Perceptual & Motor Skills: Perception 2014, 118, 1, 195-209. © Perceptual & Motor Skills 2014
EFFECTS OF ANTICIPATION ON PERCEPTION OF FACIAL EXPRESSIONS1, 2 GUANG MING RAN, XU CHEN, YAN GU PAN, TIAN QIANG HU, AND JING MA Southwest University, Chongqing, China Summary.—Human beings do not passively perceive the facial expressions of other people, but predict observed facial expressions by employing past experiences. The aim of the current study was to investigate whether and how anticipation affected the perception of facial expressions. A 3-way repeated-measures ANOVA on anticipation, orientation, and facial expression was performed on RTs and recognition accuracy in Experiments 1 and 2. The results showed that anticipation reduced susceptibility to negative facial expressions. In this regard, anticipation might be considered as an effective emotion-regulation strategy. In addition, a decreased inversion effect for positive facial expressions was found in the predictable condition, which might reflect a switch from feature-based to holistic processing.
As fundamental emotional stimuli, facial expressions play a significant role in social exchanges (Itier, Latinus, & Taylor, 2006; Luo, Feng, He, Wang, & Luo, 2010). The ability to perceive the facial expressions of other people enables an individual to identify both safe and dangerous situations. Considered from an evolutionary perspective, negative (threatening) faces are powerful visual stimuli to activate the human fear system (Öhman, 1986; Öhman, Lundqvist, & Esteves, 2001). Supporting this viewpoint, Eastwood, Smilek, and Merikle (2001) concluded that negative facial expressions guided attention more effectively than positive facial expressions (see also Eastwood, Smilek, & Merikle, 2003; Feldmann-Wüstefeld, Schmidt-Daffy, & Schubö, 2011). Therefore, it is not surprising that numerous behavioral and neurophysiological studies (e.g., Fox, Russo, & Dutton, 2002; Pourtois, Grandjean, Sander, & Vuilleumier, 2004; Righart & de Gelder, 2008) showed that negative facial expressions were processed more efficiently than positive expressions. Humans are perceptual experts in face processing and can identify thousands of facial expressions (emotional faces) at a single glance (Gaspar, Sekuler, & Bennett, 2008; Hasegawa & Unuma, 2010). Unlike other visual stimuli, facial expressions are perceived in a configural/holistic manner (Tanaka & Farah, 1993). Using a composite paradigm, Calder, Young, Keane, and Dean (2000) concluded that their experiments provided direct evidence for configural processing of facial expressions. However, only Address correspondence to Xu Chen, Faculty of Psychology, Southwest University Beibei, Chongqing 400715, China or e-mail ([email protected]). 2 The authors thank anonymous reviewers for their careful reading and constructive comments on previous versions of this paper. 1
DOI 10.2466/24.PMS.118k13w4
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adults were examined in their experiments, leaving the question as to how much of the effect is due to extensive experience and maturation. To assess this, Mondloch, Pathman, Maurer, Le Grand, and de Schonen (2007) tested 6-year-old children, and found that these children showed an adult-like composite facial expression effect. In addition, individuals with genetic and developmental prosopagnosia showed weaker configurational processing for facial expressions, which further supported the perspective of configural processing (Palermo, Willis, Rivolta, McKone, Wilson, & Calder, 2011). While individuals can easily identify upright facial expressions, their performance worsens when those same facial expressions are turned upside-down. This phenomenon is called the Face Inversion Effect (Yin, 1969). Interestingly, inverted and upright facial expressions contain the same amount of visual information, but individuals cannot extract that information from inverted faces as effectively as from upright faces (Gaspar, et al., 2008). The recognition impairment observed for inverted facial expressions could be due to a qualitative switch from configural to featural processing (Caharel, Montalan, Fromager, Bernard, Lalonde, & Mohamed, 2011). More precisely, inverted facial expressions may involve mostly featurebased processing. In support of this explanation, researches on prosopagnosia reported that inverted facial expressions were processed more like objects (Stephan, Breen, & Caine, 2006; Sato, Kochiyama, & Yoshikawa, 2011). To explore potential factors influencing the perception of upright and inverted facial expressions, previous studies have examined the influence of some bottom-up factors, such as the influence of spatial frequency (Gaspar, et al., 2008; Kikuchi, Senju, Hasegawa, Tojo, & Osanai, 2013). To date, however, anticipation (a form of top-down processing) has not been explored. It seems likely that humans do not passively perceive the facial expressions that they encounter, but predict observed facial expressions by employing experience. If that is true, the perception of facial expressions may be influenced by anticipation. According to the top-down facilitation model (Bar, 2003; Kveraga, Ghuman, & Bar, 2007), anticipation could speed up the perception process by reducing the range of possibilities from among which the perceiver chooses the identity of the objects, e.g., when one is looking for a stove in a kitchen, prior experience can be employed to predict the most likely identity of a square object which is standing on the floor. Because facial expression perception relies more strongly on configural information than object perception (Yin, 1969, 1970; Calder & Jansen, 2005), it is likely that anticipation affects the recognition of facial expressions and objects differently. Therefore, exploring the effects of anticipation on facial expressions may further clarify the perception process of facial expressions. Considerable study has indicated that negative facial expressions are preferentially processed relative to positive facial expressions, which
