Running head: EMOTION RESIDUE 1
Emotion Residue:
Emotion Lingers in a Face Intended to Display Neutrality
Daniel N. Albohn & Reginald B. Adams, Jr.
The Pennsylvania State University
Author Note
Daniel N. Albohn, 463 Moore building, University Park, PA 16802, E-Mail [email protected]
Reginald B. Adams, Jr., 464 Moore building, University Park, PA 16802, E-Mail [email protected]
Correspondence concerning this article should be addressed to Daniel Albohn, 463
Moore building, University Park, PA 16802 E-mail [email protected], or Reginald Adams, Jr.,
464 Moore building, University Park, PA 16802, E-Mail [email protected]. EMOTION RESIDUE 2
Abstract
Despite the prevalent use of neutral faces in expression research, the term neutral still remains ill-defined. A general assumption is that one’s overt attempt to pose a nonexpressive face results in a neutral display, one devoid of any expressive information. Ample research has demonstrated that nonexpressive faces do convey meaning through emotion-resembling appearance. Here, we examined whether actual prior expressive information lingers on a face, in the form of emotion residue, despite overt attempts to display a neutral face, and whether these subtle emotion cues influence trait impressions. Across three studies we found that explicit attempts at posing neutral displays retained emotion residue from a prior expression. This residue in turn significantly impacted impressions formed based on these otherwise “neutral” displays. We discuss implications of this work for better understanding how accurate impressions are derived from so- called “neutral” faces and underscore theoretical and methodological considerations for future research.
Keywords: Neutral face, Neutral, Facial expressions, Face perception, Impression formation EMOTION RESIDUE 3
Emotion Residue:
Emotion Lingers in a Face Intended to Display Neutrality
It is difficult to think of a social exchange in which the face does not play an important role. With over 40 muscles that can be arranged into more than 7,000 unique configurations, it is a constantly changing canvas that portrays a wide range of social information such as peoples’ emotions, gender, age, and social interest (Hess, Adams, Grammer, & Kleck, 2009; Kalick,
Zebrowitz, Langlois, & Johnson, 1998; Rule & Ambady, 2008; Zebrowitz, 2017). Despite its relatively confined space it is the principal vehicle of human expressive exchange. Even those who are face blind (i.e., prosopagnosic) are able to identify emotion cues in a face (Tranel,
Damasio, & Damasio, 1988) and appear to use them to make trait impressions (Todorov &
Duchaine, 2008). Likewise, neurotypical perceivers tend to use overt expression and even emotion-resembling facial features in otherwise neutral faces to form stable trait impressions of others (Knutson, 1996; Zebrowitz, 2017). Together this work points to emotion cues, even in a neutral display, as a primary source of the impressions we form of others.
Expressions can convey basic social motives such as dominance and affiliation, and more complex information such as intelligence and trustworthiness (Adams, Nelson, Soto, Hess, &
Kleck, 2012; Knutson, 1996). Social judgments derived from images of the same individual displaying different expressions at two different times varied widely, sometimes even more so than judgments of two different individuals (Todorov & Porter, 2014). This work highlights the primacy of expressions in impression formation even above and beyond appearance cues, and thus cautions against static photos conveying much accurate information. Yet, people purposefully pose for pictures, and in these cases emotional expression may be revealing of one’s actual character. For example, individuals tend to associate anger more so with straight EMOTION RESIDUE 4 males and conservatives, and happiness with gay males and liberals and can use these associations to identify, at above chance levels, the social group memberships others belong to
(Tskhay & Rule, 2015).
Further, some degree of expressivity, however subtle, is arguably an expected part of an individual’s facial baseline in typical day-to-day interactions. The lack of any expressivity can even be disturbing. For instance in the classic “still-face paradigm” babies become upset when a parent’s expressive face abruptly becomes “blank” (Tronick, Als, Adamson, Wise, & Brazelton,
1978). A lack of expression on inanimate human-like objects (e.g., mannequins, robots, dolls) is often viewed as unsettling despite approaching a life-like human status, the so-called “Uncanny
Valley” effect (Mori, 1970). Taken together, it stands to reason that we do not expect the faces we encounter in our social worlds to be completely devoid of emotionality.
