ORI GIN AL PA PER

Secrets and Lies: Involuntary Leakage in DeceptiveFacial Expressions as a Function of Emotional Intensity

Stephen Porter • Leanne ten Brinke • Brendan Wallace

Published online: 9 October 2011� Springer Science+Business Media, LLC 2011

Abstract Darwin (1872) hypothesized that some facial muscle actions associated with

emotion cannot be consciously inhibited, particularly when the to-be concealed emotion is

strong. The present study investigated emotional ‘‘leakage’’ in deceptive facial expressions

as a function of emotional intensity. Participants viewed low or high intensity disgusting,

sad, frightening, and happy images, responding to each with a 5 s videotaped genuine or

deceptive expression. Each 1/30 s frame of the 1,711 expressions (256,650 frames in total)

was analyzed for the presence and duration of universal expressions. Results strongly

supported the inhibition hypothesis. In general, emotional leakage lasted longer in both the

upper and lower face during high-intensity masked, relative to low-intensity, masked

expressions. High intensity emotion was more difficult to conceal than low intensity

emotion during emotional neutralization, leading to a greater likelihood of emotional

leakage in the upper face. The greatest and least amount of emotional leakage occurred

during fearful and happiness expressions, respectively. Untrained observers were unable to

discriminate real and false expressions above the level of chance.

Keywords Universal emotions � Facial expression � Deception � Emotional intensity

Introduction

During his 1938 Munich meeting with Hitler, British Prime Minister Neville Chamberlain

scrutinized Hitler’s face as he swore that he would not invade Czechoslovakia. After the

meeting, Chamberlain infamously reported, ‘‘I got the impression that here was a man who

could be relied upon when he had given his word’’ (see Porter and ten Brinke 2010, Ekman

1985/2001). How could he have made such a cataclysmic error in misreading Hitler’s

deceptive face?

S. Porter (&) � L. ten Brinke � B. WallaceCentre for the Advancement of Psychological Science and Law, Department of Psychology,University of British Columbia, Kelowna, BC V1V 1V7, Canadae-mail: stephen.porter@ubc.ca

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J Nonverbal Behav (2012) 36:23–37DOI 10.1007/s10919-011-0120-7

The complex musculature of the human face and its direct relation with affective

processes of the brain make it a rich canvas upon which humans communicate their

emotional states and from which we infer those of others. Accordingly, in daily life we

read the faces of intimates and strangers to make inferences about their emotions and

intentions, and adopt expressions ourselves to communicate sincerely or insincerely how

we are feeling. Accurately assessing the nature and veracity of others’ facial expressions is

a serious business in everyday life (e.g., Hess and Bourgeois 2010) and applied settings. In

the context of personal relationships, the presence of concealed but subtly communicated

negative emotional expressions is highly predictive of divorce (Gottman et al. 2001).

Further, the identification of falsified emotional information is crucial in many applied

contexts in society, including the courts, parole hearings, politics, and corporations.

The Supreme Court of Canada (R. v. B. (K. G.) 1993) concluded that judges and jurors

must view a witness to ‘‘adequately evaluate body language, facial expressions and other

indicators of credibility’’ and that credibility assessment is ‘‘common sense.’’ In a recent

landmark Canadian case R v N.S. (2010), the Ontario Court of Appeal—in deciding

whether to permit a Muslim complainant to wear her face-covering niqab during testi-

mony—concluded that: ‘‘Covering the face of a witness may impede cross-examination in

two ways. First, it limits the trier of fact’s ability to assess the demeanour of the witness.

Demeanour is relevant to the assessment of the witness’s credibility and the reliability of

the evidence given by that witness. Second, witnesses do not respond to questions by words

alone. Non-verbal communication can provide the cross-examiner with valuable insights’’

(p. 54). In sentencing and parole hearings, the perceived credibility of an offender’s

emotional display/remorse informs decision-making (ten Brinke et al. 2011). Further,

travelers’ faces are scrutinized by airport security staff trained in detecting concealed

emotions and intentions (see Porter and ten Brinke 2010).

The foundation of this evaluative process originates in our evolutionary past; the basic

discrimination of friend and foe likely was one of the earliest interpersonal judgments to

evolve (e.g., Williams and Mattingley 2006). Sometimes emotion is ‘‘written all over the

face’’, a salient and powerful representation of one’s affective state (Matsumoto 2007;

Matsumoto and Willingham 2009). However, the evolutionary development of interper-

sonal deception—partially accomplished by altering or inhibiting an expression normally

accompanying the emotion—magnified the complexity of interpreting facial expressions.

There are three major ways in which emotional facial expressions are intentionally

manipulated (Ekman and Friesen 1975): an expression is simulated when it is not

accompanied by any real emotion, masked when the expression corresponding to the felt

emotion is replaced by a falsified expression corresponding to a different emotion, or

neutralized when the expression of a genuine felt emotion is inhibited while the face

remains neutral. These deceptive displays can be highly convincing; observers often are

unable to discriminate genuine versus faked expressions (Porter and ten Brinke 2008;

Porter et al. 2010), despite high self-reported confidence in their assessments (Vrij and

Mann 2001).

