2012. Vol.3, No.1, 82-89
Published Online January 2012 in SciRes (http://www.SciRP.org/journal/psych) http://dx.doi.org/10.4236/psych.2012.31014
Copyright © 2012 SciRes.
Three Patterns of Motion Which Change the Perception
of Emotional Faces
Alhadi Chafi1,2, Loris Schiaratura1,2, Stépha n e Rusine k1,2
1Université de Lille-Nord de France UDL3, Villeneuve d’Ascq, France
2Laboratoire PSITEC, Villeneuve d’Ascq, France
Received October 1st, 2011; revised November 5th, 2011; accepted December 7th, 2011
The aim of the study was to focus on the relationship between motion and emotion. Relying on studies in
Behavioral Neurology and Social Psychology, it is believed motion is one of the core components of
Emotion. The study uses basic emotional faces (i.e., Happy, Surprised, Fearful, Sad, Disgusted and Angry)
which are presented displaying patterns of motion (i.e., a Parabolic motion, a Translational motion and a
Wave-like motion). Hypotheses are that the wave-like motion will increase perceived intensities and arou-
sal related to positive emotional faces (i.e., Happy and Surprised), and simplify their recognition. Other-
wise, the parabolic motion is hypothesized to increase perceived intensities and arousal related to negative
emotional faces (i.e., Angry, Disgusted, Fearful and Sad), while enhancing their recognition. Results sho-
wed that “Happy” is the most recognized face and “Fearful” is the least recognized one. Concerning Per-
ceived Intensity, an Emotional Face main effect and an Interaction Motion Pattern × Emotional Face were
obtained. Finally, the Arousal dimension yielded two main effects, one for the Emotional Face and one
for the Motion Pattern. On one hand, results we found are very promising in understanding the part played
by motion in Arousal. On the other hand, further research still has to be done so as to question the exact
effects of the Translational, Parabolic and Wave-like motion patterns, especially in more dynamic con-
Keywords: Emotional Face; Motion Pattern; Self-Reports; KDEF
The relationship between motion and emotions has always
been a matter of investigation in the way that motion, per se, is
believed to involve emotional experience. For instance, some
authors demonstrated that certain patterns of motion have more
emotional potential than others (Rimé, Boulanger, Laubin, Ri-
chir & Stroobants, 1985; Rimé & Schiaratura, 1991). A similar
range of studies showed that very simple patterns of motion
from an object involve animation and emotional attributions
(e.g., Heider & Simmel, 1944). Henceforth, the aim of the pre-
sent study is to show that three specific patterns of motion from
a disk, in which was inlaid a facial expression, will have an
effect on the recognition of this latter and on the perceived
intensity and arousal related to that emotional face. Indeed,
theories of the embodied cognition (e.g., Barsalou, 1999) gave
rise to findings which clearly show congruency effects between
certain types of executed actions, or even simulated actions,
and experienced emotional dynamics. These congruency effects
could be illustrated as following: an approach movement (e.g.,
pulling a lever) was faster when positive feelings were ex-
perienced whereas an avoidance movement (e.g., pushing a le-
ver) was faster when negative feelings were experienced (Ale-
xopoulos & Ric, 2007; Brouillet, Heurley, Martin, & Brouillet,
2010). Similarly, Freina, Baroni, Borghi, and Nicoletti (2009)
showed that participants were faster in reaching an away button
when reading positive words whereas they were faster in pull-
ing their hand back to their body when reading negative words.
At a perceptual level, Podevin (2009) demonstrated that three
motion patterns were linked to emotions, namely, the Tran-
slational, Parabolic and Wave-like motion patterns. For instan-
ce, Rusinek (2009) used the Wave-like motion in order to de-
sensitize an arachnophobia in a sub-clinical population. Partici-
pants of this experiment c ould bring towards them a false spider
closer than the other sub-clinically arachnophobics who were
not exposed to the Wave-like motion/picture of a spider asso-
ciation. According to Podevin (2009), the Parabolic motion en-
hanced memory for negative words whilst the Wave-like mo-
tion enhanced memory for positive words. Tremoulet and Feld-
man (2000) showed that the perception of a parabolic motion
from an object (i.e., a circle or a cylinder) gave rise to anima-
tion attribution to the object in an adults sample. Finally, the
Translational motion is evaluated by a sample of adults and chi-
ldren as neutral or weakly positive (Podevin, 2009). The positi-
ve triggering tendency of an horizontal translational stimulus
was also supported by studies of Phaf and Rotteveel (2009).
These authors showed that a left-to-right arrow gave rise to
faster approach movements and more positive evaluations than
a right-to-left arrow in Dutch left-to-right readers. Yet, as the
presented arrow was static, it is assumed that it did not have the
same effects as the Translational motion, which was asse ssed a s
neutral. Therefore, the investigation consisted in answering how
these three specific patterns of motion from a single object will
have an effect on the recognition of still emotional faces de-
picting the six basic emotions and on their related emotional
assessments. Hypothesis is that the Wave-like motion will be
related to positive emotional faces whereas the Parabolic mo-
tion will be related to negative emotional faces. Concerning the
A. CHAFI ET AL.
Translational motion, it will have a medium effect on both ty-
pes of emotional faces.
Facial expressions of emotion have long been studied in Psy-
chology and Neuroscience fields (Ekman & Friesen, 1976; Ek-
man, 1993; Ekman, 1999 Adolphs, 2002), but most research in
the domain are interested in still images (Calvo & Lundqvist,
2008; Goeleven, De Raedt, Leyman, & Verschuere, 2008). Fur-
thermore, Batty and Taylor (2003) showed that the processing
of emotional faces is automatic and rapid for the six basic emo-
tions (i.e., sadness, fear, disgust, anger, surprise and happiness).
