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Functionally distinct smiles elicit different physiological responses in an evaluative context

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When people are being evaluated, their whole body responds. Verbal feedback causes robust activation in the hypothalamic-pituitary-adrenal (HPA) axis. What about nonverbal evaluative feedback? Recent discoveries about the social functions of facial expression have documented three morphologically distinct smiles, which serve the functions of reinforcement, social smoothing, and social challenge. In the present study, participants saw instances of one of three smile types from an evaluator during a modified social stress test. We find evidence in support of the claim that functionally different smiles are sufficient to augment or dampen HPA axis activity. We also find that responses to the meanings of smiles as evaluative feedback are more differentiated in individuals with higher baseline high-frequency heart rate variability (HF-HRV), which is associated with facial expression recognition accuracy. The differentiation is especially evident in response to smiles that are more ambiguous in context. Findings suggest that facial expressions have deep physiological implications and that smiles regulate the social world in a highly nuanced fashion.
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Functionally distinct smiles elicit
dierent physiological responses in
an evaluative context
Jared D. Martin1, Heather C. Abercrombie2, Eva Gilboa-Schechtman3 & Paula M. Niedenthal1
When people are being evaluated, their whole body responds. Verbal feedback causes robust activation
in the hypothalamic-pituitary-adrenal (HPA) axis. What about nonverbal evaluative feedback? Recent
discoveries about the social functions of facial expression have documented three morphologically
distinct smiles, which serve the functions of reinforcement, social smoothing, and social challenge. In
the present study, participants saw instances of one of three smile types from an evaluator during a
modied social stress test. We nd evidence in support of the claim that functionally dierent smiles
are sucient to augment or dampen HPA axis activity. We also nd that responses to the meanings of
smiles as evaluative feedback are more dierentiated in individuals with higher baseline high-frequency
heart rate variability (HF-HRV), which is associated with facial expression recognition accuracy. The
dierentiation is especially evident in response to smiles that are more ambiguous in context. Findings
suggest that facial expressions have deep physiological implications and that smiles regulate the social
world in a highly nuanced fashion.
Sweaty palms, a racing heart, a faltering voice. Most people nd the evaluative context of public speaking unpleas-
ant. Indeed, the mere anticipation of social evaluation increases activity across almost all body systems related to
stress, with particularly robust activation in the hypothalamic-pituitary-adrenal (HPA) axis14. However, scientic
inquiry has largely been limited to investigations of the manner in which the body responds to verbal evaluative
feedback, of the type “that was/wasn’t good.5,6 Does the HPA axis respond to purely nonverbal feedback, such as
facial expression? We investigate this question and demonstrate that evaluators’ smiles are sucient to augment
or dampen HPA axis activity – depending upon the distinct meaning of the smile in the social-evaluative con-
text. Furthermore, we nd that physiological responses to smile meaning are most dierentiated in individuals
with higher baseline high-frequency heart rate variability (HF-HRV), which is associated with facial expression
recognition accuracy79.
Nonverbal feedback in social-evaluative contexts should be at least as impactful as verbal feedback, since non-
verbal signals are experienced by perceivers to be spontaneous reactions10 and thus, honest reections of internal
evaluations. In the few studies that have investigated the nonverbal communication of evaluative feedback, par-
ticipants whose audience displayed smiles and other nonverbal expressions of positive evaluation showed lower
physiological activity than participants met with frowns and similar cues to negative evaluation1113. Recent the-
ory and empirical evidence suggests, however, that smiles do not all communicate identical, uniformly positive
messages1416. Instead, evidence supports the existence of at least three morphologically distinct types of smiles,
each of which serves a dierent social function necessary for successful group living: “reward” smiles reinforce
behavior, “aliation” smiles signal lack of threat and facilitate or maintain social bonds, and “dominance” smiles
assert claims to higher status in social hierarchies15,16. In light of their social functions, each of these three smiles
should carry distinct meanings when displayed by evaluators. e rst aim of the present research was to test the
hypothesis that reward, aliation, and dominance smiles, delivered as evaluative feedback, inuence perceivers’
HPA axis activity in a manner congruent with their distinct social meaning. We expected dominance smiles,
compared to reward smiles, to increase HPA axis activity. In theory, whereas dominance smiles show disdain for
and reward smiles show approval of performance, aliation smiles reassure without being indicative of a specic
evaluation and so were expected to buer HPA axis activity to a lesser degree than reward smiles.
1University of Wisconsin-Madison, Department of Psychology, 1202 W. Johnson St., Madison, WI, 53706, United
States. 2University of Wisconsin-Madison, Department of Psychiatry, 6001 Research Park Blvd, Madison, WI, 53719,
United States. 3Bar-Ilan University, Department of Psychology, Ramat-Gan, 52900, Israel. Correspondence and
requests for materials should be addressed to J.D.M. (email: jdmartin7@wisc.edu)
Received: 12 October 2017
Accepted: 6 February 2018
Published: xx xx xxxx
OPEN
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e second aim of the present research was to account for variability in participants’ capacity to understand
the evaluative meanings of each smile. Reward smiles are more unambiguous in meaning across contexts than
either aliation or dominance smiles14, which are relevant in more limited contexts. at is, reward smiles can
reinforce widely varying behaviors in most any social situation, whereas aliation smiles serve to smooth exist-
ing or potential social bonds and dominance smiles serve to challenge social standing. Individuals who are more
accurate at recognizing facial expressions should exhibit more dierentiated physiological activity in response to
aliation and dominance smiles, indicating greater sensitivity to their social-evaluative meanings. Recent empir-
ical evidence suggests that baseline HF-HRV – an index of parasympathetic nervous system activity at the level of
the heart – is positively associated with facial expression recognition accuracy79. We thus tested the hypothesis
that individuals with higher baseline HF-HRV exhibit more dierentiated physiological activity in response to
smiles presented as evaluative feedback, particularly in response to smiles that are more ambiguous in context
(i.e., aliation and dominance smiles).