Thus, as with Chamberlain, mistakes in reading faces occur frequently and sometimes

with major consequences. In corporate settings, white-collar criminals such as Bernard

Madoff often find easy victims by appearing trustworthy, empathetic, and displaying

convincing emotional masks. Porter et al. (2009) found that psychopaths were 2.5 times as

likely as their counterparts to be granted parole in National Parole Board hearings, a

pattern the authors attributed in part to their convincing emotional performances. Indeed,

psychopaths seem particularly proficient at stifling emotional facial inconsistencies (Porter

et al. 2011).

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Although emotional performances often are thoroughly misinterpreted, emotional

deception may be expressed in subtle but reliable and perceptible ways that are sometimes

missed by untrained observers. This idea first was studied by Duchenne (1862/1990), who

examined the muscle actions of the smile. He noted that the common conceptualization of

a happiness expression is the contraction of the zygomatic major muscle, which upturns the

mouth corners. But when he electrically stimulated this muscle, the resulting smile did not

seem ‘‘genuine.’’ As it turned out, real happiness also involves the orbicularis oculi sur-

rounding the eyes, which pull the cheek up while slightly lowering the brow (e.g., Ekman

et al. 1990).

Darwin (1872), of course, was interested in emotional expressions (Hess and Thibault

2009) and observed that, ‘‘A man when moderately angry, or even when enraged, may

command the movements of his body, but…those muscles of the face which are least

obedient to the will, will sometimes alone betray a slight and passing emotion’’ (p. 79). He

hypothesized that some facial muscle actions associated with strong emotion are beyond

voluntary control and cannot be completely inhibited. Further, he proposed that certain

facial muscles cannot be intentionally engaged during emotional simulation. Collectively,

these two propositions form the inhibition hypothesis (Ekman 2003a, 2009), a proposal

with major theoretical and applied implications but one that has hardly been examined. A

derivative idea long advocated by Ekman (Ekman 1985/2001; Ekman and O’Sullivan

2006; Haggard and Isaacs 1966) is that when an emotion is concealed or masked, the true

emotion is manifested as a micro-expression, a fleeting expression suppressed in 1/25–1/5

of a second making it difficult to perceive with the naked eye. This hypothesis has been

accepted somewhat non-critically in the scientific community and media (e.g., Henig 2006;

Lipton 2006). In fact, although the validity of these hypotheses, and more generally the

idea that the face involuntarily communicates covert emotional states, are widely assumed,

they have been subjected to relatively little direct empirical scrutiny (Ekman et al. 1988,

1991; Porter and ten Brinke 2008; Stewart et al. 2009).

One might argue that the face is largely uncharted terrain in terms of the richness of the

information it may communicate relative to the empirical attention it has received. Porter

and ten Brinke (2008) investigated the nature of facial expressions accompanying genuine

and false/concealed emotions. They found that the involuntary leakage of emotions was, in

a way, ubiquitous—no participant was able to falsify emotions without such betrayals on at

least one occasion. Emotional arousal associated with this form of deception also was

revealed by changes in blink rate; masking one’s true feelings with a false emotion led to

increases in blink rate while holding a neutral ‘‘poker face’’ in response to emotional

stimuli led to decreased blink rate, relative to genuine expressions. Despite the presence of

cues to deceit indicated by these analyses, naı̈ve judges could only discriminate genuine

versus deceptive expressions at a level slightly above chance (above chance for happiness

and disgust but at chance for sad and fearful expressions; see also Ekman et al. 1988 and

Frank et al. 1993 for discrimination of genuine vs. deceptive smiles). Similarly, Warren

et al. (2009)—utilizing Ekman and Friesen’s (1974) emotional fabrication paradigm—

found that performance for emotional lie detection was slightly but significantly above

chance (mean of 64.4%), while that for unemotional lie detection was significantly below

chance (36.1%). Indeed, this may have been related to the leakage of discordant emotions

during fabricated, emotional lies. Other lie scenario variables too seem to influence ability

to detect deceit; police officers are better at detecting high stakes lies, relative to low

(O’Sullivan et al. 2009). In general, however, while lie scenario or individual differences

may produce slight advantages over chance, deception detection accuracy remains sub-par

without empirically-based training.

