An ongoing debate in affective science concerns whether certain discrete, “basic” emotions have evolutionarily based signals that are easily, universally, and innatel...

Do English-speakers think about anger as “red” and sadness as “blue”? Some theories of emotion suggests that color(s) - like other biologically-derived signals- should be reliably paired with an emotion, and that colors should differentiate across emotions. We assessed consistency and specificity for color-emotion pairings among English-speaking adults. In study 1, participants (n = 73) completed an online survey in which they could select up to three colors from 23 colored swatches (varying hue, saturation, and light) for each of ten (...) emotion words. In study 2, different participants (n = 52) completed a similar online survey except that we added additional emotions and colors (which better sampled color space). Participants in both studies indicated the strength of the relationship between a selected color(s) and the emotion. In study 1, four of the ten emotions showed consistency, and about one-third of the colors showed specificity, yet agreement was low-to-moderate among raters even in these cases. When we resampled our data, however, none of these effects were likely to replicate with statistical confidence. In study 2, only two of twenty emotions showed consistency, and three colors showed specificity. As with the first study, no color-emotion pairings were both specific and consistent. In addition, in study 2, we found that saturation and lightness, and to a lesser extent hue, predicted color-emotion agreement rather than perceived color. The results suggest that previous studies which report emotion-color pairings are likely best thought of experiment-specific. The results are discussed with respect to constructionist theories of emotion. (shrink)

ABSTRACTThe six basic emotions have long been considered discrete categories that serve as the primary units of the emotion system. Yet recent evidence indicated underlying connections among them. Here we tested the underlying relationships among the six basic emotions using a perceptual learning procedure. This technique has the potential of causally changing participants’ emotion detection ability. We found that training on detecting a facial expression improved the performance not only on the trained expression but also on other expressions. Such a (...) transfer effect was consistently demonstrated between disgust and anger detection as well as between fear and surprise detection in two experiments. Notably, training on any of the six emotions could improve happiness detection, while sadness detection could only be improved by training on sadness itself, suggesting the uniqueness of happiness and sadness.... (shrink)

It is long known that facial configurations play a critical role when inferring mental and emotional states from others. Nevertheless, there is still a scientific debate on how we infer emotions from facial configurations. The theory of constructed emotion (TCE) suggests that we may infer different emotions from the same facial configuration, depending on the context (e.g. provided by visual and lexical cues) in which they are perceived. For instance, a recent study found that participants were more accurate in inferring (...) mental and emotional states across three different datasets (i.e. RMET, static and dynamic emojis) when words were provided (i.e. forced-choice task), compared to when they were not (i.e. free-labelling task), suggesting that words serve as contexts that modulate the inference from facial configurations. The goal of the current within-subject study was to replicate and extend these findings by adding a fourth dataset (KDEF-dyn), consisting of morphed human faces (to increase the ecological validity). Replicating previous findings, we observed that words increased accuracy across the three (previously used) datasets, an effect that was also observed for the facial morphed stimuli. Our findings are in line with the TCE, providing support for the importance of contextual verbal cues in emotion perception. (shrink)

We report two experimental studies of human perceptions of robotic facial expressions while systematically varying context effects and the cultural background of subjects (n = 93). Except for Fear, East Asian and Western subjects were not significantly different in recognition rates, and, while Westerners were better at judging affect from mouth movement alone, East Asians were not any better at judging affect based on eye/brow movement alone. Moreover, context effects appeared capable of over-riding such cultural differences, most notably for Fear. (...) The results seem to run counter to previous theories of cultural differences in facial expression based on emoticons and eye fixation patterns. We connect this to broader research in cognitive science – suggesting the findings support a dynamical systems view of social cognition as an emergent phenomenon. The results here suggest that, if we can induce appropriate context effects, it may be possible to createculture-neutral modelsof robots and affective interaction. (shrink)

We report two experimental studies of human perceptions of robotic facial expressions while systematically varying context effects and the cultural background of subjects (n = 93). Except for Fear, East Asian and Western subjects were not significantly different in recognition rates, and, while Westerners were better at judging affect from mouth movement alone, East Asians were not any better at judging affect based on eye/brow movement alone. Moreover, context effects appeared capable of over-riding such cultural differences, most notably for Fear. (...) The results seem to run counter to previous theories of cultural differences in facial expression based on emoticons and eye fixation patterns. We connect this to broader research in cognitive science – suggesting the findings support a dynamical systems view of social cognition as an emergent phenomenon. The results here suggest that, if we can induce appropriate context effects, it may be possible to createculture-neutral modelsof robots and affective interaction. (shrink)

Drawing on research reviewed in this special section, the present article discusses how various contextual factors impact on production and decoding of emotion-related facial activity. Although emotion-related variables often contribute to activation of prototypical “emotion expressions” and perceivers can often infer emotional meanings from these facial configurations, neither process is invariant or direct. Many facial movements are directed towards or away from events in the shared environment, and their effects depend on these relational orientations. Facial activity is not only a (...) medium for descriptive representation of internal affective states, but also a means of adjusting to, and operating on, external objects, and of influencing other people’s appraisals of those objects. (shrink)

Do basic emotions produce their predicted facial expressions in nonlaboratory settings? Available studies in naturalistic settings rarely test causation, but do show a surprisingly weak correlation between emotions and their predicted facial expressions. This evidence from field studies is more consistent with facial behavior having many causes, functions, and meanings, as opposed to their being fixed signals of basic emotion.

Huttenlocher et al. (J Exp Psychol Gen 129:220–241, 2000) introduce the category adjustment model (CAM). Given that participants imperfectly remember stimuli (which we refer to as “targets”), CAM holds that participants maximize accuracy by using information about the distribution of the targets to improve their judgments. CAM predicts that judgments will be a weighted average of the imperfect memory of the target and the mean of the distribution of targets. Huttenlocher et al. (2000) report on three experiments and conclude that (...) CAM is “verified”. We attempt to replicate the conditions in Experiment 3 from Huttenlocher et al. (2000). We analyze judgment-level data rather than averaged data. We find evidence of a bias toward a set of recent targets rather than a bias toward the running mean. We do not find evidence of learning. The judgments in our dataset are not consistent with CAM. We discuss other defects in HHV—including dividing by zero. It seems that evidence for CAM is a statistical artifact that appears when researchers analyze data averaged across trials and do not consider a recency bias. (shrink)

In this review, we highlight evidence suggesting that concepts represented in language are used to create a perception of emotion from the constant ebb and flow of other people’s facial muscle movements. In this “construction hypothesis,” (cf. Gendron, Lindquist, Barsalou, & Barrett, 2012) (see also Barrett, 2006b; Barrett, Lindquist, & Gendron, 2007; Barrett, Mesquita, & Gendron, 2011), language plays a constitutive role in emotion perception because words ground the otherwise highly variable instances of an emotion category. We demonstrate that language (...) plays a constitutive role in emotion perception by discussing findings from behavior, neuropsychology, development, and neuroimaging. We close by discussing implications of a constructionist view for the science of emotion. (shrink)

For more than a century expressions have been approached as bidimensional, static, instantaneous, self-contained, well-defined, and universal signals. These assumptions are starting to be empirically reconsidered: this special section of Emotion Review includes reviews on the physical, social, and cultural dynamics of expressions, and on the complex ways in which, throughout the lifespan, facial behavior and emotion are perceived and categorized by primates’ and humans’ brain. All these advances are certainly paving the way for new exciting approaches to facial behavior (...) more likely to strike an appropriate balance between description and explanation. (shrink)