The "Duchenne smile", which exposes your crow's feet, was once thought to be an authentic and forgery-proof expression of positive emotion, but it is not so.

More What Duchenne Smiles Do, Less What They Express. Eva G. Krumhuber, Arvid Kappas. Perspectives on Psychological Science, June 17, 2022. https://doi.org/10.1177/17456916211071083

Abstract: 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.

Keywords: Duchenne, smile, facial expression, emotion

This research suggests that frequent Duchenne smiling may ultimately signal eudaimonic (nice, inclined to virtuous behavior) personality, as well as chronic positive mood

Duchenne Smiles as Honest Signals of Chronic Positive Mood. Kennon M. Sheldon, Mike Corcoran, Melanie Sheldon. Perspectives on Psychological Science, February 12, 2021. https://doi.org/10.1177/1745691620959831

Rolf Degen's take: Smiles that involve the eyes are reliable signs of a good-natured personality

Abstract: Chronic positive mood (CPM) has been shown to confer a wide variety of social, functional, and health benefits. Some researchers have argued that humans evolved to feel CPM, which explains why most people report better than neutral mood (the “positivity offset bias”) and why particularly happy people have particularly good outcomes. Here, we argue that the Duchenne smile evolved as an honest signal of high levels of CPM, alerting others to the psychological fitness of the smiler. Duchenne smiles are honest because they express felt positive emotion, making it difficult for unhappy people to produce them. Duchenne smiles enable happy people to signal and cooperate with one another, boosting their advantages. In our literature review, we found (a) that not all Duchenne smiles are “honest,” although producing them in the absence of positive emotion is difficult and often detectable, and (b) that the ability to produce and recognize Duchenne smiles may vary somewhat by a person’s cultural origin. In the final section of the article, we consider behavioral influences on CPM, reviewing research showing that engaging in eudaimonic activity reliably produces CPM, as posited by the eudaimonic-activity model. This research suggests that frequent Duchenne smiling may ultimately signal eudaimonic personality as well as CPM.

Keywords: emotion, affect, evolutionary psychology, Duchenne smiles, chronic positive mood, eudaimonia

Check also A Novel Test of the Duchenne Marker: Smiles After Botulinum Toxin Treatment for Crow’s Feet Wrinkles. Nancy Etcoff, Shannon Stock, Eva G. Krumhuber and Lawrence Ian Reed. Front. Psychol., January 12 2021. https://www.bipartisanalliance.com/search?q=duchenne&max-results=20&by-date=true

Botox for crow feet wrinkles: Smiles were rated as being happier, more felt, more spontaneous, & more intense than those posed by the same patients under the same conditions & instructions in post-treatment photographs

A Novel Test of the Duchenne Marker: Smiles After Botulinum Toxin Treatment for Crow’s Feet Wrinkles. Nancy Etcoff, Shannon Stock, Eva G. Krumhuber and Lawrence Ian Reed. Front. Psychol., January 12 2021. https://doi.org/10.3389/fpsyg.2020.612654

Abstract: Smiles that vary in muscular configuration also vary in how they are perceived. Previous research suggests that “Duchenne smiles,” indicated by the combined actions of the orbicularis oculi (cheek raiser) and the zygomaticus major muscles (lip corner puller), signal enjoyment. This research has compared perceptions of Duchenne smiles with non-Duchenne smiles among individuals voluntarily innervating or inhibiting the orbicularis oculi muscle. Here we used a novel set of highly controlled stimuli: photographs of patients taken before and after receiving botulinum toxin treatment for crow’s feet lines that selectively paralyzed the lateral orbicularis oculi muscle and removed visible lateral eye wrinkles, to test perception of smiles. Smiles in which the orbicularis muscle was active (prior to treatment) were rated as more felt, spontaneous, intense, and happier. Post treatment patients looked younger, although not more attractive. We discuss the potential implications of these findings within the context of emotion science and clinical research on botulinum toxin.

Discussion

Virtually all pre-treatment photographs depicted patients displaying Duchenne smiles. These smiles were rated as being happier, more felt, more spontaneous, and more intense than those posed by the same patients under the same conditions and instructions in post-treatment photographs. The photographs were matched for smile intensity (activity of the zygomatic major muscle pulling the lip corner) suggesting that the differences were due to the inhibition of the orbicularis oculi and not by the activity of zygomatic major.

Patients were also rated as being significantly younger after treatment (by approximately 1 year) likely due to less visible crow’s feet lines. There was no effect of treatment on facial attractiveness ratings. Although some have speculated that a more spontaneous smile would make a face more attractive, past research (Mehu et al., 2007b) also found no difference in ratings of attractiveness for faces displaying Duchenne vs. non-Duchenne smiles. As such, attractiveness might be more dependent on the face structure and skin health than on dynamic features.

Interestingly, we found that ratings of smile quality were dependent on sex. The smiles of female patients were rated as more felt, surprised, spontaneous, and intense as well as less sad. This is consistent with data suggesting that women are more expressive for positive valanced facial actions (McDuff et al., 2017).

These data are consistent with results of previous studies demonstrating that Duchenne smiles are perceived differently than non-Duchenne smiles (Hess and Kleck, 1994; Del Giudice and Colle, 2007; Krumhuber and Manstead, 2009; Mehu et al., 2012; Gunnery et al., 2013). Patients in the pre-treatment photographs—consisting almost exclusively of Duchenne smiles—were perceived as feeling more genuine positive emotion in comparison to post-treatment photographs. These data are also consistent with studies reporting high frequencies of Duchenne smiles in deliberate facial action tasks (Kanade et al., 2000; Krumhuber et al., 2020). Together, these findings suggest that although the Duchenne marker can be posed in the absence of positive affect, it is still perceived by others to be indicative of genuine emotion. Future research may benefit from examining potential limitations in the production or inhibition of the Duchenne marker in facial action tasks. Such work could shed new light on how different elicitation conditions might drive the reliability of this signal (McCullough and Reed, 2016; see also Zloteanu et al., 2020 in the context of surprise expressions).