We are so attuned to expressive cues that when forming impressions of others based on their neutral facial displays, we tend to focus on expression-resembling appearance features (e.g., large, wide eyes, high eyebrows versus small, beady eyes, low hooded eyebrows), an effect referred to as emotion overgeneralization (Zebrowitz, 2017). Thus, emotion-resembling cues can powerfully bias impressions, even when the observer knows the face they are viewing is emotionally nonexpressive. Here we go further to suggest that actual emotion information may be present in these so-called nonexpressive displays, from which we can derive accurate impressions as well.
In a typical face, facial muscles are never fully relaxed, and when they are, this can disrupt face processing. Consider, for example, the characteristic drooping due to facial paralysis. Faces with paralysis preferentially bias attention to specific parts of the face and disrupts normal face processing patterns (Dey, Ishii, Byrne, Boahene, & Ishii, 2014). Thus, a EMOTION RESIDUE 5 typical face, even when posed to be emotionally nonexpressive (and even when subsequently rated by others as being “neutral”), may contain in those contracted muscles some subtle, untended emotional tone. If so, this could help explain a growing body of research suggesting that individuals can consistently and accurately derive certain personality traits and social category judgments even from “neutral” faces (see, Rule & Sutherland, 2017; Zebrowitz, 2017).
Residual emotional tone in the neutral display could drive many of these judgments.
Overview
In the present research, we examine the influence of actual, residual emotional tone on impression formation in otherwise neutral displays. We refer to this as emotion residue, which we define as any observable transient emotional tone remaining on a face once an actor has finished making an expression and has intentionally returned to a neutral baseline.
We hypothesized that residual cues remaining after an actor makes an expression and then is explicitly instructed to return to neutral would: 1) be detectable on post-expression neutral facial images, and 2) alter impressions of these faces similar to what has been previously found for overt expressive and expressive-resembling cues in faces. We expect that neutral displays made after a negative expression will be associated with more negative trait impressions, while those made after a positive expression will be evaluated more positively.
Study 1:
Demonstrating That Emotion Residue is Present After Making an Expression
Before testing whether individuals are able to detect emotion residue, and if it influences impressions, it is important to examine what residual information, if any, remains on a post- expressive neutral face in the first place. Study 1 examines this by isolating on a pixel-by-pixel level the differences between the pre- and post-expressive images. Study 1 also tests whether EMOTION RESIDUE 6 participants are able to use this information to make meaningful trait impression judgements related to the prior expression.
Method
Each face used as stimuli in our studies included both a pre- and post-expressive neutral display. Because we had two images per actor, we can extract from each actors’ post-expressive neutral face what is unique to that image by subtracting from it that actors’ pre-expressive neutral face. Since each image is greyscaled, what remains after subtraction is a matrix of values between 0-1 representing the intensity of the pixel. This matrix of pixel intensities is what is unique to the post-expressive neutral, accounting for the pre-expressive neutral (Figure 1).
Supplemental Materials 1 reports detailed procedures for the subtraction method, as well as observational results on areas of significant difference between the two images utilizing pixel- wise tests.
Power Analysis
We analyzed our data in this study using a linear mixed model. Our fixed effect of interest is the interaction between prior expression (anger vs. happy) and impression valence
(positive vs. negative) on scores. Therefore, we obtained an effect size from a prior face rating study that utilized linear mixed effects modeling and had two categorical fixed effects variables
(Ebner, 2010). Next, we conducted power estimates based on simulations of our model’s critical two-way interaction term by substituting in our model the observed fixed effect value for one that corresponds roughly to that observed by averaging the absolute value of several of the reported fixed effects coefficients in Ebner (2010). Based on these simulated calculations, we estimated that a minimum of 30 participants would be necessary to detect an effect size of 0.31 at
80% power. We estimated our power (based on our sample size) to be 88.90%, 95 % CIs [86.79, EMOTION RESIDUE 7
90.78], with an effect size of 0.31, an alpha set at 0.05, and 1000 simulations. We followed the guidelines outlined by Green and MacLeod (2016) using the SIMR package.
Participants
Participants (N =39; 17 females, 21 males, 1 unreported, Mage = 20.40) were college students from a large public university. One participant was excluded from analysis because they did not complete the study. Each participant received course credit in exchange for participation in the study.