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implies that the human brain is especially sensitive to negative facial expressions (e.g., Fox, Lester, Russo, Bowles, Pichler, & Dutton, 2000; Suslow, Junghanns, & Arolt, 2001; Fox, et al., 2002; Pourtois, et al., 2004; Righart & de Gelder, 2008). According to the theory of emotional regulation (Gross, 2001), individuals can modulate their emotional response before the occurrence of emotional stimuli. Pre-awareness of forthcoming emotional events may help the brain to prepare cognitive resources in daily life (Lin, Gao, Ye, Wang, Tao, Ke, et al., 2012). In other words, individuals need not devote more attentional resources to negative events than to positive events. Therefore, it was assumed that anticipation would reduce susceptibility to negative facial expressions. Given that individuals tend to react automatically to negative (threatening) faces (Smith, Larsen, Chartrand, Cacioppo, Katafiasz, & Moran, 2006), inverted negative faces may be processed more like upright faces. However, inverted positive faces might be perceived in a feature-based manner that is not parsimonious (Caharel, et al., 2011). It has been shown that antecedent anticipation evokes past experiences to perceive external stimuli and interpret the sensory environment (Kveraga, et al., 2007). In that case, inverted positive faces might be processed holistically when individuals are able to predict the future emotional stimuli. Thus, it was expected that a reduced inversion effect for positive expressions should be found in the predictable condition compared to in the unpredictable condition. In the present work, two experiments were conducted to test the effects of anticipation on the perception of facial expressions. In Experiment 1, participants were asked to identify the emotion portrayed in each facial picture. Four types of facial pictures (upright and inverted positive, upright and inverted negative) were randomly presented in each block. In Experiment 2 the procedure was the same except that a no-arrow condition was added, in which a white screen was presented rather than an arrow. Experiment 1 METHOD Participants Thirty undergraduates (20 women, 10 men; M age = 21.1 yr., SD = 2.4) took part in the experiment. All participants were right-handed with normal or corrected-to-normal vision. None had any history of affective disorder. Each participant was asked to sign an informed consent form and received remuneration after the trial. The experimental procedure was in accordance with Helsinki guidelines as per the World Health Organization (Gilder, 1964). Stimuli and Apparatus Two sets of 192 facial pictures (192 upright and 192 inverted faces) were selected from the Chinese Facial Affective Picture System (CFAPS; Wang &
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Luo, 2005); within each set, half the faces depicted positive (happy) and half negative affects (angry, sad, fearful, disgusted or surprise), half female and half male targets. In accordance with the CFAPS scoring, comparison using t tests indicated that the positive and negative pictures differed in valence ratings (positive: 6.09 ± 0.67; negative: 2.94 ± 0.39; t190 = 40.31, twotailed p < .001) but were similar in arousal ratings (positive: 5.65 ± 0.75; negative: 5.74 ± 0.73; t190 = 0.81, two-tailed p = .42). All pictures were identical in size, background, spatial frequency, contrast, and brightness. The viewing angle (degrees subtended by an object at the lens of the eye) of each picture was 2.8 × 3.7⬚, with a screen resolution of 72 pixels per inch. Participants were seated comfortably 90 cm from the computer screen, and all the stimuli were presented in the center of the computer screen. The display was the DELL 17-in. color display, with a refresh rate of 75 Hz and a resolution 756 × 1024. The experimental procedure was organized by E-PRIME1.1. The software controlled stimulus presentations and recorded reaction times (RT) and recognition accuracy on each trial. Design and Procedure Three factors, anticipation (predictable, unpredictable), expression (positive, negative), and orientation (upright, inverted), were manipulated in the experiment. Thus, there were eight experimental conditions, with each experimental condition including 64 trials. Each trial started with a 500 msec. presentation of a red cross on a blank white screen, after which the cross disappeared and the screen remained empty for 500 msec. Next, a 200 msec. left-pointing or right-pointing red arrow was randomly presented, and when it disappeared, the white screen was presented again for 500 msec.3 After the white screen, an upright or inverted facial picture was randomly presented. Half of the participants were asked to press the “F” key with the left thumb if a positive facial picture was shown, or the “J” key with the right thumb if a negative facial picture was shown, whereas the other half of the participants were asked to use a reversed key arrangement. There were two types of experimental trials—consistent and inconsistent. On consistent trials, the left-pointing arrows were always accompanied by negative facial pictures, and the right-pointing arrows were always accompanied by positive facial pictures. On inconsistent trials, however, the orientations of the arrows were reversed and thus were exactly contrary to the consistent trials.
