced by contextual variables. In this comprehensive review, we aim at (1) systematizing the contextual variables that may influence the perception of facial expressions and (2) summarizing experimental paradigms and findings that have been used to investigate these influences. The studies reviewed here demonstrate that perception and neural processing of facial expressions are substantially modified by contextual information, including verbal, visual, and auditory information presented together with the face as well as knowledge or processing biases already present in the observer. These findings further challenge the assumption of automatic, hardwired categorical emotion extraction mechanisms predicted by basic emotion theories. Taking into account a recent model on face processing, we discuss where and when these different contextual influences may take place, thus outlining potential avenues in future research.
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 May 2013.
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#232
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Altmetric has tracked 26,367,306 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
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