Ambadar, Schooler and Cohn (2005) showed that motion in a
face, for the six above-mentioned emotional expressions, was
the most important feature to be able to decipher the expressed
emotion. Thus, it is thought to be important to study the six ba-
sic emotional expressions along with the three patterns of mo-
tion which are believed to be linked to emotions.
There are two kinds of approaches in the Motion Research: 1)
biological motion field, which refers to the identification and
recognition of a biologically possible motion, often done by a
real being (i.e., the flexion/extension of an arm, etc.); or 2) non-
biological motion field, which does not refer to any living being
and does not need to be biologically possible (i.e., the bouncing
of a ball, etc.). Many research have shown a link between mo-
tion and emotion, whether this motion is biological (Johansson,
1973; Blake & Shiffrar, 2007) or non-biological (Heider & Si-
mmel, 1944; Michotte, 1946/1962).
Biological Motion Research
Johansson (1973) has been the first author in this field of in-
terest. In fact, he placed dots on the joints of human bodies who
were filmed in the darkness. He then exposed his participants to
the moving dots only, in order to prevent his participants to
recognize a human structurally, and he showed that participants
are still able to recognize a running, dancing or walking indivi-
dual. That study was the starting point of a long tradition in the
Motion Research. For instance, Cutting and Kozlowski (1977)
showed that the perception of moving dots is sufficient to iden-
tify friends. Troje, Westhoff, and Lavrov (2005) showed that
deprivation of structural information, such as size or shape,
does not have an effect on the identification and recognition of
individuals as participants essentially rely on the kinetics of in-
dividuals’ walk. In addition, Troje and Westhoff (2006) showed
a kind of inversion effect related to the very specific position of
feet in terrestrial animals. These authors also postulated the
existence of a “Life Detector” in the visual brain sy stem of the
evoked animals. This latter hypothesis is also supported by wo-
rks of Méary, Kitromilides, Mazens, Graff and Gentaz (2007)
who showed that 4-days-old human infants looked longer at
non-biological motion compared to biological motion. That fin-
ding suggests that infants motion perception was already attu-
ned to biological kinematics.
Thereby, everything coming from the Biological Motion Re-
search seems to suggest that motion is at least as, if not more,
important as still features of an individual for its recognition
and identification. It is now possible to wonder about the non-
Non-Biological Motion Research
The ranges of interests of Psychologists had first highlighted
non-biological motion rather than motion from individuals or
animals. For example, Michotte (1946/1962) studied what he
called “phenomenal causality”, which can be defined as the fact
that participants evoked interactions between the moving ob-
jects, even though they knew that these objects were inanimate.
Heider and Simmel (1944) found that depending on the random
motion patterns of different objects (e.g., a triangle, a circle,
etc.), participants attributed different intentions, attitudes and
emotions to the moving objects (i.e., anthropomorphism). This
anthropomorphism can be defined as the fact of giving human-
like emotional and behavioral properties to the moving objects,
with the description of their patterns of motion as a base to
assess these attributes. Rimé, Boulanger, Laubin, Richir and
Stroobants (1985) showed that an intercultural consensus be-
tween Belgians, Americans and Zairians existed for 3 out of 5
kinetic structures. In that study, it was clear that it was not the
shapes of the presented objects that were important in the in-
volvement of emotional perception but it was rather the kinetic
structure of motion. In a latter research, Tremoulet and Feld-
man (2000) showed that a parabolic motion from a white single
object (i.e., a cylinder or a circle) on a dark background can
give rise to a perception of animation. That perception is in-
duced by combined changes of speed and direction, and again,
that result had been found by Michotte fifty years before. Ne-
vertheless, the groundbreaking point of Tremoulet and Feldman
dwells in the use of a specific pattern of motion, namely, the
parabolic motion. Here, it is noteworthy to refer to Casasanto
and Dijkstra (2010) who defined three dimensions related to
emotions: verticality, horizontality and flexion/extension. Con-
cerning the first dimension, it seems that up movements of the
arm favour positive statements whereas down movements fa-
vour negative statements. Concerning the horizontality dimen-
sion, Phaf and Rotteveel (2009) showed that Dutch left-to-right
readers evaluated more easily an arrow in the reading direction
(i.e., from left-to-right) than an arrow in the opposite direction
(i.e., from right-to-left). Moreover, they experienced positive
emotions when exposed to the left-to-right arrow whether the
evaluation task was explicit (i.e., a self-report scale) or implicit
(i.e., arm flexion vs. arm extension). Also, Alexopoulos and Ric
(2007), based on Chen and Bargh (1999), showed that the fle-
xion of an arm is faster when exposed to happy words whilst
the extension of an arm is faster when exposed to sad words.
All these findings showing concruency effects between a di-
mension and emotional processes could be explained in terms
of the affective monitoring hypothesis (Phaf & Rotteveel, 2009).
According to this assumption, certain perceptual features would
guide our emotional system towards corresponding affective
processes, namely: 1) Verticality: an “up” stimulus would be
related to positivity whereas a “down” stimulus is believed to
be related to negativity; 2) Horizontality: a left-to-right stimulus
would be seen as more positive than a right-to-left stimulus in a
left-to-right reader; and 3) Flexion/Extension: the flexion of an
arm is faster during the presentation of a positive stimulus whi-
lst the extension of an arm is faster during the exposure to a ne-
gative stimulus. The same type of congruency effects were
found for motion perception by Podevin (2009) and Rusinek
(2009) as above-mentioned. Effectively, these authors showed
that a wave-like motion is linked to positive emotions whilst a
parabolic motion is linked to negative ones. They also postulate
that a translational motion is related to a neutral valence. The-
refore, it is noteworthy to discuss the occurrence and type of
such a congruence in the relationship between motion and emo-
Copyright © 2012 SciRes. 83
A. CHAFI ET AL.
The Motion-Emotion Congruence: Evidence from
3 Patterns of Motion
Recently, Podevin (2009) investigated the effect of a motion
from a dark circle on a white background on the affective state
of both adults and children. According to Podevin, there is a
link which readily seems to follow a “congruence system” for
three specific patterns of motion (see Figure 1). Thus, Podevin
showed that a parabolic motion pattern was mainly assessed as
emotionally negative while a wave-like motion pattern was
strongly evaluated as positive. Furthermore, individuals attribu-
ted a neutral valence to a translational motion pattern. At a
cognitive level, the Parabolic motion enhanced memory for ne-
gative words whereas the Wave-like motion ameliorated me-
mory for positive words in an adults sample (Podevin, 2009).