Past work (Hill, Strube, Roesch-Ely, & Weisbrod, 2002) suggested that prime-face sequence would be likely to decrease participants’ reaction time (RT). To avoid this unwanted effect, left-pointing or right-pointing arrows were used to anticipate forthcoming facial expressions. This was due to the fact that there was no semantic association between arrow and facial expressions. 3
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In the predictable condition, 75% of trials were consistent trials and the remaining 25% of trials were inconsistent trials. As a consequence, participants were able to anticipate the expression (positive/negative) of the next face to appear, e.g., when seeing a left-pointing arrow, participants were led to think that a negative face would more likely appear (Todorovic, van Ede, Maris, & de Lange, 2011). In contrast, in the unpredictable condition, participants could not predict the expression of the face to appear next because half the trials were consistent and half inconsistent. Each participant completed both blocks, with the sequence in which they were offered randomized across participants. TABLE 1 MEANS AND STANDARD DEVIATIONS OF REACTION TIME (RT) AND ACCURACY IN EXPERIMENT 1 BY ANTICIPATION CONDITION Reaction Time (msec.)
Face Orientation Expression Positive Negative
Predictable
Accuracy (%)
Unpredictable
Predictable
Unpredictable
M
SD
M
SD
M
SD
M
Upright
573.36
73.68
598.28
91.19
87.08
8.65
88.33
SD 8.18
Inverted
611.88
73.14
647.40
89.75
76.10
12.83
74.81
17.72
Upright
561.12
66.65
598.97
65.77
93.00
4.93
93.02
5.30
Inverted
590.24
69.77
640.59
66.67
85.94
8.58
85.12
9.12
RESULTS AND DISCUSSION For each participant, the mean correct RTs and accuracy rates were calculated for each condition (Table 1). RTs above 1,000 msec. were deleted prior to analysis as anticipatory errors and outliers. A repeated-measures ANOVA with expression (positive, negative), orientation (upright, inverted), and anticipation (predictable, unpredictable) as within-subject factors, was performed on the mean RTs and accuracy rates (Table 2). TABLE 2 RESULTS OF ANALYSIS OF VARIANCE IN EXPERIMENT 1 Source Anticipation (A) Expression (E) Orientation (O)
Reaction Time (msec.) MS
F1
82837.44 15.11 6000.30
0.75
94070.99 61.10
p
Accuracy (%) ηp2
MS
F1
p
ηp2 0.003
.001
0.34
2.57
0.09
.76
.40
0.03
3547.24
14.67
.001
0.34
< .001
0.68
5843.83
64.00
< .001
0.69
A×E
2890.58
1.68
.21
0.06
2.13
0.05
.83
0.002
A×O
1999.83
4.88
.04
0.14
42.88
3.04
.09
0.10
E×O
1069.90
1.075
.31
0.04
342.44
2.55
.12
0.08
0.05
.82
0.02
10.75
0.29
.60
0.01
A×E×O
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200 Response Time (Msec.)
G. M. RAN, ET AL. 800 Predictable
600
Unpredictable 400 200
800
Upright
Inverted
Inverted – Upright
FIG. 1. Means of reaction times (RT) for upright and inverted faces in both anticipation conditions (predictable, unpredictable) and the differences (inversion effect indexes) between the inverted and upright orientations (*p < .05).