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Darwin’s (1872) hypothesis stated only that strong emotions would be difficult to

conceal or fabricate. No research has examined directly the intensity of emotion required

for ‘‘leakage’’ to occur in facial communication. Does emotional leakage occur only when

concealing powerful emotions, or is ‘‘more leakage’’ exhibited during such emotions

relative to lower intensity emotions? We hypothesize that powerful emotional states will be

relatively unique in leading to leakage in involuntary facial expressions, similar to an

involuntary reflex of the knee requiring contact with a minimum level of force. Emotional

leakage during high intensity deception specifically may relate in part to a reduction in

attentional resources. Gable and Harmon-Jones (2010) found that low intensity emotion

increases the breadth of one’s attention whereas high intensity narrows one’s attentional

focus. It is possible that experiencing and trying to inhibit or mask powerful emotions—

relative to weaker emotional states—require so much competing cognitive, physiological,

and affective effort that one’s voluntary control is compromised or eliminated resulting in

leakage.

The Present Study

While the interpretation of emotional facial expressions has been complicated by the

evolutionary development of interpersonal deception, it appears that certain aspects of the

face cannot be controlled. As such, the face has the potential to reveal hidden emotions

with objective analysis. However, little research has been conducted that investigates the

inhibition hypothesis and the secrets of the human face. A key remaining question is does

emotional ‘‘leakage’’ occur only for powerful emotions, or is there ‘‘more leakage’’ in such

emotions versus lower intensity emotions? The present study was the first to directly test

the proposition that intensity has an impact on the presence and duration of emotional

leakage during simulated, masked, and neutralized expressions. We tested the hypothesis

that concealed felt emotions must be relatively potent in order for ‘‘leakage’’ to appear

involuntarily on the face, and that less powerful emotional states will be easily concealed

or masked (i.e., under voluntary control).

Specifically, we predicted that more inconsistent emotional expressions would appear in

deceptive versus honest expressions, and a veracity by intensity interaction such that

inconsistent emotion would be least prevalent in high intensity genuine expressions and

most prevalent in high intensity masked expressions (replacing one’s emotion with a

different opposing emotion) followed by low intensity masked expressions, high intensity

neutralized expressions, and low intensity simulated expressions. Further, it was expected

that neutralizing high intensity emotions (trying to appear as though one is feeling no

emotion) would lead to greater emotional leakage than neutralizing low intensity emotion.

Because emotions generally involve muscles in both the upper and lower face, but some

muscles may be less controllable than others, emotional expression in the upper (eyes and

forehead) and lower (nose and mouth) face were coded separately to allow for accurate

facial coding when, for example, the eyebrows lowered as in disgust, but the mouth leaked

genuine happiness (Rinn 1984).

We also examined observers’ accuracy at identifying high versus low intensity

emotional deception. Given our prediction that more leakage will occur in high intensity

emotional deception, it was hypothesized that observers would perform somewhat better

at detecting such deception (slightly better than chance as found in Porter and ten

Brinke 2008) and around the level of chance/guessing with low intensity emotional

deception.

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Method

Participants

The primary sample was comprised of N = 59 participants (19 male, 40 female;

M age = 20.26 years, SD = 3.62) attending a Western Canadian university. An additional

28 (21 female, 7 male; M age = 19.14 years, SD = 1.14) participants participated as

untrained observers of the facial expressions; they were asked to assess the veracity of the

participants’ emotional expressions in real-time and it was anticipated that their presence

during the emotional displays would increase the realism of the experiment and the

motivation of the primary participants.

Materials

The images used to evoke emotion in this study were chosen from the International

Affective Picture System (IAPS; Lang et al. 1999). These images have been normed on

emotional valence, arousal, and the discrete emotion type that they evoke in viewers

(Mikels et al. 2005); images were selected based on these ratings. Images normed by Mikels

et al. (2005) as primarily evoking sadness, disgust, fear, contentment, and amusement (low

and high happiness, respectively) were considered for use as stimuli (i.e., images evoking a

combination of emotions, like sadness and disgust, were removed from the pool of potential

stimuli). High and low intensity emotional images then were chosen based on IAPS

(Libkuman et al. 2007) arousal norms (rated on a 1–9 Likert scale). The images were

selected to evoke either high or low intensity happiness, fear, disgust, or sadness, and

neutral/no emotion.1 For example, images included a smiling baby in the high-intensity

happy condition to a severed hand as a high-intensity disgusting image. Analysis of these

images revealed significant differences in arousal ratings of high (M = 5.89, SD = 0.75)

and low (M = 4.40, SD = 0.86) intensity images, t(22) = -4.54, p \ .01. Positive (high

and low intensity happiness) (M = 7.58, SD = 0.46), negative (high and low intensity

sadness, fear and disgust) (M = 3.27, SD = 0.84) and neutral (M = 4.82, SD = 0.21)

images were all significantly different on valence ratings, F(2,29) = 137.54, p \ .01.

Procedure

A 27-inch monitor was used to display the images. While viewing emotional images,

participants were recorded using a 30-frame per second Sony HD camcorder. The design of

the room was such that the primary sample participants sat approximately one meter away

from the display on which they viewed a timed Powerpoint presentation of images. The

camcorder was situated directly behind the display to record the participant’s face with a

direct field of view. The observer participant sat behind the camcorder and to the partic-

ipant’s right field of view.