Another groundbreaking finding was that the Parabolic motion
induced a deceleration in a writing-speed task, what is marked
by a negative emotional dynamics (Natale & Hantas, 1982).
These associations, namely Wave-like/positive emotions, Parabo-
lic/negative emotions, Translational/neutral condition were rep-
licated in children aged from 9 to 12 years old, both at a
perceptual and cognitive levels (Podevin, 2009). Therefore, not
only the emotional perception is affected by the motion patterns
displayed according to participants’ evaluations, but this rela-
tionship has an impact on cognitive ressources (i.e., the memo-
ry of emotional words) and operations (i.e., a writing-speed
task). In line with this congruence hypothesis, Rusinek (2009)
used the Wave-like motion in an arachnophobia desensitization
on a sub-clinical sample. That latter study empowers the assu-
mption that the Wave-like motion is linked to positive emo-
In the present study, congruency effects between patterns of
motion and recognition and perceived intensity of emotional
faces are expected. It is assumed that the Parabolic motion will
increase the recognition and perceived intensity of negative
faces (i.e., Sad, Fearful, Disgusted, and Angry) while the Wa-
ve-like motion will increase the recognition and perceived in-
tensity of positive faces (i.e., Happy and Surprised) compared
to the Translational motion.
For the arousal dimension, no specific hypothesis was postu-
lated as this measure for the above-mentioned patterns of mo-
tion has never been done before.
Sixty-one French students (48 women and 13 men) from the
University of Lille North of France UDL3 were randomly re-
cruited with the only criterion of having a normal or corrected-
to-normal vision. All of them are right-handed people and na-
tive French speakers.
Material and Ap paratus
According to Goeleven, De Raedt, Leyman and Verschuere
(2008), the Facial Action Coding System (FACS; Ekman &
Friesen, 1976) is nowadays old-fashioned and limits ecological
validity. Other sets of stimuli that could be possibly used to
question our hypotheses are: the Japanese and Caucasian Facial
Expressions of Emotion (JACFEE; Matsumoto & Ekman, 1988)
and the Montreal Set of Facial Displays of Emotion (MSFDE;
Beaupré, Cheung, & Hess, 2000). Yet, the weak number of pic-
tures these sets contain still remains a substantial limitation.
Therefore, Goeleven et al. (2008) measured the emotion, per-
ceived intensity, and arousal ratings for 490 frontal pictures
from the Karolinska Directed Emotional Faces (KDEF; Lundq-
vist, Flykt, & Öhman, 1998). Arousal is one of the most rele-
vant components of emotion as it directly impacts on motive-
tional dimension (Lang, Greenwald, Bradley, & Hamm, 1993).
The study of Goeleven et al. both confirms the validity of the
KDEF and offers many interesting results. Effectively, it ap-
pears that “Happy” is the best recognized emotional face while
“Fearful” is the least recognized one. Concerning the intensity
dimension, “Disgusted”, “Happy”, and “Surprised” are the most
intense emotional expressions. The arousal dimension shows no
differences between emotional categories, but there are discre-
pancies between emotional faces and neutral faces. Although
this research is in line with previous emotion studies (Gross &
Levenson, 1995), it has the limitation of only including female
participants. Nevertheless, the procedure they used so as to
assess emotions of the participants via self-reports is the same
as we are using here.
In the present study, faces were chosen on the criteria of re-
cognition, perceived intensity of emotion and arousal ratings.
Thus, participants were exposed to strongly recognizable faces
involving high ratings of perceived intensity and arousal, all of
which reflecting a high emotional experience. Hereby, six facial
expressions of emotions (i.e., Happy, Fearful, Angry, Surprised,
Sad and Disgusted) were retained among these validated by
Goeleven et al. (2008). The “gender of actor” factor was con-
trolled by only showing male emotional faces (see Figure 2).
Patterns of Motion
The disk’s size is exactly the same in this study as in the ex-
periments of Podevin (2009) and Rusinek (2009). It precisely
has a diameter of 4.1 centimeters. Effectively, that surface co-
vers a large enough space so that a face is seen without dis-
turbing the participants. Background is white and the emotional
face is encrusted in the disk.
Concerning trajectories, the Translational motion does not
seem to disrupt cognitive resources of an individual and a sche-
matic facial expression of smile is associated to that motion by
20% of children. The Parabolic trajectory would be able to in-
crease cognitive resources directed towards negative emotional
(a) (b) (c)
Patterns of Motion: (a) Parabolic, (b) Wave-like, (c) Translational.
Pictures of “Disgusted” (left) and “Angry” (right) emotional
faces as they were presented.
Copyright © 2012 SciRes.
A. CHAFI ET AL.
stimuli. Finally, the trajectory of the Wave-like motion gather-
ing spring, pendulum and translation is associated to positive
emotional processes and a smile is linked to that motion by
60% of children (see Podevin, 2009 for a review).