Our results have several potential implications and caveats. Our study did not support the strongest version of the Duchenne hypothesis—that inhibition of the orbicularis oculi would make the smile signal appear unfelt or weak. Non-Duchenne smiles were rated as less happy, genuine, felt, and spontaneous, though our small treatment effects suggest that the effect was subtle. However, our stimulus patients were instructed to pose “maximum smiles” (maximum zygomatic activation). It may be that more pronounced effects on smile authenticity occur with less intense smiles. In general, these small but statistically significant changes could have practical implications in natural contexts where smiles may be less intense and/or the Duchenne marker may be more conspicuous.

Previous research has shown that the Duchenne marker plays a role in communicating cooperative intent (Mehu et al., 2007a, b; Reed et al., 2012) as well as eliciting cooperation from others (Scharlemman et al., 2001; Brown and Moore, 2002). In light of the results of the current study, it is possible that when the Duchenne marker is absent (in this study through chemodenervation that inhibited the orbicularis oculi muscle and erased visible crow’s feet wrinkles) signals of cooperation may be lessened. If so, augmenting other signals of positive affect such as vocal affect or body language may counter the effects. Future studies can test this idea.

The images used in this study were derived from a clinical trial evaluating the efficacy of botulinum toxin on crow’s feet lines. In order to test our hypothesis, we selected a subset of patients who showed no evidence of crow’s feet lines using the Facial Wrinkle Scale post treatment. The majority of patients in the trial (66%), while having clinical improvement, did not have complete elimination of their dynamic lines. Interestingly, the patients in this trial where dynamic lines were eliminated reported feeling more satisfied with their appearance after treatment than those in whom some movement was preserved (unpublished data, Allergan). This suggests a potential disconnect between the positive perception of the aesthetic outcome on the part of the patient and the subtle negative impact on emotion communication as perceived by the observers. While not within the scope of this paper, this tension warrants further exploration. As reported, perceived smile authenticity did not impact attractiveness ratings, and did make patients appear approximately a year younger.

Three specific limitations must be taken into account when interpreting our findings. First, participants rated static images as opposed to video clips. Video clips have been shown to provide richer emotional content in comparison to static images (Ambadar et al., 2005; see Krumhuber et al., 2013, for a review) and would allow for the analysis of timing characteristics of facial expressions (Ambadar et al., 2009). Second, our sample did not include pre- and post-treatment photographs of spontaneously occurring smiles. That is, we were able to test our primary hypotheses using only deliberate facial action tasks and not when patients were experiencing genuine positive emotion (see Namba et al., 2020, for a similar approach). Future research addressing these limitations could complement the present findings and broaden our understanding of the perceptual and behavioral effects of the Duchenne smile. Third, our study was done solely with participants in the United States. It may be that participants in other cultures will be more impacted by the absence of the Duchenne marker. For example, Yuki et al. (2007) found cultural difference in the use of the eyes and mouth as cues to emotion in Japan and the U.S., with participants in Japan relying more heavily on eye expression for determination of emotion, including happiness, and participants in the U.S. on the mouth.

The Duchenne smile was first reported in 1862 by Duchenne de Boulogne in his “Mechanisme de la Physiognomie Humane.” Duchenne isolated facial muscle action using the novel method of electrical contraction of its muscles. These were the first physiological experiments illustrated by photography. Over 150 years later, we used a pharmacological technique to selectively chemodenervate, and therefore isolate specific facial muscles. In doing so, we shed further light on Duchenne’s pioneering ideas and address current controversies. We find evidence that Duchenne smiles communicate genuine and more intense happiness and that complete inhibition of orbicularis oculi leads to subtle yet statistically significant decreases in such communication.

Perceiver’s Agreeableness & Extraversion were uniquely associated with liking targets; targets who expressed positive emotions, looked relaxed, were physically attractive, & looked healthy & energetic, were the most liked

Who likes whom? The interaction between perceiver personality and target look. Jan Erik Lönnqvist, Ville-Juhani Ilmarinen, Markku Verkasalo. Journal of Research in Personality, Volume 90, February 2021, 104044. https://doi.org/10.1016/j.jrp.2020.104044

Highlights

• We investigated determinants of liking at zero-acquaintance.

• Perceivers (N = 385) viewed portrait photographs of Targets (N = 146)

• Different perceivers were differently influenced by appearance cues.

• Targets who displayed non-Duchenne (fake) smiles were generally rated less favorably.

• Those high in N or C, but not those low in A, especially disliked fake smiles.

Abstract: We investigated determinants of liking at zero-acquaintance, focusing on individual differences in perceivers’ reactions to appearance cues. Perceivers (N = 385) viewed portrait photographs of Targets (N = 146). Perceiver’s Agreeableness and Extraversion were uniquely associated with liking targets. Targets who expressed positive emotions, looked relaxed, were physically attractive, and looked healthy and energetic, were the most liked. There were substantial individual differences in how Perceivers were influenced by appearance cues. For instance, Perceivers generally rated targets who displayed non-Duchenne (fake) smiles less favorably than targets who did not smile or targets who displayed Duchenne (authentic) smiles. However, non-Duchenne smiles elicited especially negative ratings from Perceivers high in Neuroticism or Conscientiousness, but not from Perceivers low in Agreeableness.