Participants were run individually and presented with a slideshow of images that were

high or low in emotional intensity and varied in emotional valence. They were instructed to

1 Mean arousal ratings for each emotion, by intensity, were as follows: high happiness (M = 5.40), lowhappiness (M = 4.03), high sad (M = 5.86), low sad (M = 3.94), high fear (M = 6.61), low fear(M = 6.17), high disgust (M = 6.46), low disgust (M = 4.25), and neutral (M = 3.04). Mean valenceratings were: high happiness (M = 7.56), low happiness (M = 7.60), high sad (M = 2.30), low sad(M = 4.00), high fear (M = 3.90), low fear (M = 4.03), high disgust (M = 2.31), low disgust (M = 3.28),and neutral (M = 4.82).

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produce facial expressions that were genuine (felt emotion will be expressed), simulated(expressed emotion with no emotion felt), masked (felt emotion will be covered by

opposing emotional expression), or neutralized (despite presence of a felt emotion, no

emotion will be expressed on the face) while attending to the emotional image on the

screen. Participants were monitored by the naı̈ve observers—who recorded dichotomously

whether they believed each expression observed was sincere or insincere—and were

videotaped (at a rate of 30 frames per second) for later analysis.

The emotional image slideshow consisted of 29 images. Each was displayed for 5 s with

a 5 s break between images to allow the participants to return to a neutral face. Images were

divided into sets, which were prefaced with instructions about how to respond to the

subsequently presented images. Five images were presented in each emotion set, excluding

the neutral set, which consisted of nine images. Participants were instructed to respond with

the same facial expression to each of the images in that set, while maintaining their gaze at

the screen. In each of the four 5-image sets, there was a high and low intensity emotional

image that was consistent with the expressed emotion (i.e., resulting in genuine expres-

sions), a high and low intensity emotional image evoking an emotion opposite to what was

expressed (i.e., resulting in masked expressions), and a neutral image (i.e., resulting in a

simulated expression). For example, in the happiness set a participant would see an initial

screen stating ‘‘Please respond to the following five images with the expression of happi-

ness’’. Participants then viewed images of high and low intensity happy (genuine) and sad

(masked) images, along with one neutral (simulated) image. Participants were asked to

conceal their felt emotions by adopting a neutral face in response to each of the nine images

(one high and low intensity happy, sad, fearful and disgusting image, in addition to one

neutral image) comprising the neutral set (i.e., neutralized expressions). The order in which

the sets were presented, and the order of the images within each set, was randomized.

Further, to confirm that the normed emotional stimuli indeed elicited the intended (genuine)

emotions, participants rated their own emotional experiences (valence and arousal) for each

image following the presentation of the image sets using 1 (not at all) to 7 (highly) scales.

Emotion Expression Analysis

Coding of the emotional expressions was conducted using a highly reliable coding pro-

cedure developed for Porter and ten Brinke’s (2008) study, founded on the Facial Action

Coding System (FACS; Ekman et al. 2002), with particular attention to upper and lower

face action units associated with each emotion (Emotion Facial Action Coding System;

EMFACS) and Pictures of Facial Affect which served as prototypical examples for each

emotion (POFA; a set of photographs of expressions depicting the universal emotions;

Ekman and Friesen 1976). For facial coding, each 1/30th second frame of the videotaped

clips was analyzed (150 frames/each 5-s clip) for the presence and duration (from onset to

offset) of the universal emotional expressions in the upper and lower facial regions (by two

trained ‘‘blind’’ analysts). The upper facial region corresponds to the eye and forehead

regions, and the muscles underlying the upper-face action units in the FACS; these muscles

include the frontalis, corrugator, orbicularis oculi, and procerus. The lower facial region

corresponds to the nose, mouth, cheek, and chin areas; the muscles involved include the

risorius, orbicularis oris, zygomatic major, and mentalis). Coders were blind to the veracity

of the emotions they were analyzing (i.e., whether participants were displaying genuine,

simulated, masked, or neutralized expressions), but aware of the emotions participants

intended to portray. They coded a total of 256,650 frames twice each (once focused on

upper face emotion and again for the lower face) in 1,711 expressions. Coding required

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classifying the emotion exhibited in each facial region and recording the frame/time at

which these expressions began and ended. Inconsistent emotions lasting from 1/25 to 1/5th

of a second were recorded as ‘‘Ekman (1985/2001) micro-expressions’’.