Motion patterns lasted 5 seconds for any trajectory. There-
fore, we showed 18 associations (3 Motion Patterns × 6 Emo-
tional Faces) to each participant. Orders of the associations we-
re counterbalanced (3 orders at last) so that we eliminated the
In order to assess self-reported emotions, every participant
was given a brochure composed of one forced-choice question
for the emotion recognition task and two items before watching
the whole presentation. The two items are respectively: an In-
tensity item taken from the Intensity of Emotion Scale (IES;
Schaefer, Sanchez, Nils, & Philippot, 2010) and an Arousal
item taken from the Self-Assessment Manikin (SAM; Lang,
1980). The brochure is made of 19 pages (including a cover pa-
ge with a short instruction) as participants were shown 18 slides.
Thus, each slide was rated on the recognition question and the
For the emotion recognition task, participants were asked to
surround the word that matches the expressed emotion. Pro-
posals were each of the six basic emotions to which we added
“Neutral” and “?” (Indistinct). Concerning the IES (ranging
from 1 = “not intense at all” to 9 = “completely intense”), par-
ticipants were asked to surround the number on the scale that
best represents the intensity of the emotion they chose in the
recognition task. Finally, the SAM (ranging from 1 = “calm” to
9 = “excited”) consists in graphic depictions of various stages
of arousal, and the participants had to answer the question
“What did you feel when viewing the face? Match the graphic
that corresponds to your state. At one extremity of the scale,
you are excited, awaken, stimulated; at the other extremity, you
are relaxed, unstimul ated, ca lm”.
Each participant came individually in a box of the PSITEC
Lab, located in the Department of Psychology. The experi-
menter made recruitment by asking students if they had about
10 minutes to assess emotional faces. Following the entering of
the box, instructions could be said:
“You are to assess emotional faces via a brochure. Each page
of that brochure corresponds to one face. You will plainly fol-
low the instructions on the screen and in the brochure when en-
gaged in the task. First, we are going to make a bit of relaxation”.
After ensuring that the participant is ready for the relaxation
phase, the experimenter asked the participant to close his eyes,
to relax every muscular group, including his face, and to deeply
and regularly breathe. Then, he asked individuals to perform
arm and leg flexions while still deeply breathing. Relaxation
lasted about 2.5 minutes. When the relaxing sequence was fini-
shed, the participant was informed that he could begin by
pressing any key. Experimenter then asked him to follow care-
fully instructions given on the screen. Displays were seen on a
17’’ inches screen and were created via Microsoft PowerPoint
97-2003. Each participant saw every type of emotional face wi-
th every type of motion pattern (i.e., 18 emotional displays).
Between every emotional display, a transition slide instructed
the participant to fill in the corresponding page and then press
any key to see the next display. This brochure consisted in
“paper-pen” tests, so pens were available to participants. Fina-
lly, a dehoaxing step was made in the following manner:
“As you could have noticed, you saw many times the same
emotional faces. In fact, these faces were associated to different
motion patterns. The patterns of motion you saw are believed to
be differently associated to emotions, according to recent stu-
dies in that field.”
A 3 (Motion Pattern) × 6 (Emotional Face) ANOVA was
performed using within-subjects designs for each dependent
variable, namely, the Arousal, the Recognition and the Percei-
The analysis revealed a main effect of Motion Pattern, F (2,
120) = 5.24; p < .01, indicating that the Wave-like motion (M =
3.33, SD = 1.91) was significantly more arousing than the
Translational (M = 3.14, SD = 1.76) and Parabolic (M = 3.10,
SD = 1.80) motion patterns.
Concerning the Emotional Face factor, another main effect
was found, F (5, 300) = 3.15; p < .01. This effect indicated that
“Sad” (M = 2.81, SD = 1.55) was significantly less arousing
than “Disgusted” (M = 3.38, SD = 1.80), “Happy” (M = 3.37,
SD = 2.05), “Angry” (M = 3.28, SD = 1.91), and “Fearful” (M =
3.23, SD = 1.82).
Even though the Motion Pattern × Emotional Face interact-
tion was not significant, F (10, 600) = .97; p = .46, our a priori
hypotheses permitted us to look into Post-hoc tests. These
comparisons showed us that the “Happy” face displaying the
Wave-like motion (M = 3.71; SD = 2.11) was more arousing
than when associated with the Parabolic motion (M = 3.21; SD
= 1.95), p < .02, or the Translational motion (M = 3.20; SD =
2.09), p < .02. Another finding was that the “Sad” face was
more arousing when associated with the Translational motion
(M = 2.97; SD = 1.67) than when associated with the Parabolic
motion (M = 2.53; SD = 1.47), p < .04.
Therefore, it seems that Self-Assessed Arousal was modula-
ted by Motion Patterns for “Happy” and “Sad” faces only. Ana-
lysis demonstrate that “Happy” face was affected by the most
arousing motion (i.e., the Wave-like motion) whereas “Sad”
face was affected by the least arousing one (i.e., the Parabolic
motion). These results are congruent regarding the main effects
of Emot ional Face and of Mo tion Pattern ta ken together. Rec o-
gnition and perceived intensities of emotional faces could help
explaining th ese findings. (see Table 1)
The analysis revealed a main effect of Emotional Face, F (5,
300) = 22.30, p < .0001. Table 2 shows the average frequencies
means and standard deviations for each emotional face. The
Emotional Face effect indicated that “Happy” (M = .98; SD
= .15) was more recognized than any other face except the
“Disgusted” one (M = .90; SD = .29), which was itself more
recognized than “Sad” (M = .76; SD = .44) and “Fearful” (M
= .51; SD = .50). The very same results as those for “Disgu-
sted” were obtained for “Surprised” (M = .88; SD = .33). “Fear-
ful” and “Sad” were found to be, respectively, the least and se-
cond-least recognized Emotional Faces.