Keywords First impressionsZero-acquaintanceAttractivenessSmilingRelationship effects

Respondents rated photographs of patients with facial paralysis significantly lower in likeability, trustworthiness, attractiveness, and femininity or masculinity

Association of Facial Paralysis With Perceptions of Personality and Physical Traits. Keon M. Parsa. JAMA Netw Open. 2020;3(6):e205495, June 24 2020, doi:10.1001/jamanetworkopen.2020.5495

Key Points
Question  How is facial paralysis associated with the perception of attractiveness, femininity or masculinity, and personality, and do patient-reported outcome measures correlate with how patients are perceived by others?

Findings  In this cross-sectional study including 20 patients with facial paralysis and 122 survey respondents, respondents rated photographs of patients with facial paralysis significantly lower in likeability, trustworthiness, attractiveness, and femininity or masculinity compared with the digitally edited images of patients without facial paralysis. Higher social function and total Facial Clinimetric Evaluation scores were associated with increased trustworthiness and attractiveness scores.

Meaning  These results broaden understanding of how facial paralysis is associated with societal perceptions of persona.

Abstract
Importance  Facial paralysis has a significant effect on affect display, with the most notable deficit being patients’ the inability to smile in the same way as those without paralysis. These impairments may result in undesirable judgements of personal qualities, thus leading to a significant social penalty in those who have the condition.

Objective  To quantify the association of facial paralysis with the way smiling patients are perceived by others with respect to personality traits, attractiveness, and femininity or masculinity and to evaluate the potential association of facial palsy–related patient-reported outcome measures with how patients are perceived by others.

Design, Setting, and Participants  This retrospective cross-sectional study used 20 images of smiling patients with facial paralysis evaluated between January 1, 2014, and December 31, 2016. Using photograph editing software, the photographs were edited to create a simulated nonparalysis smiling facial appearance. A total of 40 photographs were split into 4 groups of 10 photographs, each with 5 altered and 5 unaltered photographs. The surveys were designed such that altered and unaltered photographs of the same patient were not placed in the same survey to avoid recall bias. Anonymous raters used a 7-point Likert scale to rate their perception of each patient’s personality traits (ie, aggressiveness, likeability, and trustworthiness), attractiveness, and femininity or masculinity based on photographs in their assigned survey. Raters were blinded to study intent. Scores from the Facial Clinimetric Evaluation questionnaire were included to assess self-perception. Data were analyzed from November 11, 2019, to February 20, 2020.

Main Outcomes and Measures  Ratings of personality traits, attractiveness, and femininity or masculinity. Social function domain scores and overall scores were analyzed from the Facial Clinimetric Evaluation questionnaire.

Results  This study included photographs of 20 patients with facial paralysis (mean [range] age, 54 [28-69] years; 15 [75%] women). A total of 122 respondents completed the survey (71 [61%] women). Most respondents were between the ages of 25 and 34 years (79 participants [65%]). Overall, smiling photos of patients with facial paralysis were perceived as significantly less likeable (difference, −0.29; 95% CI, −0.43 to −0.14), trustworthy (difference, −0.25; 95% CI, −0.39 to −0.11), attractive (difference, −0.47; 95% CI, −0.62 to −0.32), and feminine or masculine (difference, −0.21; 95% CI, −0.38 to −0.03) compared with their simulated preparalysis photographs. When analyzed by sex, smiling women with facial paralysis experienced lower ratings for likeability (difference, −0.34; 95% CI, −0.53 to −0.16), trustworthiness (difference, −0.24; 95% CI, −0.43 to −0.06), attractiveness (difference, −0.74; 95% CI, −0.94 to −0.55), and femininity (difference, −0.35; 95% CI, −0.58 to −0.13). However, smiling men with facial paralysis only received significantly lower ratings for likeability (difference, −0.24; 95% CI, −0.47 to −0.01) and trustworthiness (difference, −0.30; 95% CI, −0.53 to −0.07). As patients’ self-reported social function and total Facial Clinimetric Evaluation scores increased, there was an increase in perceived trustworthiness (rs[480] = 0.11; P = .02) and attractiveness (rs[478] = 0.10; P = .04) scores by raters.

Conclusions and Relevance  In this study, photographs of patients with facial paralysis received lower ratings for several personality and physical traits compared with digitally edited images with no facial paralysis. These findings suggest a social penalty associated with facial paralysis.

Discussion

The Duchenne smile is classically described as the anatomical marker of the genuine smile. The smile is distinctive, with the mouth turning up from the activation of the zygomatic major muscle, the cheeks lifting, and the appearance of wrinkles around the eyes (also known as crow’s feet) associated with simultaneous contraction of the orbicularis oculi. The absence of the Duchenne smile not only influences how people evaluate smiles but also how they are judged by others.^29,30

The findings of this cross-sectional study suggest that the inability to effectively smile is associated with negative perceptions in likeability, trustworthiness, attractiveness, and femininity or masculinity for patients with facial paralysis. Paralysis affecting the mouth is among the most notable of facial asymmetries, such that palsies of the zygomatic and marginal branches of the facial nerve are considered to have a significantly greater need for correction.^11,12 Interestingly, reanimation surgery of the lip significantly decreases the degree of attention to the mouth and can help decrease negative perceptions of patients with facial paralysis.³¹

A universal finding for our patient population was lower perceived trustworthiness for the photographs of patients with facial paralysis vs their digitally altered counterparts. Research in the psychological and social sciences corroborate these findings, such that a happy facial expression makes a person appear more trustworthy.^31,32 Furthermore, having a facial appearance that conveys a positive emotional state enhances trust.^33-35 These findings highlight the social significance of the asymmetric smile and the importance of further progress in the development of techniques to assist in mitigating the effects of facial paralysis.