Stimuli
We selected stimuli from the MMI Face Database (http://mmifacedb.eu), which includes facial poses of the same individuals posing neutral displays both before and after making a highly intense emotion expression. The database consists of a number of FACS coded dynamic and static stimuli. The researchers constructed the database so that both static and motion images of faces showing prototypic expressions of emotion and various expressions of single AU and multiple AU activation could be easily accessible to the field of expression research (Pantic,
Valstar, Rademaker, & Maat, 2005). To our knowledge, this is the only facial expression database to include dynamic stimuli of actors beginning and ending with a neutral facial display.
Pantic et al. (2005) indicated that each actor in the database “[was] instructed by an expert (a
FACS coder) on how to display the required facial expressions, and they were asked to include a short neutral state at the beginning and at the end of each expression” (p. 319). For each pre- and post-expressive neutral face, we extracted the first and last frame of the video, respectively.
These stimuli were then grey-scaled and cropped to a standard width and height. From the larger set of emotional faces, we selected neutral poses before and after anger and joy expressions that were of similar orientation and quality. We were able to acquire 18 pre- and post-expressive EMOTION RESIDUE 8 anger pairs (5 female), and 20 pre- post-expressive joy pairs (8 females) of images. Figure 1 displays example stimuli.
Figure 1. Examples of pre- and post-expression neutral faces (top two rows), as well as Post- expression neutral minus pre-expression neutral subtracted image (bottom row).
Procedure
Participants were presented with each of the subtracted images and asked to rate it on both how positive and how negative the person in the image appeared. Responses were made on a 1 to 7 Likert-type scale with anchors “1 Not at all”, “4 Somewhat”, and “7 Very.” Positive and EMOTION RESIDUE 9 negative ratings were blocked such that participants rated all faces on either trait before doing the same for the remaining trait. Block order and stimuli presentation was randomized across participants.
Results
All of the repeated measures analyses reported were done using linear mixed effects models. Linear mixed effects models provide a number of advantages over classic repeated measures ANOVAs. Most notably for the current analyses, linear mixed effects models allow for missing data, do not require an assumption of independence, and can simultaneously account for the random variation of both participants and stimuli (Judd, Westfall, & Kenny, 2012).
We conducted a 2 (prior expression: anger/joy) by 2 (rating valence: positive/negative) linear mixed model to examine whether residue faces were rated differently on overall positivity and negativity. There was a main effect of prior expression, F(1, 36) = 23.73, p < .001, such that faces that had previously expressed anger (estimated marginal mean (EMM) = 1.78) were overall rated lower than faces that previously expressed joy (EMM = 2.20). There was no main effect of valence.
Critically, however, these main effects were qualified by a prior expression by valence interaction, F(1, 2811) = 35.75, p < .001. Probing this interaction revealed that the relative differences between the residue types were significantly different from each other. Specifically, anger residue was rated higher on negativity (estimated marginal mean (EMM) = 1.99) than positivity (EMM = 1.58), t(2811) = 4.70, p < .001. Further, joy residue was rated higher on positivity (EMM = 2.36) than negativity (EMM = 2.05), t(2811) = -3.73, p < .001. The full linear mixed model table is reported in the Supplemental Materials 2.
Study 2: EMOTION RESIDUE 10
Identifying Emotion Residue on Neutral Displays
Having successfully identified that there is a quantifiable difference between pre- and post-expression neutral images, and that participants are able to utilize this information when making trait judgements, Study 2 examines whether emotion residue is detectable in unaltered face images.
Method
Power analysis
A power analysis for a single sample t-test with a medium effect size (d = 0.5), and an alpha of 0.80 revealed a necessary minimum sample size of approximately 34 participants.
Participants
Participants (N = 78; 41 females, 32 males, 5 unreported, Mage = 18.46) were college students from a large public university. Six participants were excluded from data analysis for either not completing the study (n = 4) or because they scored 0% correct on the task (n = 2), suggesting inattention to directions or an opposite mental mapping to the directed key pairings.
Each participant received course credit in exchange for participation in the study.
Study Stimuli
Stimuli were the same 38 pre- and post-expressive neutral pairs discussed above. Forty- three additional neutral face pairs, on which no expressions were made before, served as filler items being pre-rated for another study, and thus are not included in the current analysis.