Training in this method involves facial musculature recognition, memorization of facial

action units associated with universal emotions, and identification of the seven universal

emotions. One of the analysts was previously trained for the Porter and ten Brinke (2008)

study. The second analyst was trained for two weeks in the coding procedure. Both coders

studied facial musculature, facial action units associated with the universal emotions, and

the identification of universal emotional expressions extensively. To facilitate training, we

have created a detailed reference guide that includes numerous examples of each emotion

and the main muscle movements involved. Training with this reference guide was com-

plemented by detailed study of the POFA and by practice/expertise with the FACS,

although the FACS was not formally used for coding. In addition, the coders reviewed

studies investigating facial actions involved in the universal emotional expressions (Kohler

et al. 2004; Suzuki and Naitoh 2003).

So that we could assess the coders’ knowledge level after training, coders viewed a slide

show of 50 faces from the POFA database and classified the emotion expressed in each

image. Additionally, they viewed 48 videos in a micro-expression task similar to that used

by Frank and Ekman (1997). Each of these videos included a 1/25-s glimpse of one still

picture of facial affect embedded within another, different expression, and coders were

required to classify the emotion in the micro-expression image. The two coders obtained

accuracy rates of 100 and 96% on the POFA task, and 98 and 96% on the micro-

expression-identification task. Finally, they practiced frame-by-frame video analysis of

emotional facial expressions by coding the video of a sample participant until they were

able to attain nearly perfect reliability.

Coding Reliability

To examine inter-rater reliability statistically, we had both coders analyze the complete

videos of nine participants (261 expressions or 39,150 frames, each coded twice—once for

the upper, and once for lower face emotional expression). Inter-rater reliability was at least

‘‘good’’ (as defined, e.g., by Cicchetti and Sparrow 1981, and Fleiss 1981) on all indices.

The coders demonstrated good reliability in coding the presence of inconsistent emotions

(i.e., any emotional expression discordant with the intended expression, not including

neutral/no emotion) and the duration of the displays, Kappa = .70, p \ .001, 87.3%

agreement, and r(520) = .75, p \ .001, respectively. The raters averaged 92.18%

(SD = 17.79) agreement on the number of inconsistent frames per expression. Disagree-

ment in coding a frame as inconsistent was infrequent, occurring for an average of 12.28

(SD = 27.24) frames for the upper face and 11.14 (SD = 26.14) frames for the lower face,

out of 150 frames per expression (i.e., the coders agreed on an average of 137.72 and

138.86 frames for the upper and lower face, respectively).

Results

Ensuring that Participants Experienced the Intended Emotion

Because participants were instructed to exhibit particular expressions in response to the

normed stimuli, we wanted to ensure that the intended genuine emotions were experienced.

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As such, we had participants rate their own emotional reactions (valence and arousal) to

the images on 7 point scales. Indeed, analyses of mean ratings of emotional valence and

arousal replicated those conducted using IAPS norms. Analysis of participant ratings (on a

1–7 Likert scale) revealed significant differences in arousal ratings of high (M = 5.16,

SD = 0.50) and low (M = 4.37, SD = 0.52) intensity images, t(22) = -3.78, p \ .01.

Positive (high and low intensity happiness) (M = 5.71, SD = 0.51), negative (high and

low intensity sadness, fear and disgust) (M = 2.30, SD = 0.65), and neutral (M = 4.06,

SD = 0.05) images were all significantly different on valence ratings, F(2,29) = 137.54,

ps \ .01.

Testing the Inhibition Hypothesis

Due to the within-subjects study design and the greater number of images in neutral,

relative to happy, sad, fear or disgust sets, the inhibition hypothesis was examined in two

independent sets of statistical tests. Specifically, the impact of emotional intensity on the

frequency and duration of emotional leakage was examined in genuine versus masked

expressions and in genuine neutral versus neutralized expressions, separately. Potential

differences in blink rate also were examined in genuine versus masked expressions and in

genuine neutral versus neutralized expressions, separately.

Inconsistent Emotional Leakage

Impact of Emotional Intensity in Genuine Versus Masked Expressions

First, a 4 (expressed emotion: happy, sad, fear disgust) 9 2 (veracity: genuine, masked) 9

2 (intensity: high, low)2 MANOVA was conducted to evaluate the effect of emotional

intensity on the presence of inconsistent emotion in the upper and lower face. A significant

multivariate main effect of expressed emotion was revealed, F(6,53) = 28.28, p \ .01,

gp2 = .76. This effect was present for the both upper (F(3,174) = 19.68, p \ .01, gp

2 = .25)

and lower face (F(3,174) = 40.99, p \ .01, gp2 = .41). An examination of means suggests

that inconsistencies were most likely to occur in fearful expressions (upper face: M = 0.48,

SE = 0.05; lower face: M = 0.53, SE = 0.05) and least likely to occur during expressions

of happiness (upper face: M = 0.08, SE = 0.02; lower face: M = 0.03, SE = 0.01).