In an adaptation of the classic Trier Social Stress Test17, male participants (N = 90) extemporaneously
addressed three topics about themselves in front of a male evaluator who watched them over a web camera. e
evaluator was, in fact, one of two confederates working for the research team; approximately half of the partici-
pants (Ns = 47 and 43) interacted with each confederate. To increase believability, the evaluator briey appeared
live on the computer screen, then turned o his web camera for the remainder of the session. Aer responding
to each of the three topics, participants saw videos of their evaluator’s facial expressions, which they believed
represented spontaneous reactions to their performance that had been extracted by facial recognition soware.
e videos were, in fact, pre-recorded. Participants were assigned to one of three smile conditions such that they
saw either one reward, aliation, or dominance smile aer each of their responses to the three topics. Along with
one smile video, participants also saw a control video that showed the evaluator making a neutral response such
as face scratching or eye blinks. us, each participant was exposed to six videos of their evaluator in total (three
dierent instances of one type of smile, three neutral videos) with one smile and one neutral video presented
aer each of the three responses. Smile videos were constructed to meet a priori specications of morphological
activity associated with each of the three smile types (for further details, see Supplementary Materials)14. us,
smile type was the only feature of the evaluative feedback that varied between conditions. Physiological activity, in
both the HPA axis and cardiovascular system, was assessed throughout the study; salivary cortisol was measured
at seven time points, and a continuous electrocardiograph was collected before, during, and aer the speech task.
Results
Raw means for total salivary cortisol level by smile condition were consistent with the prediction that reward, al-
iation, and dominance smiles inuence perceivers’ physiological activity in distinctive ways, such that the receipt
of dominance smiles is associated with higher HPA axis activity relative to thereceipt of reward smiles. (AUCi
nmol/l: dominance: M = 19.4, SD = 24.74; aliation: M = 2.43, SD = 22.3; reward: M = 1.21, SD = 21.54). We
used dummy-coded condition contrasts to directly compare total salivary cortisol responses between smile types
(“AUCi, see Methods, below). Compared to reward smiles, dominance smiles induced a greater overall salivary
cortisol response (b = 18.18, t (86) = 2.93, p = 0.004, CI(95%) = [5.83, 30.54], Δr2 = 0.087). Similarly, even though
aliation smiles do not signal a clear social evaluation in this context, compared to such smiles, dominance
smiles induced a greater overall salivary cortisol response (b = 16.97, t (86) = 2.92, p = 0.004, CI(95%) = [5.41,
28.53], Δr2 = 0.086).
Further corroborating the nding that dominance smiles induce greater HPA axis activity, participants receiv-
ing reward or aliation smiles returned to their individual cortisol baseline by 30-minutes post-speech, whereas
those who received dominance smiles continued to have signicantly higher cortisol levels than their individ-
ual baseline. In this ancillary analysis, cortisol values at 20- and 30-minutes post-speech were predicted from
dummy-coded condition contrasts and average baseline cortisol level. Intercepts for each smile condition at both
20-minutes post-speech (reward, b = 0.23, t (86) = 1.49, p = 0.14, CI(95%) = [0.08, 0.53]; aliation, b = 0.25, t
(86) = 1.79, p = 0.08, CI(95%) = [0.03, 0.53]; dominance, b = 0.57, t (86) = 4.47, p < 0.0001, CI(95%) = [0.31,
0.82]) as well as 30-minutes post-speech (reward, b = 0.02, t (86) = 0.13, p = 0.9, CI(95%) = [0.32, 0.28];
aliation, b = 0.03, t (86) = 0.2, p = 0.84, CI(95%) = [0.25, 0.31]; dominance, b = 0.36, t (86) = 2.82, p = 0.006,
CI(95%) = [0.11, 0.61]) show that mean salivary cortisol values for the dominance group continued to be signif-
icantly greater than zero up to 30-minutes post-speech, which was not the case for the other groups. is shows
that individuals receiving dominance smiles take signicantly longer to return to their individual cortisol base-
line, thus corroborating ndings from the AUCi analysis.
We also tested the prediction that baseline HF-HRV is positively associated with dierentiation in HPA axis
activity in response to aliation and dominance smiles. We again created dummy-codes for smile feedback con-
dition in order to compare the eect of smile feedback between conditions. We entered these dummy-codes
along with a continuous measure of baseline HF-HRV and the dummy-code by HF-HRV interaction terms into
a linear regression model. Results from this analysis conrmed our expectations. With those who received dom-
inance smiles as the dummy-coded reference group, baseline HF-HRV was positively correlated with salivary
cortisol responses (b = 9.72, t (84) = 2.02, p = 0.046, CI(95%) = [0.14, 19.29], Δr2 = 0.04). Comparing the linear
association between baseline HF-HRV and salivary cortisol responses between individuals who received domi-
nance versus aliation smiles, the comparison of simple slopes was signicant (b = 14.63, t (84) = 2.40, p = 0.018,
CI(95%) = [2.54, 26.83], Δr2 = 0.057), indicating that the relationship between baseline HF-HRV and salivary
cortisol is more positive for those receiving dominance compared to aliation smiles as evaluative feedback
(Fig.1).
Convergent evidence that baseline HF-HRV is positively associated with greater dierentiation of phys-
iological responses to affiliation and dominance smiles comes from cardiovascular data. Again, we created
dummy-coded condition contrasts and entered them into a linear regression model along with baseline HF-HRV
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and the HF-HRV by smile feedback dummy-code interaction terms. With the dummy-coded condition contrasts
referenced on participants who received aliation smiles, baseline HF-HRV was negatively associated with heart
rate during the speech task (b = 5.84, t (84) = 2.85, p = 0.006, CI(95%) = [9.91, 1.76], Δr2 = 0.086). A
comparison of the linear association between baseline HF-HRV and heart rate between individuals who received
aliation versus dominance smiles reveals that the relationship between baseline HF-HRV and heart rate was
more negative for those exposed to aliation compared to dominance smiles as evaluative feedback (b = 7.28,
t (84) = 2.19, p = 0.032, CI(95%) = [13.92, 0.66], Δr2 = 0.051).
Since indicators of HF-HRV reactivity (i.e., baseline – task) have also been associated with facial expres-
sion recognition accuracy18, we conducted ancillary analyses of the association between reactivity measures of
HF-HRV and perceivers’ physiological activity in response to smile feedback. Specically, we calculated a dif-
ference score between task level HF-HRV and baseline by subtracting task HF-HRV, assessed during the rst
2.5 minutes of the speech, from baseline HF-HRV. Higher values on this dierence score reect greater with-
drawal of vagal inuence over the heart during task, compared to baseline. We entered the dierence score into
a model similar to the one employed in the cortisol and heart rate analyses, entering dummy-coded condition
contrasts along with the continuous HF-HRV dierence score and the condition by dierence score interactions.