Procedure
Participants read instructions detailing that the face pairs they were about to see came before and after an actor made an expression. They were then tasked with “indicating which face came after the actor felt/expressed a certain emotion.” Following these instructions participants EMOTION RESIDUE 11 were randomly presented with a pre- and post-expressive neutral or filler neutral pair from the pool of 81 faces. The face remained on the screen until the participant made a response.
Participants were told to press the “e” key if they believed the post-expressive face was the one on the left side of the screen, and to press the “i” key if they believe the post-expressive face was on the right side of the screen. The side that the post-expressive face appeared on was randomized across trials, and for specific face pairs, between participants. Between each trial there was a 150 ms fixation cross.
Results
This type of experimental design lends itself to being analyzed using Signal Detection
Theory (SDT). According to SDT, the sensitivity (d ') at which a signal can be perceived can be estimated by: d'=Z ( H ) −Z (F)
Where Z represents the inverse of the cumulative gaussian distribution function, H corresponds to “hit rate”, and F corresponds to the “false alarm rate. For this study we represent a “hit” as when a participant correctly selects a face that contains emotion residue on a given trial, and a “false alarm” as when a participant selects a face that contains no emotion residue. In accordance with standard reporting procedures for a two-alternative forced-choice (2AFC) design, we divided d' by √2. We estimate the significance of sensitivity through 95% confidence intervals (CIs) using non-parametric bootstrapping with 10,000 samples.
However, because sensitivity is a dimensionless statistic, we also include t-tests as a traditional estimate of significance and effect size. To do so, we calculated for each participant a proportion of correct responses utilizing a single sample t-tests with a true mean of 0.5 (i.e., chance levels for a 2AFC design). EMOTION RESIDUE 12
In line with our hypotheses, individuals were able to successfully and accurately discriminate pre- from post-expressive neutral faces, t(69) = 7.44, p < .001, d = 0.90. On average, participants were able to determine which of two neutral faces was the post-expressive face with an accuracy of 58.6% CIs [0.56, 0.61], and the sensitivity for accurately discriminating post-expressive from pre-expressive faces was d'= 0.25, CIs [0.19, 0.32]1.
Study 3:
The Influence of Emotion Residue on Impression Ratings
Study 2 examined whether individuals can discriminate between unaltered pre- and post- expressive neutral faces. Having established that people can correctly identify emotion residue, in the next phase of the study, we examined whether this emotion residue meaningfully influences impressions derived from natural, non-manipulated neutral faces.
Method
Power analysis
We conducted a power analysis on the critical three-way interaction term (i.e., valence of impression ratings by prior expression by pre- or post-expression neutral) utilizing the same procedure outlined in Study 1. However, this time we utilized the effect size obtained from Study
1 as our estimate (0.73). Based on these simulated calculations a sample size with a minimum of
20 participants per group would be necessary to detect an effect size of 0.73 at 80% power. We estimated our power (given our actual sample size) to be 100%, CIs [99.63, 100.00], with an effect size of 0.73, an alpha set at 0.05, and 1000 simulations.
Participants
Participants (N = 103; 43 females, 58 males, 2 unreported, Mage = 18.67) were college
1 We replicated the effects reported in Studies 2 and 3 in a separate group of participants. See Supplemental Materials S5 for details. EMOTION RESIDUE 13 students from a large public university. Each participant received course credit in exchange for participation in the study. Three participants were excluded from analysis because they did not complete the entire study. Remaining participants were randomly assigned to one of two conditions: 1) pre-expressive (n = 49), 2) post-expressive (n = 54).
Stimuli
The same post-expressive anger and joy neutrals used for experiment 2 were used as the stimuli for a total of 38 pre- and 38 post-expressive stimuli.
Procedure
Trait ratings were blocked and randomized across participants. Participants rated each of either the pre- or post-expression neutral faces (randomly presented) on a single trait before moving on to another trait. Participants read, “how [trait] does this person appear?” and then used a seven-point Likert-type scale with anchors, 1 - “Not at all”, 4 - “Somewhat”, and 7 -
“Very” to make their rating. We selected highly negative traits and highly positive traits. The negative traits included: angry, deceptive, troublesome, rude, uncivil, and introverted. The positive traits included: happy, creative, smart, enthusiastic, admirable, trustworthy, and extraverted. In a pilot study, these traits showed no difference in mean ratings (See Supplemental
Materials 3 for collection details).