Reaction Times A significant main effect of anticipation was found. The predictable facial expressions (M = 584.15, SD = 60.59) elicited faster RTs than unpredictable facial expressions (M = 621.31, SD = 66.25). There was also a significant main effect of orientation. Participants responded faster to upright facial expressions (M = 582.93, SD = 61.77) than to inverted facial expressions (M = 622.53, SD = 57.10). The main effect of expression was not statistically significant. There was a significant interaction between anticipation and orientation. Simple effects analyses showed that inversion effects were apparent in both anticipation conditions (predictable: p < .001; unpredictable: p < .001). To elaborate on the magnitude of inversion effects (Fig. 1), the inversion effect index (a metric for the inversion effect) was first calculated by subtracting the RTs elicited by inverted faces to those elicited by upright faces for each participant separately for the predictable and unpredictable conditions.4 Then a paired samples t test was used to compare the inversion effect indexes between both anticipation conditions. Interestingly, a reduced inversion effect was found in the predictable condition (M = 33.82, SD = 35.25) compared to the unpredictable condition (M = 45.37, SD = 26.58; t29 = 2.21, two-tailed p = .04, Cohen's d = 0.33). The other interactions were not statistically significant. Accuracy The main effects of orientation and expression were statistically significant. Participants were more accurate in the upright condition (M = 90.36, SD = 4.86) than in the inverted condition (M = 80.49, SD = 7.64). For expresThis analysis was also used by other researchers, e.g., Mondloch, Le Grand, and Maurer (2002), Vizioli, Foreman, Rousselet, and Caldara (2010), and Caharel, et al. (2011). 4
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sion, the accuracy rates of negative faces (M = 89.27, SD = 5.52) were higher than that of positive faces (M = 81.58, SD = 9.44). However, there was no main effect of anticipation. Furthermore, none of the interactions were statistically significant. Overall, anticipation exerted an influence on the perception of facial expressions. In this experiment, the authors provided direct evidence that anticipation could facilitate cognitive processing for human expressions. Furthermore, a reduced inversion effect was found in the predictable condition. However, this experiment is not without limitations. It is likely that the processing in the unpredictable condition might be disturbed by the arrow presentation. Therefore, the anticipation effect observed in Experiment 1 must be further verified. Experiment 2 To verify the anticipation effect, it is necessary to set a condition in which the arrow was not presented. Therefore, in Experiment 2 participants were asked to identify the emotion portrayed by each face in the three anticipation conditions (predictable, unpredictable, no arrow). METHOD Participants Thirty undergraduates (15 women, 15 men; M age = 21.3 yr., SD = 1.4) participated in the experiment. All participants were right-handed with normal or corrected-to-normal vision and had no history of any affective disorder. Stimuli and Apparatus In addition to the facial pictures of Experiment 1, another 192 facial pictures (96 upright and 96 inverted faces) were employed in Experiment 2. All pictures were significantly different in valence (positive: 5.86 ± 0.75; negative: 3.11 ± 0.57; t286 = 34.89, two-tailed p < .001), but were similar in arousal (positive: 5.39 ± 0.93; negative: 5.54 ± 1.05; t286 = –1.29, two-tailed p = .20). The apparatus were the same as those used in Experiment 1. Design and Procedure A 2 × 2 × 3 within-subject design was adopted. The three factors were expression (positive, negative), orientation (upright, inverted), and anticipation (predictable, unpredictable, no arrow). The procedure was the same as Experiment 1, except that a no arrow condition was added, in which a white screen rather than an arrow was presented. RESULTS AND DISCUSSION For each participant, the mean correct RTs and accuracy rates were calculated for each condition (Table 3). RTs above 1,000 msec. were deleted
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Negative
Positive
Expression
539.52
518.99
547.12
Inverted
Upright
Inverted
509.53
M 110.31 118.78
102.28 627.26
597.42
628.15
591.86
M
60.82
79.72
79.72
77.70
SD
Unpredictable M 633.17 632.64
608.07 55.07
49.89
62.32
64.03
SD
No Arrow 606.56
Reaction Time (msec.)