Table1 reports these ndings. HF-HRV reactivity was positively associated with physiological responses to social
evaluation, regardless of the type of smile feedback a participant received (i.e., HF-HRV reactivity did not interact
with experimental condition: see Table1). ese ndings strengthen the conclusion that higher baseline HF-HRV
is associated with more dierentiated physiological responses to smiles as evaluative feedback.
Analyses were conducted in the “R” statistical environment19. All results reported in the present work remain
signicant when adding a dichotomous predictor to account for which of the two confederates a participant inter-
acted with, as well as when statistically accounting for factors known to inuence levels of physiological activity
(caeine use, depression severity).
Discussion
In the present study, we observed that smiles with dierent social functions16, when delivered as evaluative feed-
back in a stressful social context, exert distinct inuences on perceivers’ physiological activity. Dominance smiles
Figure 1. Physiological Response to Smiles as Evaluative Feedback Depends on Baseline High Frequency Heart
Rate Variability. Salivary Cortisol: Total salivary cortisol (nmol/l: dominance: M = 19.4, SD = 24.74, N = 27;
aliation: M = 2.43, SD = 22.3, N = 36; reward: M = 1.21, SD = 21.54, N = 27) in response to social evaluation
was greater for those receiving dominance smiles as evaluative feedback relative to the two other types of smiles.
e dierence in total salivary cortisol response between the aliation and dominance groups increased as HF-
HRV increased. Heart Rate: Heart rate assessed during the speech task (bpm: dominance: M = 83.51, SD = 9.84,
N = 27; aliation: M = 82.13, SD = 14.43, N = 36; reward: M = 85.93, SD = 12.65, N = 27) was not signicantly
dierent between conditions. e dierence in heart rate between the dominance and aliation groups
increased as HF-HRV increased. Dotted lines between the +/ 1 SD bars indicate a statistically signicant
simple slope for baseline HF-HRV in that feedback condition; solid lines are not signicant below the 0.05 level.
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(compared to reward or aliation smiles) were associated with increases in heart rate and salivary cortisol that
mirror the inuences of negative verbal feedback20. In contrast, reward and aliation smiles exerted inuences
similar to the eects of displays of friendliness21 and positive social evaluation12, such that, compared to domi-
nance smiles, they buered physiological activity. e ndings thus provide further evidence for the view that
smiles do not constitute a homogenous category of “positive” nonverbal feedback. e ndings also contribute
to abody of literature that proposes a role for cortisol in adaptive responding to the social environment22. In
particular, cortisol appears to support the detection of social threat and coordinate biological activity needed to
adequately respond to the threat.
e present research also contributes to a growing literature on individual dierences in sensitivity to the
meaning of facial expression. Specically, baseline HF-HRV was negatively related to participants’ physiologi-
cal activity when they received aliation smiles, and was positively related to their physiological activity when
they received dominance smiles as evaluative feedback. e observed relationship between HF-HRV and phys-
iological responsiveness to specic smile meaning is consistent with a claim of the Neurovisceral Integration
Model according to which HF-HRV indexes an individual’s capacity to respond appropriately to social stimuli23.
Conversely, individuals with particularly low baseline HF-HRV may be at risk of poor socio-emotional outcomes
due to decits in both understanding as well as responding to the social signals of others. A number of pathologi-
cal and pre-disease body states are related to lower HF-HRV, including heightened inammation and obesity24,25.
As such, these body states may fundamentally change an individual’s ability to respond physiologically to the
social world, and in light of the present ndings, may be associated with decits in understanding the expressions
of others. A compelling avenue for future research therefore is to investigate how individuals with relatively low
HF-HRV recognize and respond to the expressions of others.
Future research should also consider how aective disorders associated with lower HF-HRV, such as anxiety26
and depression27, relate to cognitive and physiological responses to social stimuli. Given the social stress proce-
dure implemented in the present work, an especially fruitful avenue for future research on the social functions
of smiles lies in the relationship between smile processing and social anxiety. Social anxiety disorder involves the
fear of embarrassing oneself in front of others in performance or evaluative situations28. Although research con-
sistently documents that individuals with social anxiety disorder exhibit heightened negative aect both in antici-
pation of and in response to social evaluation29,30, ndings are mixed31,32 regarding how these individuals respond
to positive and supportive social signals. Social anxiety was not accounted for in the present study. Although
randomization into condition likely mitigated any eect of social anxiety on the present ndings, future work is
needed to investigate how individuals with social anxiety respond to facial expressions as evaluative feedback. A
crucial comparison in this work will be to assess dierences in aective and physiological responses between the
relatively unambiguous reward smiles and the less clear aliation smiles.
One limitation of the present research is that the experimental design contained no “neutral” feedback con-
dition. It would be hard to create such an experience, since neutral feedback is interpreted in highly varied ways
across individuals. However, methods to create such a control condition could be imagined for future research.
Along similar lines, future research could also directly compare the eects of receiving dominance smiles with the
eects of receiving more overt signals of negative evaluation such as disgust, contempt, and anger. By employing
the present paradigm to test the physiological eects of facial expressions beyond the smiles tested here, research-
ers could not only more clearly describe the unique eects of receiving social functional smiles but also under-
stand the eects of facial expressions on perceivers’ physiological activity more generally.
e present work includes other limitations that warrant comment, two of which concern the participant sam-
ple. First, the sample size in this study may have been relatively small given the size of the eects detected. Since,
to our knowledge, no work has explored the eect of receiving social functional smiles as social evaluation, a pri-
ori power analyses were dicult to conduct. We estimated required sample size from extant studies with methods
and aims as similar to the present research as possible12. Following these guidelines, 90–100 participants is typical
for a study of this nature involving three between-subjects conditions. Post-hoc power analyses using G*Power33
indicate that achieved power was modest for the critical comparisons within the HPA axis (dominance vs. alia-
tion: β = 0.72; dominance vs. reward: β = 0.81). In light of the achieved power, we recommend that future studies
of this sort rely on no fewer than 35–40 participants per between-subjects condition to ensure adequate power.