Results
In order to examine how prior expression influenced trait ratings, we pre-processed the data in the following manner: First, we subtracted 1 from each score so that the range of scores for each trait fell between 0-6. Next, for each participant we computed an average negative and positive trait score by averaging the negatively (angry, deceptive, troublesome, rude, uncivil, and introverted) and positively (happy, creative, smart, enthusiastic, admirable, trustworthy, and EMOTION RESIDUE 14 extraverted) valenced trait impressions, respectively. The magnitude of each positive and negative trait impression index served as the dependent variable. Finally, we subjected these positive and negative scores to a linear mixed model with fixed effects for impression valence
(positive, negative) and prior expression (angry or happy, as well as their interaction. We included random intercepts for each subject and each face.
We conducted a 2 (prior expression: anger/joy) by 2 (impression valence: bad/good) linear mixed effects model to determine whether post-anger versus post-joy neutral faces were evaluated differently on overall positivity and negativity scores. We included ratings of corresponding pre-expressive neutral face scores as a covariate to control for any face-specific variance that might be present across the faces in our sample.
There was a main effect of valence, F(1, 7603.8) = 127.27, p < .001, such that faces were rated overall more negatively (EMM = 2.65) than they were positively (EMM = 2.39). There were no other main effects. However, the predicted emotion by valence interaction was significant, F(1, 7603.8) = 780.43, p < .001.
Probing this interaction revealed that post-anger neutral faces were rated higher in negativity (EMM = 2.95) than positivity (EMM = 2.05), t(7604) = 27.36, p < .001. Similarly, post-joy neutral faces were rated higher in positivity (EMM = 2.73) than negativity (EMM =
2.35), t(7604) = -11.94, p < .001. Also as expected, post-anger neutral displays were rated more negatively compared to post-joy neutral displays, t(45.6) = 9.82, p < .001, and post-joy neutral displays were rated with more positivity compared to post-anger neutral displays, t(45.6) = -
11.01, p < .001.
Figure 2 displays the contrasts for each individual impression for post-expressive faces.
The full linear mixed model table and contrasts for individual impressions are reported in the EMOTION RESIDUE 15
Supplemental Materials 4.
For the sake of completeness, we also examined direct comparisons of pre- vs. post- expression neutral faces. Post-joy expressive neutrals (EMM = 2.73) were rated higher on positive traits than pre-joy expressive neutrals (EMM = 2.57), t(3821) = -8.03, p < .001. Post-joy neutrals (EMM = 2.34), however, showed no differences on negative traits copared to pre-joy neutrals (EMM = 2.39), t(114) = -0.55, p = .58. Post-anger expressive neutrals (EMM = 2.95) were rated higher on negative traits than pre-anger expressive neutrals (EMM = 2.64), t(3429) =
19.39, p < .001. Post-anger neutrals (EMM = 2.05) were also rated lower on positivity than pre- anger neutrals (EMM = 2.39), t(105) = -3.38, p = .001.
Anger Happy 3 e
s 2 n o p
s Condition e Pre R Post n a
e 1 M
0
ve ve ve ve ti ti ti ti a i a i g s g s e o e o N P N P Impression Rating
Figure 2. Mean ratings for each set of impressions (positive and negative). Dark grey bars represent pre-expression neutrals, dark grey bars represent post-expression neutrals. X-axis EMOTION RESIDUE 16 represent impression valence. Positive impressions include happy, creative, smart, enthusiastic, admirable, trustworthy, and extraverted. Negative impressions include angry, deceptive, troublesome, rude, uncivil, and introverted. Each panel (left vs. right) is what emotion was expressed between each neutral. Error bars represent 95% confidence intervals.
General Discussion
The current work offers evidence that emotion residue remaining in faces intended to display neutrality meaningfully influence trait impression formation. We show that faces explicitly intended to display no expressive cues nonetheless still convey emotional tone of prior expressions.