Copyright © 2012 SciRes. 85
A. CHAFI ET AL.
Copyright © 2012 SciRes.
The main effect of Motion Pattern was not significant, F (2,
120) = 2.27, p = .11. However, further tests showed that the
Parabolic motion (M = .82; SD=.34) induced more Recognition
than the Wave-like motion (M = .79; SD = .36).
Even though the Motion Pattern × Emotional Face interact-
tion was not significant, F (10, 600) = 1.51, p = .13, further
tests showed that the recognition of “Disgusted” was impaired
when displaying the Wave-like motion (M = .82; SD = .39)
compared to displaying the Translational one (M = .95; SD
= .22), p < .01. Another finding that got along with our hypo-
theses was that “Fearful” was more recognized when displaying
the Parabolic motion (M = .57; SD = .50) than when displaying
the Wave-like motion (M = .46; SD = .50), p < .05. Both results
emphasized the expected positive effects of the Wave-like mo-
tion by diminishing the recognition of negative emotional faces.
Hence, we can infer that the Wave-like motion impaired the
processing of negative faces. (see Table 2).
The analysis revealed a significant main effect of Emotional
Face, F (5, 300) = 33.65; p < .0001. It indicated that “Sur-
prised” (M = 6.33; SD = 1.55), “Happy” (M = 6.72; SD = 1.50)
and “Disgusted” (M = 6.88; SD = 1.59) did not differ from one
another. Besides, “Angry” (M = 5.69; SD = 1.59) was perceived
as less intense than “Happy”, p < .01, and “Disgusted”, p < .001,
but as more intense than “Sad”, p < .01. In fact, the “Sad” ex-
pression differed from all other emotional faces, making it the
least intensely perceived (M = 4.72; SD = 1.67). The second
least intensely perceived emotional face was “Fearful” (M =
5.42; SD = 1.74), though its score still was higher than “Sad”, p
< .05, and did not significantly differ from “Angry”.
No main effect for the Motion Pattern factor was found.
Nevertheless, the Motion Pattern × Emotional Face interact-
tion was significant, F (10, 600) = 3.45; p < .001 (see Table 3).
Post-hoc tests indicated that “Surprised” was perceived as
more intense when displaying the Wave-like motion than when
displaying the Translational one, p < .01, or the Parabolic one,
p < .01. The “Sad” expression was evaluated as more intense
when displaying the Parabolic motion than when displaying the
Translational motion, p < .01. The expected difference between
the Wave-like and Para bolic motion were obtained for “Happy”
and “Angry”, respectively, the Wave-like motion increased the
perceived intensity of the “Happy” face, p < .05, and decreased
the perceived intensity of the “Angry” face, p < .05.
Arousal means and standard deviations for the Motion Pattern × Emotional Face interaction .
Motion Surprised Angry Happy Sad Disgusted Fearful
Translation 2.92 (1.75) 3.25 (1.82) 3.20 (2.09) 2.97 (1.66) 3.36 (1 .59) 3.16 (1.67)
Parabol 3.03 (1.74) 3.23 (1.94) 3.21 (1.95) 2.53 (1.46) 3.31 (1. 93) 3.29 (1.81)
Wave 3.31 (2.04) 3.36 (1.96) 3.71 (2.11) 2.92 (1.52) 3.46 (1 .88) 3.25 (1.98)
Recognition means and standard deviations for the Motion Pattern × Emotional Face interaction.
Motion Surprised Angry Happy Sad Disgusted Fearful
Translation .88 (.32) .90 (.30) .98 (.13) .70 (.46) .95 (.22) .49 (.50)
Parabol .85 (.36) .84 (.37) .98 (.13) .79 (.41) .92 (.28) .57 (.50)
Wave .90 (.30) .85 (.36) .97 (.18) .74 (.44) .82 (.39) .46 (.50)
Perceived Intensity means and standard deviations for the Motion Pattern × Emotional Face interaction.
Motion Surprised Angry Happy Sad Disgusted Fearful
Translation 6.15 (1.60) 5.72 (1.54) 6.77 (1.48) 4.39 (1.69) 7.02 (1 .57) 5.52 (1.70)
Parabol 6.13 (1.62) 5.93 (1.60) 6.46 (1.60) 5.06 (1.51) 6.73 (1. 58) 5.25 (1.97)
Wave 6.70 (1.43) 5.42 (1.62) 6.93 (1.42) 4.72 (1.81) 6.88 (1 .61) 5.49 (1.56)
A. CHAFI ET AL.
The same results were obtained when performing simple ef-
fects for each Emotional Face taken alone in the Emotional
Face × Motion Pattern interaction. Motion patterns affected the
perceived intensity for three types of emotional faces: “Sur-
prised”, F (2, 120) = 5.64; p < .01, “Happy”, F (2, 120) = 4.28;
p < .02, and “Sad”, F (2, 120) = 5.84; p < .01. The Wave-like
motion increased the perceived intensity of the “Surprised”
emotional face compared to the Translational motion and the
Parabolic one. In line with the previous result, the Wave-like
motion also increased the perceived intensity of the “Happy”
face unlike the Translational and the Parabolic motion. Results
highlighted that the Parabolic motion increased the perceived
intensity of the “Sad” emotional face contrary to the Wave-like
and the Translational motion. Besides, it seems substantial to
note that other simple effects revealed a tendency for “Angry”,
F (2, 120) = 2.71; p = .07. This tendency showed a similar find-
ing to the one concerning the “Sad” expression, namely, the
Parabolic motion tended to increase the perceived intensity of
the “Angry” face compared to the Translational and the Wave-
like motion. Again, the positive effects from the exposure to the
Wave-like motion and the negative effects from the exposure to
the Parabolic motion were emphasized by our results concern-
ing the perceived intensities of the emotional faces (see Figure
From that standpoint, we can say that Perceived Intensities
confirmed the positive effects of the Wave-like motion and the
negative effects of the Parabolic motion. Thus, the Wave-like
motion increased the intensities of the “Surprised” and “Happy”
emotional faces whilst the Parabolic motion rather increased
intensities for negative emotional faces, namely, the “Sad” and
“Angry” expressions. Further explanations will be given in the
The experiment’s findings partly confirm the hypotheses
concerning the effects of the Wave-like, Parabolic and Transla-
tional motion patterns. Indeed, these specific patterns of motion
were thought to change the perception of emotional stimuli.