A significant expressed emotion 9 veracity interaction also was present at the multivariate

level, F(6,53) = 2.70, p \ .05, gp2 = .23. Follow-up univariate analyses revealed that this

effect held only for the upper face, F(3,174) = 4.05, p \ .01, gp2 = .07. While veracity did

not affect the presence of inconsistent emotions for either fearful or disgusting expressions

(ps [ .05), emotional leakage was more likely to occur in masked (M = 0.10, SE = 0.04)

than genuine (M = 0.05, SE = 0.02) expressions of happiness and in genuine (M = 0. 37,

SE = 0.05) than masked (M = 0.24, SE = 0.05) displays of sadness. Lastly, while the

intensity 9 veracity interaction only approached significance, F(2,57) = 1.81, p = .17,

gp2 = .06, there was a significant multivariate expressed emotion 9 intensity 9 veracity

interaction, F(6,53) = 4.28, p [ .01, gp2 = .33, which held for both the upper and lower

face, ps \ .01. In general, an examination of means revealed that masking high intensity

emotions resulted in a greater likelihood of inconsistent emotion for expressions of

2 In all analyses, the order of images to which the participants was assigned was included as a between-subjects variable. The effect of this variable was never statistically significant, p’s [ .05, and was droppedfrom subsequent analyses.

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happiness and sadness, but did not lead to greater emotional leakage during masks of fear

or disgust.

In addition, the impact of veracity and emotional intensity on duration of inconsistent

emotional expressions was examined using a 4 (expressed emotion) 9 2 (veracity) 9 2

(intensity) MANOVA. Duration of inconsistent emotional expressions in the upper and

lower face, respectively, served as dependent variables. A main effect of expressed

emotion was present at the multivariate level (F(6,53) = 15.73, p \ .01, gp2 = .64) and for

the upper and lower face independently, p’s \ .01. In general, the greatest amount of

emotional leakage occurred during fearful expressions (upper face: M = 35.09,

SE = 4.83; lower face: M = 46.10, SE = 6.14) while happiness expressions were the least

likely to include inconsistent emotions (upper face: M = 2.99, SE = 1.00; lower face:

M = 0.62, SE = 0.28). As the inhibition hypothesis would predict, our analysis revealed a

significant Intensity 9 Veracity interaction, F(2,57) = 4.28, p \ .05, gp2 = .13. Further,

this interaction was significant in both the upper (F(1,58) = 6.74, p \ .05, gp2 = .10) and

lower (F(1,58) = 4.49, p \ .05, gp2 = .07) face. In the upper face in particular, there was

significantly longer emotional leakage in the high intensity masked relative to the high

intensity genuine condition, p \ .05. Further, the difference between duration of emotional

inconsistency during high intensity masks (M = 23.67; 95% CI [17.89, 29.45]) and low

intensity masks (M = 18.56; 95% CI [12.59, 24.30]) approached significance (see Fig. 1).

This interaction is qualified by an expressed emotion 9 intensity 9 veracity interaction,

F(6,53) = 5.65, p \ .01, gp2 = .39. In general, emotional leakage was greater in both the

upper and lower face during high-intensity masked, relative to low-intensity masked,

expressions for all emotions except disgust.

Impact of Emotional Intensity in Neutralized Expressions

The impact of veracity and emotional intensity on duration of inconsistent emotional

expressions during emotion neutralization was examined using 4 (felt emotion) 9 2

(intensity) MANOVAs. First, the presence of inconsistent emotional expression in the

upper and lower face were the dependent variables. Although the main effect of intensity

did not reach statistical significance at the multivariate level, F(2,57) = 2.06, p = .14,

gp2 = .07, post-hoc univariate follow-up analyses revealed that this effect was significant in

the upper face, F(1,58) = 4.11, p \ .05, gp2 = .07. Emotional inconsistencies were more

Genuine, Low, 23.2

Genuine, High, 17.68

Masked, Low, 18.56

Masked, High, 23.67

Genuine

Masked

Fig. 1 Duration (in 1/30th-second frames) of inconsistentemotion in the upper face as afunction of intensity and veracity

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likely to occur during high (M = 0.14, SE = 0.03) relative to low (M = 0.09, SE = 0.02)

intensity neutralized expressions. Second, duration of inconsistent emotional expression

(measured in 1/30th-second frames) in the upper and lower face, respectively, served as

dependent variables. The analyses did not reveal any significant main effects or interac-

tion. However, there was a trend for high intensity emotions (M = 7.0, SE = 2.14) to be

revealed by emotional leakage of a longer duration than low intensity emotions (M = 5.13,

SE = 1.95) in the upper face, F(1,58) = 3.34, p = .07.

Ekman Micro-Expressions

No complete micro-expressions (1/25th–1/5th of a second) involving both the upper and

lower halves of the face simultaneously (as described by Ekman and Friesen 1975) were

detected in any of the 1,711 analyzed expressions. However, 15 participants exhibited 18

partial micro-expressions; 10 in the upper and 8 in the lower facial region. Of these, seven

occurred during the presentation of high intensity emotional images, and 11 during low

intensity emotional images. Six of the 10 micro-expressions that occurred during masked

and neutralized emotional portrayals were congruent with the deceivers’ felt emotion.