(N = 90) b (s.e.) vs. Aliation vs. Dominance
Reward
Cortisol (AUCi)7.04 (4.39) 0.95 (5.60) 1.30 (5.83)
Heart R ate 6.44** (2.31) 0.32 (2.94) 1.97 (3.06)
Aliation
Cortisol (AUCi) 7.99* (3.46) 0.36 (5.16)
Heart R ate 6.12** (1.82) 1.65 (2.71)
Dominance
Cortisol (AUCi) 8.35* (00.0)
Heart R ate 4.47* (2.01)
Table 1. Associations Between HF-HRV Reactivity and Physiological Responses to Social Evaluation.
Unstandardized regression coecients quantifying the association between HF-HRV reactivity (baseline – task)
and physiological responses are reported in the le-hand column, for each group. Dierences between groups
are reported in the middle and right-hand columns. *p < 0.05; **p < 0.01; ***p < 0.001.
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Second, the present sample was restricted to men. Although we limited the sample to males for reasons that
were established and justied before the research was conducted (see Methods, below), generalizations from our
ndings are necessarily limited. Since sex eects are observed in research on the perception of facial expression
of emotion34,35, future work should determine what portion (if any) of the currently documented eects are con-
tingent upon the sex of the smiler or perceiver. Some work suggests that men respond more to threats of physical
aggression whereas women respond more to condescending behaviors and social aggression36. us, men and
women may respond to the same type of smile in dierent ways and may also use each of the smile types with
varying degrees of frequency37.
e present research demonstrates that functionally dierent smiles are sucient to augment or dampen HPA
axis activity in accordance with the social functional meaning associated with each smile. Furthermore, physi-
ological responses to each functionally distinct smile are most dierentiated in individuals with higher baseline
HF-HRV, suggesting that HF-HRV is a useful individual dierence moderator of the ability to respond to the
social environment in a exible and nuanced fashion. We may therefore conclude that smiles coordinate the phys-
iological activity that supports interpersonal encounters to a previously undocumented degree, and that facial
expressions help regulate the social world, in part, through their impact on the physiological activity of perceivers.
Methods
Participants. Ninety-two male undergraduates at a large university in the Midwest participated in exchange
for credit in an introductory Psychology course. Participants provided written consent, indicating full under-
standing of the requirements for participation. e research protocol was reviewed and approved under the
University of Wisconsin – Madison Institutional Review Board. All research was conducted in accordance with
institutional guidelines and regulations.
Due to the robust sex dierences in cortisol responses to laboratory stressors38 and the variability in corti-
sol responses introduced by oral contraceptive use39, only males were invited to participate in this study. Since
females generally outperform males in the accurate recognition of positive facial expressions40, the expectation
was that the present study would underestimate the eects of smiles on physiological responses. Pre-inclusion cri-
teria limited participation to U.S.-born, English-speaking males without a diagnosed heart condition and not cur-
rently taking medications that alter hormone levels. Participants were instructed to refrain from exercise on the
day of the study and to avoid alcohol and caeine consumption within twenty-four hours of their participation.
Due to a network failure, data collection from one participant was terminated before experimental manipulation.
Furthermore, data from a second participant were excluded from analysis due to the presence of an abnormal
heart rhythm resembling premature beats41 which made it dicult to score the data and conicted with the
pre-inclusion criterion of cardiac health. e exclusion of all data from these two participants le a nal sample
of ninety participants (dominance: N = 27; aliation: N = 36; reward N = 27).
Data collection was limited to the number of participants that could be involved during one academic semes-
ter, not to exceed 120 participants (40 per condition). Participants were randomly assigned to one of three smile
experimental conditions as well as one of two confederates. Given that some participants did not show up for
their assigned experimental sessions, a certain amount of imbalance between the number of participants in each
condition and assigned to each confederate is to be expected.
At the conclusion of the study, participants underwent a funneled debrieng. First, they were asked if they
thought they knew what the study was about. In this general interview, no participants brought up suspicions
about deception. We then asked participants if they found anything strange about the study or were suspicious of
anything. In a logistic regression model with experimental condition and confederate as predictors of a dichoto-
mous (“yes”/“no”) suspicion outcome, no signicant dierences were detected by experimental condition (all ps
> 0.2) or by confederate (p = 0.93). Participants who thought the study was slightly strange indicated that they
were unsure how the ller video was related to the study, were unaccustomed to providing saliva samples, or were
uncomfortable giving speeches.
Procedure. In order to reduce variation due to diurnal changes in cortisol levels, experimental sessions took
place in the aernoon. Upon arriving at the experimental laboratory, the participant encountered another male
“participant” who was actually a confederate—one of the two whose stimuli were validated in a separate study (see
Supplemental Material for further information). e experimenter then entered from a nearby room and told the
two men that he had randomly assigned them to dierent tasks in the study: the participant was always assigned
to “give the speech” and the confederate was always assigned to “judge the speech.” Aer the participant and
confederate had provided informed consent, the participant supplied the rst of seven saliva samples (collection
method described below) and completed an online questionnaire assessing his compliance with pre-restriction
criteria (alcohol and caeine use) as well as other medical information (prescription and recreational drug use).
e men were told that only the person giving the speech (always the participant and never the confederate) had
to answer the online questionnaires and provide the saliva samples because it directly pertained to giving the
speech; the confederate waited with the participant and the experimenter while the participant responded to the
surveys and provided the saliva sample.
The experimenter then demonstrated a facial expression recognition software, the Computer Emotion
Recognition Toolbox42. e participant and confederate were informed that the program could extract mean-
ingful facial expressions from live video feed. e experimenter used the computer’s built-in web camera and the
participant’s face as the live feed in a demonstration in order to increase believability in the soware’s (actual)
capabilities.
Next, the participant and confederate were separated. Leaving the confederate behind in the initial room,
the experimenter mentioned that a second experimenter would arrive shortly to provide the confederate with
further instructions and tasks. e experimenter escorted the participant to a psychophysiology lab in the same
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building. ere, the experimenter attached sensors to the participant’s chest and explained that they would be
used to measure aspects of his cardiovascular reactivity. e experimenter sat with the participant in the experi-
mental room while a research assistant in an adjacent control room recorded a 3-minute baseline measure of the
participant’s heart activity.