It is interesting to find that men and women with facial paralysis did not experience the same social penalty with respect to their facial paralysis. The relative decrease in attractiveness and femininity perceived in women with facial paralysis likely reflects the different social expectations by sex in our society. This is consistent with the results reported in a 2019 study³⁶ that suggest that the appearance of a smile is not as integral to the perception of masculinity as it is to femininity.

Lastly, there was a correlation between the way patients with facial paralysis perceived themselves and how they were perceived by others. Specifically, as self-perception of social function and overall facial function improved, there was an increase in perceived trustworthiness and attractiveness by others. This is similar to the results reported by Lyford-Pike et al³⁷ that suggest that higher FaCE scores correspond with decreased perception of disfigurement by patients.

It is important to note that this study included patients with facial paralysis presenting with a range of facial impairment. Not all patients with facial paralysis experienced a significant decrease in the perception of their personality traits, femininity or masculinity, and attractiveness. More research is needed to better understand the different variables that can optimize outcomes at the individual patient level.

Limitations

There are several limitations to this study. This study was performed using static smiling images, but other studies have found that observers judged the severity of paralyzed faces to be more noticeable when viewing dynamic expressions.³⁸ In addition, as this study included only patients willing to have their photos viewed by others, there may have been a selection bias rendering the study patient group to be less reflective of the true gamut of patients with facial paralysis.³⁹

People trust happy-sounding artificial agents more, even in the face of behavioral evidence of untrustworthiness

If your device could smile: People trust happy-sounding artificial agents more. Ilaria Torre, Jeremy Goslin, Laurence White. Computers in Human Behavior, December 9 2019. https://doi.org/10.1016/j.chb.2019.106215

Highlights
• Smiling can be heard in the voice without any visual cue.
• This ‘smiling voice’ elicits higher trusting behaviors than a neutral one.
• The higher trust persists even when the speaker is untrustworthy.
• This has implications for the design of voice-based artificial agents.

Abstract: While it is clear that artificial agents that are able to express emotions increase trust in Human-Machine Interaction, most studies looking at this effect concentrated on the expression of emotions through the visual channel, e.g. facial expressions. However, emotions can be expressed in the vocal channel too, yet the relationship between trust and vocally expressive agents has not yet been investigated. We use a game theory paradigm to examine the influence of smiling in the voice on trusting behavior towards a virtual agent, who responds either trustworthily or untrustworthily in an investment game. We found that a smiling voice increases trust, and that this effect persists over time, despite the accumulation of clear evidence regarding the agent’s level of trustworthiness in a negotiated interaction. Smiling voices maintain this benefit even in the face of behavioral evidence of untrustworthiness.