Thus, the Wave-like motion, which is believed to be linked to
positive emotions (Podevin, 2009; Rusinek, 2009), plays here
an important role in the high perceived intensities of positive
faces (i.e., “Surprised” and “Happy”) according to the Motion
Pattern × Emotional Face Interaction. This interaction also lea-
ds us to state that the Parabolic motion increases perceived
intensities of “Sad” emotional face. The Translational motion
seems to be related to the “Disgusted” and “Fearful” emotional
faces if we take a look at the perceived intensities of these fa-
cial expressions. Nevertheless, these findings were non-signifi-
cant both for the “Disgusted” and “Fearful” conditions. More-
over, the Translational motion was less negative than the Para-
bolic motion and less positive than the Wave-like motion for
other emotional faces. This latter result is in line with theoretic-
cal assumptions. Another odd finding concerns the high per-
ceived intensities for “Fearful”, “Disgusted”, and “Sad” faces
when displayed with the Wave-like motion, yet believed to be
linked to positive faces only. In fact, the only significant and
relatively high perceived intensity of that motion with a nega-
tive face was found for the Wave-like/“Sad” association. In fact,
the Parabolic motion increased more the perceived intensity of
the “Sad” face compared to the Wave-like motion. These find-
ings confirm the relationship between positive emotions and
Wave-like motion observed by Podevin (2009), but in the mean
time, present findings do clearly demonstrate the relationship
between negative emotions and Parabolic motion. If Podevin
(2009) showed a relationship between emotional words and the
three motion patterns, namely, a relation between a visual per-
ception and the verbal domain, results from the present study
show that this bond between emotion and motion go far beyond,
as emotional faces are non-verbal stimuli. Concerning results
such as the high perceived intensity of the “Sad” face display-
ing the Wave-like motion, an explanation holds in the counter-
regulation principle (Rothermund, 2003; Rothermund, Voss &
Wentura, 2008; Wentura, Voss, & Rothermund, 2009). The coun-
ter-regulation hypothesis consists in the automatic attention shi-
ft towards information that is incongruent with an individual’s
current emotional dynamics. That principle would therefore
permit the individual to be flexible and adaptable to its envi-
ronment while preventing him from emotional escalation. We
could imagine that when watching a “Sad” face displaying the
Wave-like motion pattern, the individuals paid more attention
to the features of the face and less to the Motion than for any
other Emotional Face. Indeed, the “Sad” expression had a par-
ticular status as it was the least intensely perceived in our ex-
periment. It is noteworthy that we retrieved results from Goele-
ven et al. (2008), namely, independently of the motion pattern
displayed, “Disgusted”, “Happy” and “Surprised” were per-
ceived as the most intense emotional faces.
Perceived Intensity means a nd s ta n d ard deviations for “Surprised”, “Happy” and “Sad” facial expressions.
Copyright © 2012 SciRes. 87
A. CHAFI ET AL.
In addition, the Motion Pattern × Emotional Face interaction
results reinforce the idea that the Wave-like motion should be
positively evaluated whereas the Parabolic motion should be
rather negatively evaluated (Podevin, 2009). That schema of
findings seems to be retrieved for the Arousal dimension. Ef-
fectively, the Wave-like motion was more arousing when asso-
ciated to the “Happy” face than both the Parabolic motion and
the Translational one. That latter is definitely in accordance
with Podevin’s works (2009). In line with present findings con-
cerning the Perceived Intensity, another counter-intuitive result
was found for the “Sad” expression regarding the Arousal di-
mension: the Translational motion increased the self-assessed
Arousal compared to the Parabolic motion for that emotional
face. Again, this would suggest a particular status for the “Sad”
The lack of arousing power combined to the increase of ne-
gative emotions’ perceived intensities for the Parabolic motion
could help explaining his harmful effects on a cognitive task in
Podevin (2009). Likewise, the arousing power of the Wave-like
motion combined to its emotional perceived intensity features
can account for the drawing of smiles to a plain black disk per-
forming that pattern of motion (Podevin, 2009). It is very plau-
sible that high arousal levels associated to the experiment’s task
could be taken as a positive marker. Indeed, the fact that the
task is somewhat interactive should involve participants’ inte-
rest. Therefore, a weak level of arousal could highlight that the
participant showed little interest to the task while a strong level
of arousal could trace the interest of the participant (Simons,
Detenber, Roedema, & Reiss, 1999; Simons, Detenber, Reiss,
& Shults, 2000). By contrast, the exact effects implied by the
Translational motion still has to be questioned. Indeed, Phaf
and Rotteveel (2009) showed that a translational arrow going
from left to right is even more arousing and more positive than
emotional faces. These authors proved the positivity of a left-to-
right arrow in an explicit manner (i.e., subjective self-reports)
and in an implicit manner (i.e., approach vs. avoidance). That
latter gives powerful evidence to the positive involvements of
left-to-right monitoring in left-to-right readers and therefore, we
could have expected the Translational motion to be evaluated
more positively than the Wave-like motion and the Parabolic
motion. In effect, the Translational motion was the only pattern
that was smooth and uninterrupted, while both others were
The “Happy” face occurs to be more recognized than the
“Sad” and “Fearful” expressions, which makes it the most reco-
gnized emotional face in the experiment. This result is in line
with what was shown under an explicit perception condition by
Calvo and Lundqvist (2008). Also, “Fearful” was the least reco-
gnized emotional expression in the study as in their research.