Blink Rate

Impact of Emotional Intensity in Genuine Versus Masked Expressions

A 4 (expressed emotion: happy, sad, fear, disgust) 9 2 (veracity: genuine, masked) 9 2

(intensity: high, low) repeated measures ANOVA was conducted to evaluate the effect of

veracity and emotional intensity on the number of blinks in each 5-second expression.

There was a significant main effect of expressed emotion, F(3,174) = 5.41, p \ .05,

gp2 = .09, such that the greatest number of blinks occurred during sad (M = 1.71,

SE = 0.19), followed by fearful (M = 1.49, SE = 0.16), happy (M = 1.28, SE = 0.16),

and disgust (M = 1.21, SE = 0.17) expressions. However, effects of veracity and intensity

were non-significant, ps [ .05.

Impact of Emotional Intensity in Neutralized Expressions

The impact of veracity and emotional intensity on blink rate during emotion neutralization

was examined using 4 (felt emotion) 9 2 (intensity) repeated measures ANOVA. A sig-

nificant effect of intensity was revealed, F(1,58) = 5.61, p \ .05, gp2 = .09, with high

intensity neutralized expressions being associated with fewer blinks (M = 1.25,

SE = 0.16) than low intensity (M = 1.44, SE = 0.15).

Accuracy of the Observers in Judging the Veracity of Expressions

A final question was whether the observers could identify deceptive facial expressions with

the naked eye. A 4 (expressed emotion: happy, sad, fear, disgust) 9 2 (intensity: high vs.

low) 9 2 (veracity: genuine vs. masked) was conducted to test the hypothesis that high

intensity deceptive emotions would be easier for naı̈ve observers to detect than low

intensity emotional deception. However, this analysis did not yield any significant main

effects or interactions, all ps [ .05. In general, judges achieved an overall mean accuracy

of 54.82%, which was not significantly above chance, t(27) = 1.93, p = .06. Judges

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performed above the level of chance in detecting deception in happiness, t(27) = 2.56,

p \ .05, whereas their accuracy in judging the veracity of sad, disgust and fearful

expressions did not differ from chance (ps [ .05).

Discussion

The widespread notion that the human face and its expressions can betray covert emotional

states originates in the inhibition hypothesis (Ekman et al. 1988, 1991). Darwin (1872)

postulated that powerful emotions in particular could not be completely inhibited nor

fabricated because of the involuntary nature of emotional expressions. A century later,

Haggard and Isaacs (1966) and then Ekman and colleagues (e.g., Ekman 1985/2001;

Ekman 2006; Frank and Ekman 1997) argued that extremely brief ‘‘flashes’’ of an indi-

vidual’s true emotion appear on the face uncontrollably as ‘‘micro-expressions.’’ If con-

firmed, these hypotheses potentially offer critical insights into the nature of human

communication.

The present study was a comprehensive investigation relating to these ideas. It also was

one of the most thorough studies of human facial expressions yet conducted, with a

database of 1,711 expressions comprising a manual analysis of 256,650 video frames of

facial behavior and four of the universal emotions. Results were consistent with the

proposition that facial communication is not always under conscious control in that

emotional leakage was essentially ubiquitous, occurring in 98.3% of participants at least

once. Most importantly, the findings strongly supported the inhibition hypothesis; high

intensity deceptive emotions were associated with substantially more emotional leakage

than low intensity deceptive emotions. High intensity emotion was more difficult to

conceal than low intensity emotion during emotional masking (replacing a felt emotion

with another, false emotional expression), and leakage was especially likely to manifest in

the muscles of the upper face (see also Rinn 1984). As in Porter and ten Brinke (2008), it

was more difficult for participants to mask an emotion than to neutralize one (maintain a

neutral face in the presence of felt emotion). However, there were trends toward more and

longer inconsistencies in high intensity neutralization relative to low intensity neutral-

ization, consistent with the inhibition hypothesis. On the other hand, some leakage did

occur in low intensity deceptive emotions, suggesting the possibility that leakage may

occur on a continuum of emotional intensity as opposed to being an ‘‘all or none’’ phe-

nomenon (as we predicted), occurring only in falsified emotions of a particular high

intensity. Future research could clarify this issue by using a greater number of levels of

emotional intensity and establish the intensity threshold required for leakage to occur.

Inconsistencies were more likely to occur during particular emotions relative to others.

Specifically, in both the upper and lower face, inconsistencies were most likely to occur in

fearful expressions and least likely to occur during expressions of happiness, which may

relate to level of experience; Somerville and Whalen (2006) found that happiness is the

most commonly experienced expression whereas fearful expressions are exhibited the

least. Further, the impact of emotional intensity on the likelihood that one’s emotional

deception would be revealed by leakage of emotional inconsistencies varied by emotion.