Keywords: TrustSmiling voiceVirtual agents


5. Discussion

Using an investment game paradigm, we found that positive vocal emotional expression – smiling voice – increases participants’ implicit trust attributions to virtual agents, compared with when agents speak with an emotionally neutral voice. As previously observed, the monetary returns of the agent also affected implicit trust, so that participants invested more money in the agent that was behaving generously. Critically, however, there was no interaction between behavior and vocal emotional expression: smiling voice enhanced trust regardless of the explicit behavioral cues that the virtual agent provided to its trustworthiness. The effect of smiling voice in the game, supported by our questionnaire findings, adds to previous studies on emotional expression, showing that the display of a positive emotion increases trust and likeability, even in the vocal channel (Scharlemann et al., 2001; Krumhuber et al., 2007; PentonVoak et al., 2006). Smiling was a consistent predictor of investments overall. That is to say, while participants’ investments were primarily driven by the virtual player’s generosity or meanness, they also overall invested more money in the smiling agents. This contrasts with the predictions of the EASI model (Van Kleef et al., 2010), according to which the display of a positive emotion in an incongruent context (such as the mean behavior condition) should elicit uncooperative behaviors. While Van Kleef et al. (2010) listed social dilemma tasks based on Prisoner’s Dilemma among possible competitive situations, it is possible that participants in an iterated investment game view it as an essentially cooperative task. Specifically,
while typical Prisoner’s Dilemma tasks involve a dichotomous choice (cooperate/defect), in our experiment, even in the mean condition, the agent was still returning a (small) amount of money, which might have been seen as a partially cooperative signal by participants. If participants are reluctant to give up on cooperation — as shown by the fact that investments increase in the second half of the game in the mean condition (Fig. 3) — they might be even more reluctant to give up on partners who seem to encourage them to cooperate, with their positive emotional expression. In Krumhuber et al. (2007), people explicitly and implicitly trusted smiling faces more than neutral faces, regardless of the sincerity of their smile, and genuine smiles were trusted more than fake smiles (Krumhuber et al., 2007). Similarly, Reed et al. (2012) found that people displaying either Duchenne or non-Duchenne smiles were more likely to cooperate in a one-shot investment game (Reed et al., 2012). Thus, displaying an emotion, even a feigned one, might be preferred to not displaying any emotion at all, hence the increased investments to the mean smiling agents. Additionally, participants might have felt more positive emotions themselves upon hearing a smiling agent. In fact, emotional expressions can evoke affective reactions in observers (Geday et al., 2003), which may subsequently influence their behavior (Hatfield et al., 1994), and this ‘emotional contagion’ might be transmitted through the auditory channel as well. If this is the case, participants might have trusted the smiling agents more because feeling a positive emotion themselves might have prompted them to behave in a cooperative manner (Schug et al., 2010; Mieth et al., 2016). These results show similarities with Tsankova et al. (2015), who found that people rated trustworthy faces and voices as happier (Tsankova et al., 2015). Although they addressed the issue from the opposite direction – "Are trustworthy stimuli perceived as happier?" rather than "Are happy stimuli perceived as trustworthy?" – taken together, the studies suggest a bidirectionality in the perception of trustworthiness and cues to positive emotion, congruent with a ’halo effect’ of positive traits (Lau, 1982). The smiling-voice effect suggests that, in the absence of visual information, the audio equivalent of a Duchenne smile might act as a relative ‘honest signal’ of cooperation. As mentioned before, Duchenne smiles are smiles describing genuine happiness or amusement (Ekman & Friesen, 1982). Traditionally, in the visual domain they can be distinguished from other types of smiles because they involve the contraction of the ‘Orbicularis Oculi’ muscle, which is a movement that is notoriously more difficult to fake (Ekman & Friesen, 1982; Schug et al., 2010). Obviously, in the auditory channel it is not possible to detect a genuine smiling voice from this muscular movement. However, it is possible that a smiling voice which sounds happy might be the auditory equivalent of a Duchenne smile. As participants indicated that the smiling voices used in this study did sound happy, it is possible that the expression of happiness and amusement in the speech signal led listeners to believe that the agent could be trusted. A limitation of this study is that no video recordings were taken during the audio recordings of the speakers used in this experiment. This means that, while every effort was was made to ensure consistency in the smile production, it is possible that our speakers might have produced different kinds of smiles. As is well known in emotion theory, smiles can convey many different meanings, and several different facial expressions of smiles are known (e.g. Rychlowska et al., 2017; Keltner, 1995). However, much of the research on the effect of different types of smiles on person perception and decision making has concentrated on the difference between polite (non-Duchenne) and genuine (Duchenne) smiles (e.g. Chu et al., 2019; Krumhuber et al., 2007; Reed et al., 2012). Traditionally, these two are characterised by different muscle activation, with non-Duchenne smiles only activating the Zygomaticus Major muscle, and Duchenne smiles also activating the Orbicularis Oculi muscle (Frank et al., 1993). However, recent studies have suggested that Orbicularis Oculi activation in Duchenne smiles might actually be a by-product of the Zygomaticus Major activation (Girard et al., 2019; Krumhuber & Manstead, 2009). Also, the acoustics of smiling are only affected by activation of the Zygomaticus Major muscle, which contributes to vocal tract shape, but not of Orbicularis Oculi. Following past research that Orbicularis Oculi activation is the only thing that distinguishes Duchenne from non-Duchenne smiles, we would still expect both smiles to sound the same, as the Zygomaticus Major activation would be the same. Still, research on the acoustic characteristics of different types of smiles is lacking. Drahota et al. (2008-04) obtained three different smiling expressions – Duchenne smiles, nonDuchenne smiles, and suppressed smiles – as well as a neutral baseline, from English speakers, and asked participants to correctly identify these four expressions. Participants were only able to reliably distinguish Duchenne smiles from non-smiles, but the majority of the other smile types were classified as non-smiles. Furthermore, they only performed pairwise comparisons between a smile type and a non-smile, but they did not compare differences in identification between two different smile types. Even though they only had 11 participants, which warrants for a much-needed replication of this study, this finding suggests that people might only be able to acoustically discriminate between two categories, smile and non-smile. Similar results were obtained in studies using different types of visual smiles in decision-making tasks. Previous work using cooperative games with Duchenne and non-Duchenne (facial) smiles have shown that people made the same decisions regardless of the type of smile (Reed et al., 2012; Krumhuber et al., 2007). This suggests that people might react according to a broad, dichotomous smile category (smile vs. non-smile), even though the smiles in the experiment stimuli were of different qualities. This corroborates previous findings in nonconscious mimicry, whereby facial EMG recordings were different when viewing a face with a Duchenne smile and a neutral expression, but not when viewing a face with a non-Duchenne smile and a neutral expression (Surakka & Hietanen, 1998). This contrasts with Chu et al. (2019), who
found that participants cooperated more with a confederate expressing a non-Duchenne smile, than with a confederate expressing a Duchenne smile, following a breach of trust. However, in this study the confederate only showed the smiling expression after the cooperate/defect decision was made, whereas in Reed et al. (2012); Krumhuber et al. (2007), as well as in the current study, the smiling expression was displayed before the decision was made. As Chu et al. (2019) point out, this factor might have influenced the decisions and could explain the different behaviors. For example, participants might interpret an emotional expression – such as a smile – after a decision as being an appraisal of that decision. People might put more cognitive effort into understanding this appraisal, as this is essential for shaping future interactions, hence the more accurate discrimination of different smile types. As de Melo et al. (2015, 2013) suggest, a happy expression following the decision to cooperate conveys a different meaning than a happy expression following the decision to defect. This is also consistent with the EASI model (Van Kleef et al., 2010). On the other hand, a happy expression shown before the decision to cooperate / defect might rather convey some information about the emotional state of the person in question, and might be kept independent from that person’s actual behavior in the game. Also, counterparts’ smiles may lead people to anticipate positive social outcomes (Kringelbach & Rolls, 2003). Thus, it seems that the timing of emotional expression in relation to the behavior of interest drastically changes the interpretation of that, and future, behaviors. It would be very interesting to replicate the current experiment with different smiling voices, shown before and after the action is taken in the game. Also, if a similar study were to be replicated, the actual facial expression of the speakers could be recorded in order to determine whether different facial expressions correspond to different auditory smiles, both in terms of objective measures (acoustics) and in terms of perception and behavior correlates in the game. So far, we have compared our results with previous studies that used facial smiles. These comparisons are necessary, as at the time of writing there are virtually no studies that have employed trust games with expressive voices. However, emotional expressions are naturally multimodal, and it is possible that a certain emotion expressed only in the voice might elicit different behaviors than if it were expressed only in the face, or in a voice + face combination. In fact, previous research suggested that an ’Emotional McGurk Effect’ might be at play (Fagel, 2006; Mower et al., 2009; Pourtois et al., 2005). Thus, our current results can only inform the design of voice-based artificial agents, but should not be extended to the design of embodied agents. The results from questionnaires validate the behavioral measures obtained from the investment game. We found that people consistently gave higher ratings of trustworthiness and liking to the smiling agents, and to the agents that behaved generously in the game. Again, the lack of interactions between smiling and behavior suggests that the smiling voice mitigates negative reactions following an untrustworthy behavior. We also found some evidence that individual differences among participants might play a role in trusting behavior, as shown by the 3-way interaction between behavior, game turn, and gender (Section 4.1). The effect of gender on trusting and trustworthiness has been widely studied using game theoretic paradigms, but so far there has been no definite conclusion on whether women trust more / are more trustworthy than men, or vice versa (e.g. Chaudhuri et al., 2013; Bonein & Serra, 2009; Slonim & Guillen, 2010). Our results support previous findings showing that we tend to trust people of the opposite gender more (Slonim & Guillen, 2010), as men in our experiment invested more money than women to the virtual agents, which had a female voice. They also support findings that men trust more than women in general (Chaudhuri & Gangadharan, 2007). However, these conclusions only hold insofar as the generous behavior condition is concerned, as in the mean condition men actually trusted the virtual agent less than women did. A similar behavior was previously observed in Haselhuhn et al. (2015), who found that men showed less trust following a trust breach on the trustee’s part (Haselhuhn et al., 2015). Also, Torre et al. (2018) showed that people who formed a first impression of trustworthiness of a virtual agent punished it when the agent behaved in an untrustworthy manner, by investing less money than to an agent whose first impression was lower. Thus, a ’congruency effect’ might be at play here: our male participants might have formed a first impression of trustworthiness of the female agents (Slonim & Guillen, 2010); when this first impression was congruent with the observed behavior (in the generous condition), the agent received more monetary investments from the male participants. On the other hand, when the first impression was incongruent with the observed behavior (mean condition), it received less (cf. Torre et al., 2018). Participants’ age did not have an effect on the behavioral results from the investment game, but it did influence participants’ explicit ratings of the artificial agents’ trustworthiness, with older people indicating lower trust. This is consistent with the idea that younger people trust technology more, perhaps due to a higher degree of familiarity (e.g. Scopelliti et al., 2005; Giuliani et al., 2005; Czaja & Sharit, 1998). However, we did not match participants’ age – or gender– systematically, so more research is needed on the role of individual differences on trust towards voice-based artificial agents. Finally, speaker identity was varied randomly rather than wholly systematically in our experimental design, and so we included speaker identity as a random rather than fixed effect in our analyses. It is possible, indeed likely, that participants’ trust attributions were influenced by the virtual agents’ unique vocal profiles as well as their behavior and smiling status. In fact, Fig. 7 shows that people invested more money with speaker B2, followed by speakers R1, R2, and B1 (mean overall investments = £5.46, £4.76, £4.11, £3.56, respectively). This is not unexpected: voices carry a wide variety of information about the speaker, such as gender, accent, age, emotional state, socioeconomic background, etc., and all this information is implicitly used by listeners to
form an initial impression of the speaker; a short exposure to someone’s voice is enough to determine if that someone can be trusted (McAleer et al., 2014). For example, in the free-text comments explaining the liking rating to each voice, one participant remarked that smiling speaker B2 “varied in tone and was much more interesting to listen to” and neutral speaker B2 was “calm and convincing”; on the other hand, smiling speaker R2 was “mellow and monotone"and neutral speaker R2 “sounded bored and insincere”. Smiling speaker B1 was “quite annoying” and the neutral version “didn’t seem trustworthy or reassuring”, “sounded too neutral” and even “too fake”. Thus, when designing a voice for an artificial agent, it is important to also keep in mind what effect its specific vocal imprint will have on the user (see als McGinn & Torre, 2019). Nevertheless, any potential between-speaker differences in the current experiment were nested within the effect of smiling voice, as all speakers were recorded in both smiling and neutral conditions