The Wave-like motion impaired the recognition of “Disgusted”
compared to the Translational motion whilst the Parabolic mo-
tion increased the recognition of “Fearful” compared to the Wa-
ve-like motion. Both findings reinforce the assumption that the
Wave-like motion is associated to positive emotional stimuli
whereas the Parabolic motion is associated to negative emo-
In sum, the present study could be seen as a successful atte-
mpt to investigate the three specific patterns of motion which
are somehow linked to emotions, especially discrete emotions.
Thus, Ekman evolved from a vision of emotion that is global
(i.e., positive vs. negative) to a discrete vision of emotion (i.e.,
basic emotions), and the current research used six basic emo-
tional faces in order to stay relevant to this view. Furthermore,
the Arousal has also been investigated as it was believed to be a
substantial component of emotional experiences. Further resea-
rch shall be directed towards a more dynamic prospect (i.e.,
emotional films, emotional scenes) and more ecological envi-
ronment so that one quietly understands the effects of these pat-
terns of motion, especially their parts in the affective monitor-
ing. Effectively, the main limitation of the present study holds
in the lack of ecological validity as one could expect faces to be
moving in their inner properties (e.g., emotional faces videos)
rather than in their whole. Another prospect concerns the use of
motion in cognitive-behavioral therapies such as Rusinek (2009)
suggested it in his trial to desensitize sub-clinical arachnopho-
bia. A final aspect of the motion-emotion link research would
lay in Sports and their many applications. For example, it is
now proved that Taekwondo distinguishes between four types
of motion. Hence, it would be possible to investigate the effects
of the three above-studied motions in martial artists or other
The research reported in this article has been made possible
thanks to the Dr. Gaëlle Podevin and Dr. Céline Douilliez who
provided us most of our material.
Adolphs, R. (2002). Recognizing emotion from facial expressions:
Psychological and neurological mechanisms. Behavioral and Cogni-
tive Neuroscience Review, 1, 21-62.
Alexopulos, T., & Ric, F. (2007). The Evaluation-behavior link: Direct
and beyond valence. Journal of Experimental Social Psychology, 43,
Ambadar, Z., Schooler, J. W., & Cohn, J. F. (2005). Deciphering the
enigmatic face: The importance of facial dynamics in interpreting
subtle facial expressions. Psychological S c i e n c e , 16, 403-410.
Barsalou, L. W. (1999). Perceptual symbol systems. Behavioral and
Brain Sciences, 22, 577-660.
Batty, M. & Taylor, M. J. (2003). Early processing of the six basic
emotional expressions. Cognitive Brain Research, 1 7, 613-620.
Beaupré, M. G., Cheung, N., & Hess, U. (2000). The Montreal set of
facial displays of emotion [Slides]. Montreal, Canada: Department of
Psychology, Univers ity of Quebec.
Berridge, K. C. (2003). Pleasures of the brain. Brain and Cognition, 52,
Blake, R., & Shiffrar, M. (2007). Perception of human motion. Annual
Review of Psychology, 58, 47-74.
Brouillet, T., Heurley, L., Martin, S., & Brouillet, D. (2010). The em-
bodied cognition theory and the motor component of “yes” and “no”
verbal responses. Acta P s yc holog ica, 134, 310-317.
Calvo, M. G., & Lundqvist, D. (2008). Facial expressions of Emotion
(KDEF): Identification under different display-duration conditions.
Behavior Research Methods, 40, 109-115.
Casasanto, D., & Dijkstra, K. (2010). Motor Action and Emotional
Memory. Cognition, 115, 179-185.
Chen, M., & Bargh, J. A. (1999). Consequences of automatic eva-
Copyright © 2012 SciRes.
A. CHAFI ET AL.
luation: Immediate behavioral predispositions to approach or avoid
the stimulus. Personnality and Social Psychology Bulletin, 25, 215-
Creem, S. H., & Proffitt, D. R. (2001). Defining the cortical visual sys-
tems: “What”, “Where” and “How”. Acta Psychologica, 107, 43-68.
Crockford, D. N., Goodyear, B., Edwards, J., Quickfall, J., & el-Gue-
baly, N. (2005). Cue-induced brain activity in pathological gam-
blers. Biological Ps yc hi a tr y, 58, 787-795.
Cutting, J. E., & Kozlowski, L. T. (1977). Recognizing friends by their
walk: Gait perception without familiarity cues. Bulletin of the Psy-
chonomic Society, 9, 353-356.
Detenber, B. H., Simons, R. F., & Bennet, G. C. (1998). Roll’ Em: The
effects of picture motion on emotional responses. Journal of Broad-
casting & Electronic Media, 42, 112-126.
Ekman, P. (1993). Facial expression and emotion. American Psy-
chologist, 48, 384-392. doi:10.1037/0003-066X.48.4.384
Ekman, P. (1999). Facial expressions. In Dalgleish, T., & Power, M.
(Eds.), Handbook of cognition and emotion (pp . 301-32 0). New Yor k:
John Wiley & Sons Ltd.
Ekman, P., & Friesen, W. V. (1976). Measuring facial movement.
Environmental Psychology and Nonverbal Behavior, 1, 56-75.
Ekman, P., Friesen, W. V., & Tomkins, S. S. (1971). Facial affect
scoring technique: A first validity study. Semiotica, 3, 37-58.