Considering high intensity emotion specifically, masking resulted in a greater likelihood of

inconsistent emotion for expressions of happiness and sadness, but did not lead to greater

emotional leakage during masks of fear or disgust. The data suggest that one reason for this

is a ‘‘ceiling’’ effect such that fear and disgust were associated with a high level of leakage

for both low and high intensity emotions.

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This support for the inhibition hypothesis, specifically in the upper face, during falsi-

fication of happiness may reflect the incomplete fabrication of deceptive, negative emo-

tions, and the leakage of genuine, positive emotion in falsified emotion (and vice versa for

the falsification of sadness). As in a recent study of falsified remorse (ten Brinke et al.

2011), this finding may be due specifically to the uncontrollability of the medial portion of

the frontalis muscles. Whereas most people can easily raise the eyebrows (frontalis muscle,

Action Units 1 & 2; Ekman et al. 2002), it is difficult for most people to engage only the

medial portion of the frontalis muscle (Action Unit 1; Ekman et al. 2002) spontaneously,

which brings the inner eyebrows upward to mimic the upper face activation associated with

a genuine sad face (Ekman 2003b). Thus, the deceiver activates the complete (inner and

outer) frontalis muscle, appearing surprised and leaking inconsistent emotion during fal-

sified sadness. Alternatively, while genuinely experiencing sadness, the deceiver may not

be able to suppress medial frontalis action, leading to leakage of a raised brow during a

falsified display of happiness.

The notion of the 1/25th–1/5th of a second full-face micro-expression long advocated

by Ekman was not supported here. No complete micro-expressions involving both the

upper and lower halves of the face simultaneously (as described by Ekman and Friesen

1975) were detected in any of the 1,711 analyzed expressions, suggesting that they may not

exist or that they are exceedingly rare. However, there were rare occurrences of ‘‘partial’’

fleeting micro-expressions manifesting in either the upper or lower face. Fifteen (25.4%)

participants exhibited 18 partial micro-expressions: ten in the upper and eight in the lower

facial region. From an applied perspective, this offers good and bad news. The good news

is that most instances of emotional leakage lasted longer than 1/5th of a second, and

frequently lasted for closer to a full second. This means that ‘‘subtle’’ deceptive expres-

sions occur frequently (especially in high intensity emotional displays) and should be

relatively perceptible to the trained eye. On the other hand, both Ekman (1985/2001)

micro-expressions and (the far more common) longer-lasting emotional leakage we

observed typically are manifested in one region of the face (the latter more common in the

upper face) making them more ‘‘subtle’’ than traditionally believed. Clearly, relative to the

traditional view of micro-expressions, a better way to conceptualize involuntary facial

communication is as subtle emotional leakage lasting long enough for the trained eye to

detect and more often occurring in the upper face and for high intensity emotions. Related

‘‘real-life’’ findings were recently generated in study of extremely high-stakes emotional

deception (ten Brinke and Porter 2011); deceptive individuals (killers) ‘‘pleading’’ for the

return of a missing relative (versus sincere pleaders) exhibited similar patterns of emo-

tional leakage in their facial expressions.

Despite the perceptible leakage that appeared on deceptive emotional faces, observers

generally were unable to discriminate sincere and insincere emotions, performing at the

level of chance for all negative emotions and only slightly above chance for happiness

expressions (see also Ekman et al. 1988). Although objectively there was more leakage in

high intensity expressions, observers did no better at identifying high intensity versus low

intensity emotional deception. It should be noted that when producing the expressions,

participants were asked to look at the screen. Thus, it is possible that observers had

difficultly detecting deceptive expressions because all participants were looking away from

them (e.g., Adams and Kleck 2003). However, the findings are consistent with the general

findings on deception detection (see Vrij et al. 2011) and are similar to the findings of Hess

and Kleck (1994) and Porter and ten Brinke (2008) relating to emotional deception.

Generally, these findings suggest that if observers are not sophisticated in evaluating

emotional facial expression, the increased likelihood and duration of diagnostic emotional

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leakage are of little assistance to naı̈ve judges. However, research does suggest that short

training programs that focus on emotional cues to deceit can drastically improve the

detection of high-stakes, high-intensity emotional deception from the level of chance to

80% accuracy (Shaw et al. 2011).

This exciting scientific area promises to provide greater illumination of a topic pio-

neered by Duchenne, Darwin, and Ekman: that of human facial communication and the

universal emotions. Arguably, many aspects of human facial communication are uncharted

scientific territory, despite long-standing ideas and assumptions about the involuntary

nature of face communication. Research such as the current study is firmly establishing that

the human face can reveal the presence of a contradictory underlying emotion, particularly

when the deceiver is experiencing a powerful emotional state at odds with the expressed

emotion. Ultimately, this knowledge could improve the identification of emotional

deception in legal and security environments where such assessments carry enormous

consequences.

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