Human foetuses and newborns smile first during sleep, before they smile while awake and interacting with caregivers; adults may have true smiling and laughing, a true inner mirth, during sleep

Smiling asleep: A study of happy emotional expressions during adult sleep. Marion Clé et al. Journal of Sleep Research, https://doi.org/10.1111/jsr.12814

Abstract: Human foetuses and newborns smile first during sleep, before they smile while awake and interacting with caregivers. Whether smiling persists during adult sleep, and expresses inner joy, is yet unknown. Smiles were looked for during night‐time video‐polysomnography combined with electromyography of the zygomatic and orbicularis oculi muscles in 100 controls, 22 patients with sleepwalking and 52 patients with rapid eye movement (REM) sleep behaviour disorder. Autonomous reactions (heart rate and level of vasoconstriction) and the presence of rapid eye movements were examined during smiles and laughs. On visual examination of the face video clips synchronous with zygomatic contraction, 8% of controls smiled while asleep (7% in REM sleep and 1% in non‐REM sleep). Some patients with sleepwalking also smiled and laughed during N2 sleep and N3 parasomnia. Half of the patients with REM sleep behaviour disorder smiled and one‐third laughed, mostly during REM sleep. The 173 happy faces included mild smiles (24.8%), open‐mouth smiles (29.5%) and laughs (45.7%). More than half of the smiles were the Duchenne (genuine) type, including an active closure of the eyelids. Approximately half of the smiles and laughs were temporally associated with rapid eye movements. There was no increased heart rate variability during smiles and laughs. Two scenic behaviours including smiles and laughs suggested that the happy facial expression was associated with a happy dreaming scenario. Smiling and laughing occasionally persist during adult sleep. There are several lines of evidence suggesting that these happy emotional expressions reflect a true inner mirth.