Aer completion of this baseline recording, the experimenter informed the participant that he would deliver
his speech to the “other participant” via Skype. He would not see the evaluator as his web camera would be turned
o in order to avoid distraction. e format of the speech involved answering three questions in sequence, with
two minutes to respond to each question. e participant was also told that at the conclusion of every two-minute
speech period, he would see videos of several of the evaluator’s facial expressions. e participant was told that
the videos had been “randomly extracted by the facial expression soware” while the evaluator watched the par-
ticipant’s speech. is led the participant to believe that the videos conveyed authentic evaluative responses by the
confederate. e facial expressions displayed in these videos constituted the experimental manipulation.
When the participant indicated that he had understood the speech task, the experimenter gave him a sheet
of paper with the three questions he was required to answer, and then sat with the participant for three min-
utes while the participant prepared his speech. A continuous cardiovascular recording was taken during this
three-minute “anticipation” period. Aer the time was over, the second saliva sample was taken.
Next, the experimenter launched Skype. In order to enhance believability, the confederate appeared live on
the participant’s screen and waved “hello.” e experimenter asked the evaluator to turn o his camera “so as
not to distract” the participant during the speech. With the participant no longer able to see the evaluator, the
experimenter asked the participant to begin his speech. Participants responded to each question in order, with
two minutes for each question: (1) What makes you happy? (2) What do you like most and least to eat?, and (3)
What is your favorite part of living in Madison, Wisconsin? ese questions were designed to be personal and to
contain enough positive material to make the smiles sent by the evaluator appear plausible.
At the conclusion of each two-minute speech period, the experimenter stopped the participant and showed
him two videos of the evaluator that were “randomly extracted” when he was listening to the participant’s speech.
From the other room, the confederate dropped each video into a network-basedfolder in order to simulate the
facial expression recognition program extracting and sending the videos in real time. Each participant saw 6 vid-
eos in total, 2 aer each question. 3 of the 6 total videos were smiles and the other 3 were a set of dierent neutral
videos—evaluators faced the camera with a neutral expression and madeoccasional small, non-evaluative move-
ments such as face scratching. e smile videos were three dierent short video clips of the same confederate
making only one smile type (dominance, reward, or aliation). Participants were thus exposed to three dierent
examples of the same type of smile. In sum, smile type was manipulated between-subjects with the 3 neutral
videos retained across participants. At the conclusion of the speech task, the third saliva sample was taken. e
speech task lasted between 7–8 minutes, during which a continuous cardiovascular recording was taken.
Immediately upon concluding his nal speech, the participant was directed to reect on his performance,
focusing on how he felt and what his evaluator thought. A continuous cardiovascular recording was taken during
this ve-minute reection period. Aer the reection/recovery period, the participant was detached from the
sensors and led to the nal room by a second experimenter who was blind to the participant’s video feedback
condition.
In the last room, the participant watched a ller video available on YouTube from the series “e Life of Birds”
(available at https://www.youtube.com/playlist?list=PLB1F251E81DE15E9B) which provided a neutral experi-
ence during which cortisol recovery was assessed. e video was the same for all participants. e remaining four
saliva samples were taken at 10-minute intervals from the cessation of the speech task. At the conclusion of the
ller video, and aer completing verbal questions assessing deception suspicion, the participant was debriefed
and dismissed.
Physiological Measures: Collection and Analysis. Cortisol. Saliva samples were obtained with cot-
ton salivettes (Fisher Scientic Company, LLC). Participants were instructed to let the cotton salivette touch all
parts of their mouth (under their tongue, between their teeth and their cheeks) without chewing on it. Saliva
collection was strictly timed for two minutes, aer which the sample was returned to its plastic casing. Samples
were frozen aer collection and stored at 20 C. At the conclusion of the study, samples were express shipped to
Dresden, Germany where they were single-assayed at the lab of Dr. Clemens Kirschbaum (T.U. Dresden). Samples
were assayed using the chemi-luminescence assay, which has a high sensitivity of 0.16 ng/mL (IBL-International,
Hamburg, Germany) and intra and interassay CVs of <10%. In total, saliva samples were collected at seven
time points during the study and assayed for unbound cortisol. Due to skewness, all cortisol values were rst
log-transformed. Salivary alpha amylase was assayed but is not reported in these analyses.
In order to test our hypotheses with regard to the HPA axis, Area Under the Curve with respect to increase
(AUCi)43 values were calculated for the cortisol response of each participant. AUCi scores index total cortisol
response over a given period of time, referenced to each individual’s baseline cortisol level. We averaged the two
cortisol values collected before experimental manipulation (receipt of smile feedback) as a pre-speech baseline.
Heart Rate. Continuous EKG recordings were sampled at 1000 Hz via one of the bipolar inputs available on
the SynAmps2 Headbox (Compumedics Neuroscan Ltd., U.S.A). Ag/AgCl spot electrodes were placed in a
thoracic-modied lead-II conguration to maximize detection of R-spikes while minimizing movement arti-
facts. We calculated mean heart rate values separately for the baseline period, the “anticipation” period, the speech
period, and the post-speech period.
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7
Scientific REPORts | (2018) 8:3558 | DOI:10.1038/s41598-018-21536-1
Data Processing. EKG data were rst scored oine using OpenANSLAB44, manually inspected for artifacts, and
the resultant inter-beat-interval series were extracted and saved. CMETx soware (available at http://apsychos-
erver.psych.arizona.edu) was then used on the extracted inter-beat-interval to quantify HF-HRV.
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Acknowledgements
e authors would like to thank Craig Berridge, Allison Blumenfeld, Stephanie Carpenter, Crystal Hanson,
Judy Harackiewicz, Roxanne Hoks, Cathy Marler, and Wendy Berry Mendes for their assistance and helpful
comments. Magdalena Rychlowska and Adrienne Wood provided critical feedback during the revision process.