Freina, L., Baroni, G., Borghi, A. M., & Nicoletti, R. (2009). Emo-
tive-concept nouns and motor responses: Attraction or repulsion?
Memory & Cognition, 37, 493-499. doi:10.3758/MC.37.4.493
Goeleven, E., DeRaedt, R., Leyman, L., & Verschuere, B. (2008). The
Karolinska directed emotional faces: A validation study. Cognition
and Emotion, 22, 1094-1118. doi:10.1080/02699930701626582
Goodale, M. A., & Milner, A. D. (1992). Separate visual pathways for
perception and action. Tr en ds in N e urosciences, 15, 21-26.
Gross, J. J., & Levenson, R. W. (1995). Emotion elicitation using films.
Cognition and Emotion, 9, 87- 108.
Heider, F., & Simmel, M. (1944). An experimental study of apparent
behavior. American Journal of Psychology, 57, 243-259.
Johansson, G. (1973). Visual perception of biological motion and a
model for its analysis. Perception and Psychophysics, 14, 202-211.
Lang, P. J. (1980). Behavioral treatment and bio-behavioral assessment.
In J. B. Sidowski, J. H. Johnson, & T. A. Williams (Eds.), Technolo-
gy in mental health care delivery systems (pp. 119-167). Norwood,
NY: Ablex. doi:10.1111/j.1469-8986.1993.tb03352.x
Lang, P. J., Greenwald, M. K., Bradley, M. M. & Hamm, A. O. (1993).
Looking at pictures: Affective, facial, visceral and behavioral reac-
tions. Psychophysio logy, 30, 261-273 .
Lundqvist, D., Flykt, A., & Öhman, A. (1998). The karolinska di-
rected emotional face (KDEF). Stockholm: Department of Neuro-
sciences Karolinska Hospital.
Matsumoto, D., & Ekman, P. (1988). Japanese and Caucasion Facial
Expressions of Emotion (JACFEE) [Slides]. San Franc isco: Intercul-
tural and Emotion Research Laboratory, Department of Psychology,
San Francisco State University.
Méary, D., Kitromilides, E., Mazens, K., Graff, C., & Gentaz, E. (2007).
Four-day-old human neonates look longer at non-biological motions
of a single point-of-light. Plos ONE, 2, 186.
Michotte, A. (1946). La perception de la causalité. Louvain: Publica-
tions Universitaires de Louvain; Paris-Bruxelles: Erasme; Anvers-
Michotte, A. (1962). Causalité, permanence et réalité phénoménales.
Louvain: Publications Universitaires de Louvain.
Morris, J. S., DeGelder, B., Weiskrantz, L., & Dolan, R. J. (2001). Dif-
ferential extrageniculostriate and amygdala responses to presentation
of emotional faces in a cortically blind field. Brain, 124, 1241-1252.
Phaf, R. H., & Rotteveel, M. (2005). Affective modulation of recogni-
tion bias. Emotion, 5, 309-318. doi:10.1037/1528-3518.104.22.1689
Phaf, R. H., & Rotteveel, M. (2009). Looking at the bright side: The
affective monitoring of directi on. Emotion, 9, 729-733.
Podevin, G. (2009). Influence des mouvements elementaires sur les
processus cognitifs emotionnels. Thèse de Doctorat, Université de
Lille Nord de France UDL3.
Rimé, B., Boulanger, B., Laubin, P., Richir, M., & Stroobants, K. (1985).
The perception of interpersonal emotions originated by patterns of
movement. Motivation and Em otion , 9, 241-260.
Rimé, B., & Schiaratura, L. (1991). Gesture and speech. In R. S.
Feldman, & B. Rimé (Eds.), Fundamentals of nonverbal behavior
(pp. 239-281). New York: Press Syndicate of the University of Cam-
Rothermund, K. (2003). Motivation and attention: Incongruent effects
of feedback on the processing of val ence. Emotion, 3, 223-238.
Rothermund, K., Voss, A., & Wentura, D. (2008). Counter-regulation
in affective attentional biases: A basic mechanism that warrants
flexibility in emotion and motivation. Emotion, 8, 34-46.
Rusinek, S. (2009). Désensibilisation de l’arachnophobie à l’aide d’une
induction émotionnelle positive par le mouvement. 1er Congrès
Français de Psychiatrie, N ic e , décembre 2009.
Schaefer, A., Nils, F., Sanchez, X., & Philippot, P. (2010). Assessing
the effectiveness of a large database of emotion-eliciting films: A
new tool for emotion researchers. Cognition and Emotion, 24, 1153-
Simons, R. F., Detenber, B. H., Roedema, T. M., & Reiss, J. E. (1999).
Emotion processing in three systems: The medium and the message.
Psychophysiology, 36, 619-627. doi:10.1111/1469-8986.3650619
Simons, R. F., Detenber, B. H., Reiss, J. E., & Shults, C. W. (2000).
Image motion and context: A between and within subjects com- pa-
rison. Psychophysiology, 37, 706-710 .
Tremoulet, P. D., & Feldman, J. (2000). Perception of animacy from
the motion of a single ob j e ct. Perception, 29, 943-951.
Troje, N. F., Westhoff, C., & Lavrov, M. (2005). Person identification
from biological motion: Effects of structural and kinematic cues.
Perception & Psychophysics, 67, 667-675. doi:10.3758/BF03193523
Troje, N. F., & Westhoff, C. (2006). The inversion effect in biological
motion perception: Evidence for a “Life Detector”? Current Biology,
16, 821-824. doi:10.1016/j.cub.2006.03.022
Wentura, D., Voss, A., & Rothermund, K. (2009). Playing TETRIS for
science counter-regulatory affective processing in a motivationnally
“hot” context. Acta Psychologica, 131, 171- 177.
Copyright © 2012 SciRes. 89