Smartphones reduce smiles between strangers

Smartphones reduce smiles between strangers. Kostadin Kushlev et al. Computers in Human Behavior, https://doi.org/10.1016/j.chb.2018.09.023

Highlights
•    Strangers smiled less to one another when they had their phones in a waiting room.
•    Participants were randomly assigned in pairs to have or not have their phones.
•    Smiling behavior was coded by trained researchers blind to hypotheses.
•    The effects applied to frequency of Duchenne smiles and to total smiling time.
•    This preregistered study shows that phones are altering the fabric of social life.

Abstract: New developments in technology—from the printing press to television—have long facilitated our capacity for “absent presence,” enabling us to escape the limits of our immediate environment. Does being constantly connected to other people and activities through our smartphones diminish the need to engage with others in the immediate social world, reducing the likelihood of approach behavior such as smiling? In a preregistered experiment, strangers waited together with or without their smartphones; their smiling was later coded by trained assistants. Compared to participants without smartphones, participants with smartphones exhibited significantly fewer smiles of any kind and fewer genuine (Duchenne) smiles. These findings are based on objective behavioral coding rather than self-report and provide clear evidence that being constantly connected to the digital world may undermine important approach behavior.

During a comedy routine, alcohol consumption enhanced enjoyment (Duchenne) smiles-but not nonenjoyment social smiles-and elevated mood ratings

The effects of alcohol on positive emotion during a comedy routine: A facial coding analysis. Sayette MA, Creswell KG, Fairbairn CE, Dimoff JD, Bentley K, Lazerus T. Emotion. 2018 May 17. doi: 10.1037/emo0000451

Abstract: There is considerable interest in understanding the emotional effects of alcohol. While a great deal of experimental research has focused on alcohol's ability to relieve negative emotions, there has been far less focus on the effects of alcohol on positive emotions. Further, the available research on positive emotion tends to test alcohol while participants are alone. Yet alcohol is often consumed in social settings, and enhancing social pleasure is consistently identified as being a primary motive for drinking. We aimed to address this gap in the literature by investigating the impact of alcohol on positive emotional experience in a social setting. We used the Facial Action Coding System (FACS) to examine in a large sample the effects of alcohol on response to comedy in a group setting. Five hundred thirteen social drinkers (51.9% female) were assembled into groups of three unacquainted persons and administered either a moderate dose of alcohol, a placebo, or a nonalcohol control beverage. Following beverage consumption, groups listened to a roughly 5-min comedy clip while their facial expressions were video recorded. More than 5 million frames of video were then FACS-coded. Alcohol consumption enhanced enjoyment (Duchenne) smiles-but not nonenjoyment social smiles-and elevated mood ratings. Results provide multimodal evidence supporting the ability of alcohol to enhance positive emotional experience during a comedy routine delivered in a social context. More broadly, this research illustrates the value of studying emotion in a social context using both self-report and behavior-expressive approaches.

Gene Editing Using CRISPR -- Why the Excitement?

JAMA Viewpoint
Gene Editing Using CRISPR -- Why the Excitement? Anthony L. Komaroff, MD
JAMA. Published online August 10, 2017. doi:10.1001/jama.2017.10159
jamanetwork.com/journals/jama/fullarticle/2646800

The gene-editing technique known as CRISPR (clustered regularly interspaced short palindromic repeats) is only 5 years old, yet it has galvanized biomedical research and raised important ethical questions. What is it, how does it work, and how could it change medical practice?
The Evolution of Gene Editing

Biomedical scientists have been “editing” (or, at least, altering) genes for many years. Recombinant DNA technology allowed particular genes to be inserted into a plasmid (a circle of DNA) or into a virus: bacterial and yeast cells now could produce therapeutically useful human proteins, and viral vectors could perform gene therapy in humans. Gene targeting and RNA interference allowed the knockout of particular genes and the insertion of a healthy gene at the site of a defective gene. Zinc finger proteins and transcription activator-like effector nucleases (TALENs) precisely altered specific genes. Then came CRISPR. Compared with these previous technologies, CRISPR is easier, faster, less expensive, and more powerful.


How Does CRISPR Work?

CRISPR technology depends on the fact that a strand of nucleic acid (DNA or RNA) with a particular sequence of bases binds naturally to another nucleic acid strand with a matching (complementary) sequence. The workhorse of CRISPR technology is a complex of RNA and protein (primarily nucleases). The most widely used complex is called CRISPR-Cas9.

The RNA in a CRISPR-Cas9 complex has 2 functions. One part is programmed to recognize a particular sequence of bases in the target gene, while the other holds the Cas9 proteins close. Cas9 then unwinds or unzips a double helix so that the target nucleic acid sequence is made “visible” to the matching CRISPR RNA sequence, which quickly binds to its target. Then Cas9 cuts both strands of the target DNA precisely at the right spot.

CRISPR can affect the structure of a gene and can correct a single-base mutation. For example, CRISPR can transform the gene for hemoglobin S (sickle cell globin) into the gene for hemoglobin A. It does this by adding into the CRISPR mix a short DNA sequence for the healthy hemoglobin A gene: after Cas9 cuts the globin gene at the point of the sickle mutation, the sequence that codes for hemoglobin A is inserted.