Stella Mayerho, Josh Lucas, Sarah Hervdejs, and Mathias Hibbard were instrumental in collecting data. We
also acknowledge the tireless contribution of our two confederates A.J. Laird and Zeus Markos. This work
was supported by the National Institutes of Mental Health [grant number T32MH018931-26 to J.D.M]; the
U.S. – Israeli Binational Science Foundation [grant number 2013205 to P.M.N. and E.G.S.]; and the National
Science Foundation [grant number 1355397 to P.M.N.]. Further support for this research was provided by the
Graduate School and the Oce of the Vice Chancellor for Research and Graduate Education at the University of
Wisconsin-Madison with funding from the Wisconsin Alumni Research Foundation. Sources of nancial support
had no inuence over the design, analysis, interpretation, or choice of submission outlet for this research. Data are
available by contacting the corresponding author.
Author Contributions
J.D.M., P.M.N., and H.C.A. designed the study. J.D.M. collected and analyzed data. J.D.M. wrote the rst dra of
this manuscript, and all authors contributed revisions.
Additional Information
Supplementary information accompanies this paper at https://doi.org/10.1038/s41598-018-21536-1.
Competing Interests: e authors declare no competing interests.
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... However, far from being simple readouts of positive affect, smiles have been shown to signal a wide range of socially relevant information and to regulate social interactions in a highly nuanced fashion [10,15]. Indeed, the political context offers one of the most ecologically valid settings for the smiles' nuanced meanings to emerge [17]. For instance, in addition to genuine enjoyment, smiles often serve as signals of a willingness to cooperate and absence of threat (i.e., affiliative smiles). ...
... For instance, in addition to genuine enjoyment, smiles often serve as signals of a willingness to cooperate and absence of threat (i.e., affiliative smiles). They may also be employed to express feelings of superiority and dominance towards a fierce opponent (i.e., dominance smiles), indicating in this case more negative rather than positive affect [15][16][17][18][19]. ...
... These results expand upon previous work by Fino et al., [29] revealing fine-grain distinctions in the readers' smile response, particularly when tracking concurrent activation of distinct facial muscles. Not all smiles are equal they say, and when our participants were reading of ingroup politicians smiling, spontaneous muscle contractions could be captured in the eye corner (OO) and the lip puller (ZM) muscles, suggesting a Duchenne (aka positive affect) smile reaction for ingroup but not outgroup politicians' smiles [4,17]. This was confirmed by the reported emotions towards target politicians which were significantly more positive for ingroup and more negative for outgroup political leaders, consistent with our predictions. ...
Article
Full-text available
Spontaneous smiles in response to politicians can serve as an implicit barometer for gauging electorate preferences. However, it is unclear whether a subtle Duchenne smile–an authentic expression involving the coactivation of the zygomaticus major (ZM) and orbicularis oculi (OO) muscles–would be elicited while reading about a favored politician smiling, indicating a more positive disposition and political endorsement. From an embodied simulation perspective, we investigated whether written descriptions of a politician’s smile would trigger morphologically different smiles in readers depending on shared or opposing political orientation. In a controlled reading task in the laboratory, participants were presented with subject-verb phrases describing left and right-wing politicians smiling or frowning. Concurrently, their facial muscular reactions were measured via electromyography (EMG) recording at three facial muscles: the ZM and OO, coactive during Duchenne smiles, and the corrugator supercilii (CS) involved in frowning. We found that participants responded with a Duchenne smile detected at the ZM and OO facial muscles when exposed to portrayals of smiling politicians of same political orientation and reported more positive emotions towards these latter. In contrast, when reading about outgroup politicians smiling, there was a weaker activation of the ZM muscle and no activation of the OO muscle, suggesting a weak non-Duchenne smile, while emotions reported towards outgroup politicians were significantly more negative. Also, a more enhanced frown response in the CS was found for ingroup compared to outgroup politicians’ frown expressions. Present findings suggest that a politician’s smile may go a long way to influence electorates through both non-verbal and verbal pathways. They add another layer to our understanding of how language and social information shape embodied effects in a highly nuanced manner. Implications for verbal communication in the political context are discussed.
... Of particular importance to the present research the only study we are aware of that has investigated the impact of different smile types in an evaluative performance context was conducted by Martin and colleagues. 15 The study has demonstrated that various smiles can augment or dampen hypothalamic-pituitary-adrenal (HPA) axis activity in an evaluative context. 15 The HPA has been shown to be a major player within the neuroendocrine system that controls bodily reactions to stress. ...
... 15 The study has demonstrated that various smiles can augment or dampen hypothalamic-pituitary-adrenal (HPA) axis activity in an evaluative context. 15 The HPA has been shown to be a major player within the neuroendocrine system that controls bodily reactions to stress. More specifically, this research has shown that dominant smiles increased HPA axis activity (increased heart rate and salivary cortisol) and reward smiles seemed to buffer against higher physiological activity (decreased heart rate and salivary cortisol) in an adapted version of the Trier Social Stress Test. ...
... This hypothesis was based on the EASI theorising 32 and recent empirical evidence suggesting that dominant and reward smiles, delivered as evaluative feedback, influence perceivers' HPA axis activity in a manner congruent with their distinct social meaning. 15 We assumed that performing in front of a coach would be a stressful situation for athletes. We further predicted that receiving rewarding facial feedback (reward smile) in this situation would lead to a decrease in HPA activity and, in turn, to a lower heart-rate and less-subjective feelings of stress and more positive affect. ...
Article
Full-text available
Non-verbal expressions from other people play an important role in everyday life. We tested the psychological and physiological effects of different non-verbal facial expressions given by a coach to athletes in a performance context. In a study with 60 athletes, we tested how dominance versus reward smiles shown by a coach after various performances affected athletes’ subjective affective state, stress levels, and their own facial expressions. Results showed that athletes who perceived dominant smiles after their performances had higher heart-rates than those who received rewarding smiles. Athletes receiving dominant smiles also reported feeling less happy after their performances than athletes receiving rewarding smiles. No effects were evident on subjective stress levels and facial expressions of emotion measured by Noldus FaceReader. The present results are the first to show that subtle differences in facial expressions of coaches can affect an athlete's heart rate and affective state in an evaluative performance context. The results join research on the interpersonal effects of non-verbal behaviour between athletes and their coaches. They provide evidence that the facial expressions of coaches have communicative content that is perceived by the athletes and influences them on different levels.