In Study 1 we found that there was a quantifiable difference between pre- and post- expression neutral images, thereby isolating emotion residue in post-expressive neutral faces. We then found that this residue offered enough information itself to influence impression formation ratings in a manner consistent with the valence of the prior expression. In Study 2, we found that this emotional tone was not only discernably through pixel-by-pixel computer vision analysis, it is readily detectable by human observers when seen naturistically on post-expressive neutral facial displays. The ability to overtly discern a pre-expressive neutral from a post-expressive neutral display suggests that despite both faces being objectively rated and subjectively posed as
“neutral,” participants can nonetheless detect subtle changes between the two images that cue emotionality. Finally, in Study 3, this emotion residue influenced trait impression formation: post-anger neutral displays were rated more negatively compared to post-joy neutral displays, and post-joy neutral displays were rated with more positivity. Taken together, the results demonstrate that despite the explicit intention to display neutrality, emotion residue remains following an expression, this residue is detectable, and it has a clear and predictable impact on EMOTION RESIDUE 17 positive and negative trait impressions.
Research has shown that stable personality trait inferences are derived from facial expressions (Knutson, 1996). Our attunement to expression is so important for social-visual navigation, despite at times yielding inaccurate impressions, we are even prone to making spontaneous inferences based on facial features that merely resemble emotion expression.
(Adams et al., 2016; Todorov, Said, Engell, & Oosterhof, 2008; Zebrowitz). Thus from both overt and subtle emotion-resembling cues in the face, observers derive stable trait impressions
(Adams et al., 2016; Hareli, Shomrat, & Hess, 2009), making what appear to be face specific fundamental attribution errors (Albohn, Brandenburg, & Adams, forthcoming). The current work shows this fine-grained attunement to expressive cues enables us to pick up on emotion residue, very subtle emotion cues that remain on the face even after someone attempts to display neutrality. The results across three studies confirm that emotion residue does remain on a face even when participants are instructed to pose neutral displays, devoid of any emotion, and that this residue exerts a powerful influence on trait impressions.
So, is there a true “neutral” facial display?
Despite the rich empirical treatment of face perception, and extensive research on the impact of neutral facial appearance on social preference, person perception etc., definitions of
“neutral” remain scarce and inconsistent. For instance, Ekman and colleagues considered neutral to be the “baseline for the actor” (Ekman & Friesen, 1978, p. 73), while others consider it as existing at the midpoint of a 2-dimensional plane consisting of a horizontal “arousal” dimension, and a vertical “valence” dimension. Russell (1980) describes what exists at the intersection of these two dimensions as an “average, everyday feeling” (p. 501), and researchers have shown that neutral expressions tend to cluster around this midpoint when compared to expressive faces EMOTION RESIDUE 18
(Carrera-Levillain & Fernandez-Dols, 1994).
Emotion residue suggests that our face may never truly be a “blank slate.” Indeed, attempts at an effortful display of a neutral visage do not appear to wipe away all prior affective information. Because we are constantly expressing ourselves to one another via the face, it is important to understand how, even when we are not overtly emoting, lingering emotional tone on our face can impact others’ impressions. Interpreted in another manner, one could draw the conclusion that we simply cannot conceal our internal states or prior expressions, even when deliberately attempting to do so through our own volition or being asked to by someone else.
This interpretation seems logical given the observation that individuals–particularly those closest to us–can seemingly infer when something is “wrong” despite our best efforts to act as though all is normal. That we seldom exhibit a truly neutral display may allow for accurate impressions of others even from their so-called neutral faces.
Conclusions
Researchers have examined the “neutral face” for decades, detailing when and why a specific set of facial features will be evaluated one way over another, the influence that sociodemographic factors such as age and sex/gender have on neutral face perception, and how these all interact to form consistent and stable impressions that observers appear to be able to draw from neutral faces. Our results extend this work by showing that objectively rated, intentionally posed neutral faces nonetheless convey actual lingering expressive content. Further, this emotion residue serves as a mechanism through which trait impressions from a face are derived. Our findings indicate that people’s impressions are at times tuned into actual, residual emotional information in a face, even when they are intentionally posed as neutral. If people chronically express certain emotions, what our work suggests is that attempts at displaying EMOTION RESIDUE 19 neutrality will likely fail to mask this. Indeed, across a lifetime, the expressions we wear on our faces do appear to get etched into age-related facial appearance, enough so that we are able derive accurate impressions of others’ emotion dispositions (Adams et al., 2016; Malatesta et al.,
1987). The current work reveals that emotional tone does not need years to be etched into a face, but lingers after every day expression, even in young adult faces attempting to convey neutrality. EMOTION RESIDUE 20
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