CRISPR also can affect the expression of a gene: it can shut off the production of a protein, or ramp it up. For example, it can edit the messenger RNA made by a gene; alternatively, it can edit the “noncoding” DNA in the genome that controls the expression of specific genes.
Using CRISPR in Living Organisms

The DNA that codes for the CRISPR RNA, and for the CRISPR proteins (such as Cas9), can be introduced into living organisms using viral vectors, lipid nanoparticles, and other means. Typically, the goal is to reach just the pertinent cells—for example, just hematopoietic stem cells if the goal is to generate hemoglobin A instead of hemoglobin S.

The delivery of CRISPR to a target tissue can be hazardous, and the CRISPR payload does not always reach the intended destination. One way of solving that problem is to first edit an organism’s target cells (such as hematopoietic stem cells) in the laboratory, allow the edited cells to multiply, and then reinfuse those edited cells into the organism, where they home to their target tissue (such as the bone marrow).

CRISPR also can generate organisms in which every cell has been altered in a specific way. For instance, editing the genes in a fertilized egg leads to animals that have the edited genes in every cell.


How Was CRISPR Discovered?

Some medical breakthroughs are inventions, others are discoveries, and some, like CRISPR, are both.

The path leading to CRISPR was tortuous and full of surprises. First, scientists discovered unusual structures in bacterial genomes: clustered regularly interspaced short palindromic repeats (CRISPR) followed by genes for various nuclease proteins. These structures were found to somehow aid a bacterium’s ability to prevent infection by viruses (bacteriophages). The mechanism was subsequently discovered: the CRISPR genes edit viral genes, thereby disabling the viruses.1,2

Then came ultimate discovery and the invention. Scientists realized that the CRISPR-Cas9 complex could be modified and simplified to produce a programmable tool by which the nucleic acids of all plant and animal species could be precisely edited.1,2 The technology was optimized for use in mammalian cells and to edit multiple genes simultaneously.3,4 Subsequent variants of CRISPR technology involving different nuclease proteins have been developed to make CRISPR simpler and more precise.
Limitations of CRISPR

CRISPR allows remarkably precise editing, but it is not perfect. Sometimes, unintended nucleic acid sequences get edited—so-called off-target effects. This may occur more frequently than had been thought. Furthermore, some genetic “defects” that increase the risk of one disease decrease the risk of another. For example, people with sickle cell disease are less vulnerable to malaria: fixing hemoglobin S to solve one problem may cause another. Moreover, scientists understand relatively little about the health effects of “fixing” any particular polymorphic variant. In addition, like any powerful technology, CRISPR could be abused. Indeed, the US intelligence community has publicly expressed concern that CRISPR could produce a weapon of mass destruction.5


How Is CRISPR Affecting Biological Research?

CRISPR technology has transformed genetic research with plants and microbes. It has greatly aided research with many animal models, such as fruit flies, worms, and zebrafish, and has revolutionized the process for creating genetically modified mice,6 essential tools for medical research. Also, CRISPR has made possible the editing of primate genomes. Moreover, CRISPR has been used to treat disease in mice: a viral vector carried a CRISPR complex programmed to edit a mutated gene for dystrophin into the skeletal and cardiac muscle of mice with Duchenne-like muscular dystrophy, and a single treatment led to greatly improved muscle function.7


How Might CRISPR Affect Medical Practice?

CRISPR has greatly reduced the tumor burden of human prostate cancer cells in mouse xenografts.8 It has made possible a test that can be used in resource-limited settings for immediate diagnostics, such as for Zika virus.9 CRISPR also has been used for editing genes in T cells, ex vivo, to program them to attack a patient’s tumor when those cells are reinfused.

Similarly, it may be possible to edit a patient’s hematopoietic stem cells to correct sickle cell anemia and β-thalassemia. Using CRISPR in humans to edit solid-organ cells in vivo, however, as in the mice with muscular dystrophy, is further off.

The role of CRISPR in treating most of the major causes of disability and death in the developed nations is uncertain. These diseases typically are influenced by variants in multiple genes, each of which only slightly increases disease risk. More important, lifestyle modification is likely to have a greater influence on preventing and controlling these diseases than gene editing, no matter how powerful the technology becomes.

Experiments using CRISPR to edit human germ cells are subject to particular scrutiny because such experiments affect all descendants. Gene editing followed by in vitro fertilization could eliminate the risk that a conceptus would inherit (and pass on) a terrible disease—but it also could create an editing error that would harm future generations. The use of CRISPR to edit disease-related genes in germ cells also could generate a demand to protect all offspring against future risks (such as reducing the risk of Alzheimer disease by converting the ε4 variant of APOE to an alternative polymorphism). Moreover, CRISPR could create a demand for “designer babies” with certain desired traits. Society needs to grapple now with the ethical questions raised by such demands, before the technology can satisfy them.
How Might CRISPR Affect Human Health More Broadly?

CRISPR is being used to make plants and animals resistant to disease; to create certain animals (eg, pigs and cows) that become “bioreactors” for making therapeutic human proteins; and to generate pigs that could serve as human organ donors (such as for heart valve tissue), because their organs do not elicit an immune attack following transplantation. Theoretically, CRISPR gene drives could render mosquitoes all over the globe incapable of hosting various human pathogens.

The discovery and invention of CRISPR are already having a profound effect on biomedical research and are beginning to have an impact on medical practice. The scientists who created the CRISPR technology probably cannot imagine all of the ways in which it will be used. Two of those scientists said it best: “Every time we unlock one of nature’s secrets, it signals the end of one experiment—and the beginning of many others.”5

References at the original source.