... A recent account proposed that both smiles and laughter vary in the extent to which they serve rewarding, affiliative, or dominance functions Wood & Niedenthal, 2018). Studies supporting this social functional account have identified the physical attributes of smiles and laughter that determine their perceived intent Rychlowska et al., 2017;Wood et al., 2017), demonstrated that natural smiles and laughter vary according to social context Wood, 2020), and showed the divergent effects of different smiles on recipients' physiology (Martin et al., 2018). ...
... We have proposed the harmlessness message conveyed by smiles can be usefully divided into three sub-functions: reward, affiliation, and dominance Rychlowska et al., 2017). The prototypical smiles for each sub-function (see Fig. 1) have been validated using reverse-correlation and perceiver judgment studies (Dapprich et al., 2021;Martin et al., 2021;Rychlowska et al., 2017), a production task where naïve participants smiled in response to hypothetical scenarios , a social evaluation paradigm (Martin et al., 2018), and a cooperative decision-making task (Rychlowska et al., 2021). ...
... Dominance smiles are perceived as relatively less trustworthy than reward and affiliation smiles, but still more trustworthy than scowls and grimaces . Receiving a dominance smile as social feedback results in higher salivary cortisol levels, a marker of physiological arousal, compared to receiving a reward or affiliation smile (Martin et al., 2018). ...
Article
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Laughter and smiles co-occur and accomplish similar communicative tasks. Certain smiles and laughter elicit positive affect in the sender and the recipient, serving as social rewards. Other smiles and laughter lack this positivity but retain a message of harmlessness and affiliation that lubricates the interaction. And finally, some smiles and laughter convey disapproval or dominance in a less serious way than more overt displays (e.g., frowns). But work on the social functions of smiles and laughter has progressed independently. We ask whether smiles and laughter are judged as more alike if they are high on the same social functional dimensions. First, online participants’ (N = 244) judged the similarity of a set of validated reward, affiliation, and dominance smiles to each other, resulting in a 2-dimensional semantic smile space. Then we inserted laughter clips (rated on the social functional dimensions in prior work) into the semantic smile space using new participants’ (N = 1089) responses on a smile-laughter similarity task. The laugh samples grouped in the smile space according to their previously determined social function, suggesting participants’ judgments about smile-laughter similarity were partly guided by the reward, affiliation, and dominance values of the displays. Trial-level analyses indicate reward and affiliation smiles were most likely to be matched to reward and affiliation laughs, respectively, but dominance displays were more complicated. This suggests perceivers judge the meaning of smiles and laughs along reward, affiliation, and dominance dimensions even without verbal prompts. It also deepens our understanding of the functional overlap of smiles and laughter.
... Finally, asymmetrical smiles, a wrinkled nose and a raised upper lip express dominance and superiority (dominance smile; Martin et al., 2017;Niedenthal et al., 2010;Rychlowska et al., 2017). Despite the growing body of research showing that the reward, affiliation and dominance smiles have different, namely positive and negative, functions (Martin et al., 2018Orlowska et al., 2018;Rychlowska et al., 2017Rychlowska et al., , 2021, many studies used smiles homogenously to represent positive social stimuli. ...
... decreased cortisol reactivity), whereas male participants who faced observers who expressed dominance smiles showed higher stress responses (i.e. increased cortisol reactivity; Martin et al., 2018). However, participants with higher baseline high-frequency heart rate variability (HF-HRV), i.e. an index of emotion recognition abilities (Lischke et al., 2017;Quintana et al., 2012), showed the lowest stress responses when confronted with the affiliation smile (i.e. ...
... decreased heart rate) and the highest stress responses when confronted with the dominance smile (i.e. increased cortisol reactivity), respectively (Martin et al., 2018). Thus, perceiver characteristics seem to play a role in the recognition of the positive and negative meanings of different smiles. ...
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Research has identified three different types of smiles – the reward, affiliation and dominance smile – which serve expressions of happiness, connectedness, and superiority, respectively. Examining their explicit and implicit evaluations by considering a perceivers’ level of social anxiety and psychopathy may enhance our understanding of these smiles’ theorised meanings, and their role in problematic social behaviour. Female participants (N=122) filled in questionnaires on social anxiety, psychopathic tendencies (i.e. the affective-interpersonal deficit and antisocial lifestyle) and callous–unemotional (CU) traits. In order to measure explicit and implicit evaluations of the three smiles, angry and neutral facial expressions, an Explicit Valence Rating Task and an Approach-Avoidance Task were administered. Results indicated that all smiles were explicitly evaluated as positive. No differences in implicit evaluations between the smile types were found. Social anxiety was not associated with either explicit or implicit smile evaluations. In contrast, CU-traits were negatively associated with explicit evaluations of reward and dominance smiles. These findings support the assumptions of non-biased explicit information processing in social anxiety, and flattened emotional sensitivity in CU-traits. The importance of a multimethod approach to enhance the understanding of the effects of smile types on perceivers is discussed.
... This is because people who are cheerful have better social relationships [14]. The cheerful intonation of the voice attracts students to pay attention to the feedback [16][17]. However, well-timed emphasizing body movements, along with appropriate voice tone and volume, can drive points across effectively [15]. ...
... The most noticeable cue is hands movement in the camera space where students can see. This is to emphasize the information that needs to be conveyed by the lecturer as the interaction can only be done through an online platform [1,6,8,17]. The lecturers were seen to spread their hands apart, with palms facing slightly towards the camera. ...
... The facial stimuli consisted of full colour, frontal images (size: 960 × 540 pixels) of eight (four female) White adult faces with direct gaze and neutral background. Images were retrieved from a stimulus set developed by Martin and colleagues (Martin et al., 2018) and displayed a non-enjoyment smile corresponding to the description of affiliation smiles (Rychlowska et al., 2017). In morphological terms (FACS, Ekman et al., 2002), the smile expressions involved the Lip Corner Puller (Action Unit (AU) 12) and Chin Raiser (AU17), with or without the Brow Raiser (AU1 + 2). ...
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Theoretical accounts and extant research suggest that people use various sources of information, including sensorimotor simulation and social context, while judging emotional displays. However, the evidence on how those factors can interplay is limited. The present research tested whether social context information has a greater impact on perceivers’ smile judgments when mimicry is experimentally restricted. In Study 1, participants watched images of affiliative smiles presented with verbal descriptions of situations associated with happiness or politeness. Half the participants could freely move their faces while rating the extent to which the smiles communicated affiliation, whereas for the other half mimicry was restricted via a pen-in-mouth procedure. As predicted, smiles were perceived as more affiliative when the social context was polite than when it was happy. Importantly, the effect of context information was significantly larger among participants who could not freely mimic the facial expressions. In Study 2 we replicated this finding using a different set of stimuli, manipulating context in a within-subjects design, and controlling for empathy and mood. Together, the findings demonstrate that mimicry importantly modulates the impact of social context information on smile perception.
... In future research, the impact of masked emotional expressions on subsequent social behavior and physiological responses would provide a stronger test of the hypothesis that the perception of emotion in facial expression is compromised by face masks (cf. Martin et al., 2018). ...
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According to the familiar axiom, the eyes are the window to the soul. However, wearing masks to prevent the spread of viruses such as COVID-19 involves obscuring a large portion of the face. Do the eyes carry sufficient information to allow for the accurate perception of emotions in dynamic expressions obscured by masks? What about the perception of the meanings of specific smiles? We addressed these questions in two studies. In the first, participants saw dynamic expressions of happiness, disgust, anger, and surprise that were covered by N95, surgical, or cloth masks or were uncovered and rated the extent to which the expressions conveyed each of the same four emotions. Across conditions, participants perceived significantly lower levels of the expressed (target) emotion in masked faces, and this was particularly true for expressions composed of more facial action in the lower part of the face. Higher levels of other (non-target) emotions were also perceived in masked expressions. In the second study, participants rated the extent to which three categories of smiles (reward, affiliation, and dominance) conveyed positive feelings, reassurance, and superiority, respectively. Masked smiles communicated less of the target signal than unmasked smiles, but not more of other possible signals. The present work extends recent studies of the effects of masked faces on the perception of emotion in its novel use of dynamic facial expressions (as opposed to still images) and the investigation of different types of smiles. Supplementary information: The online version contains supplementary material available at 10.1007/s42761-021-00097-z.
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In the present study, we investigated whether inter-individual differences in vagally-mediated cardiac activity (high frequency heart rate variability, HF-HRV) would be associated with inter-individual differences in mind-reading, a specific aspect of social cognition. To this end, we recorded resting state HF-HRV in 49 individuals before they completed the Reading the Mind in the Eyes Test, a test that required the identification of mental states on basis of subtle facial cues. As expected, inter-individual differences in HF-HRV were associated with inter-individual differences in mental state identification: Individuals with high HF-HRV were more accurate in the identification of positive but not negative states than individuals with low HF-HRV. Individuals with high HF-HRV may, thus, be more sensitive to positive states of others, which may increase the likelihood to detect cues that encourage approach and affiliative behavior in social contexts. Inter-individual differences in mental state identification may, thus, explain why individuals with high HF-HRV have been shown to be more successful in initiating and maintaining social relationships than individuals with low HF-HRV.
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A smile is the most frequent facial expression, but not all smiles are equal. A social-functional account holds that smiles of reward, affiliation, and dominance serve basic social functions, including rewarding behavior, bonding socially, and negotiating hierarchy. Here, we characterize the facial-expression patterns associated with these three types of smiles. Specifically, we modeled the facial expressions using a data-driven approach and showed that reward smiles are symmetrical and accompanied by eyebrow raising, affiliative smiles involve lip pressing, and dominance smiles are asymmetrical and contain nose wrinkling and upper-lip raising. A Bayesian-classifier analysis and a detection task revealed that the three smile types are highly distinct. Finally, social judgments made by a separate participant group showed that the different smile types convey different social messages. Our results provide the first detailed description of the physical form and social messages conveyed by these three types of functional smiles and document the versatility of these facial expressions.
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Ideal for students and as a review for practicing clinicians, Goldberger's Clinical Electrocardiography explains the fundamentals of ECG interpretation and analysis, helping facilitate an understanding of rhythm disorders and the relevant clinical outcomes. The authors take readers through the nuts and bolts of ECG, using Dr. Ary Goldberger's award-winning teaching style to clarify complex concepts in an easy-to-read manner. You'll learn simple waveform analysis and beyond to present ECGs as they are used in hospital wards, outpatient clinics, emergency departments, and most especially intensive care units - where the recognition of normal and abnormal patterns is the starting point in patient care.
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The polyvagal theory suggests that the vagus nerve is the key phylogenetic substrate enabling optimal social interactions, a crucial aspect of which is emotion recognition. A previous study showed that the vagus nerve plays a causal role in mediating people's ability to recognize emotions based on images of the eye region. The aim of this study is to verify whether the previously reported causal link between vagal activity and emotion recognition can be generalized to situations in which emotions must be inferred from images of whole faces and bodies. To this end, we employed transcutaneous vagus nerve stimulation (tVNS), a novel non-invasive brain stimulation technique that causes the vagus nerve to fire by the application of a mild electrical stimulation to the auricular branch of the vagus nerve, located in the anterior protuberance of the outer ear. In two separate sessions, participants received active or sham tVNS before and while performing two emotion recognition tasks, aimed at indexing their ability to recognize emotions from facial and bodily expressions. Active tVNS, compared to sham stimulation, enhanced emotion recognition for whole faces but not for bodies. Our results confirm and further extend recent observations supporting a causal relationship between vagus nerve activity and the ability to infer others' emotional state, but restrict this association to situations in which the emotional state is conveyed by the whole face and/or by salient facial cues, such as eyes.
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The human smile is highly variable in both its form and the social contexts in which it is displayed. A social-functional account identifies three distinct smile expressions defined in terms of their effects on the perceiver: reward smiles reinforce desired behavior; affiliation smiles invite and maintain social bonds; and dominance smiles manage hierarchical relationships. Mathematical modeling uncovers the appearance of the smiles, and both human and Bayesian classifiers validate these distinctions. New findings link laughter to reward, affiliation, and dominance, and research suggests that these functions of smiles are recognized across cultures. Taken together, this evidence suggests that the smile can be productively investigated according to how it assists the smiler in meeting the challenges and opportunities inherent in human social living.