100.50
SD
Predictable
Upright
Orientation
83.80
92.09
84.06
90.32
M
14.22
12.17
13.59
11.05
SD
Predictable
79.11
84.67
66.41
82.97
M
16.99
18.70
26.71
19.49
SD
Unpredictable
Accuracy (%)
TABLE 3 MEANS AND STANDARD DEVIATIONS OF REACTION TIME AND ACCURACY IN EXPERIMENT 2 BY ANTICIPATION CONDITION
79.22
84.06
66.27
80.42
12.73
8.57
19.58
15.23
SD
No Arrow M
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ANTICIPATION, FACIAL EXPRESSION TABLE 4 RESULTS OF ANALYSIS OF VARIANCE IN EXPERIMENT 2 Source
Reaction Time (msec.) df
Anticipation (A)
2
Expression (E)
1
Orientation (O)
1
Accuracy (%) ηp2
df
MS
304111.91 16.48 < .001 0.36
MS
F
p
F
p
ηp2
2
3765.82
8.00
.001 0.22
0.01
1
2639.00
5.55
.03
76941.26 38.36 < .001 0.57
1
7740.08 49.54 < .001 0.63
1290.53
.33
.57
0.16
A×E
2
532.36
.60
.55
0.02
2
498.94
5.22
.01
0.15
A×O
2
420.15
.58
.56
0.02
2
108.60
4.58
.01
0.14
E×O
1
268.17
.31
.58
0.01
1
836.80
3.99
.06
0.12
A×E×O
2
50.75
.08
.92
0.003
2
375.92
7.36
.001 0.20
prior to analysis as anticipatory errors and outliers. A repeated-measures ANOVA with expression (positive, negative), orientation (upright, inverted), and anticipation (predictable, unpredictable, no arrow) as within-subject factors, was performed on the mean RTs and accuracy rates (Table 4). Reaction Times The analysis of RT data revealed significant main effects for anticipation and orientation. Participants responded faster in the predictable condition (M = 528.79, SD = 105.28) than in the no arrow (M = 620.11, SD = 48.45; p < .001) and unpredictable (M = 611.17, SD = 61.17; p = .001) conditions, while the latter two were not significantly different from each other (p = .26). Upright faces (M = 572.07, SD = 49.11) were processed faster than inverted ones (M = 601.30, SD = 56.72). However, there was no main effect of expression. Furthermore, none of the interactions were statistically significant. Accuracy The analysis of accuracy data showed statistically significant main effects for anticipation, orientation, and expression. Participants performed at higher accuracy rates in the predictable condition (M = 87.57, SD = 10.58) than in the no arrow (M = 77.49, SD = 9.33; p < .001) and unpredictable (M = 78.29, SD = 17.78; p = .02) conditions, while the latter two conditions did not show significant differences (p = .79). For orientation, human faces were recognized more accurately in the upright condition (M = 85.76, SD = 10.03) than in the inverted condition (M = 76.48, SD = 10.59). For expression, negative faces (M = 83.83, SD = 10.25) led to the higher accuracy rates, as compared with positive faces (M = 78.41, SD = 12.68). The interaction between anticipation and expression was significant. Simple effects analyses showed that recognition accuracy rates for negative faces were superior to that for positive faces in the unpredictable
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(negative: M = 81.90, SD = 17.14; positive: M = 74.69, SD = 21.25; p = .01) and no arrow (negative: M = 81.64, SD = 9.76; positive: M = 73.75, SD = 15.50; p = .02) conditions. However, participants recognized faces of both emotions (valences) equally well in the predictable condition (negative: M = 87.84, SD = 12.45; positive: M = 87.20, SD = 11.30; p = .71). There was also a statistically significant interaction between anticipation and orientation. Simple effects analyses showed that inversion effects were apparent in three anticipation conditions (predictable: p < .001; unpredictable: p < .001; no arrow: p < .001). As in Experiment 1, the inversion effect index was first calculated by subtracting the accuracy rates of upright faces to those of inverted faces for each participant separately for each anticipation condition. Then the inversion effect indexes were submitted to a repeated-measures analysis with anticipation as within-subject factor. A statistically significant main effect of anticipation revealed that the face inversion effect was decreased in the predictable condition (M = 7.27, SD = 7.75) compared to the unpredictable (M = 11.06, SD = 9.80; p = .02) and no arrow (M = 9.49, SD = 6.89; p = .05) conditions, while the latter two conditions displayed equivalent inversion effects (p = .20). It was found that there was a significant three-way interaction between expression, orientation, and anticipation, which suggested that the reduced inversion effect in the predictable condition was found only for positive faces (F2, 58 = 9.68, p < .001, ηp2 = 0.25) but not for negative faces (F2, 58 = 1.66, p = .20, ηp2 = 0.05). The results of Experiment 2 indicated that the predictable condition was significantly different from the no arrow and unpredictable conditions, but the latter two were not significantly different from each other. As in Experiment 1, participants were more accurate with the negative faces than with the positive ones. This finding is consistent with the hypothesis that emotional processing, especially potentially threatening stimuli, can occur automatically (Meng, Yuan, Li, 2009). Interestingly, a reduced inversion effect was found in the predictable condition, which is also in keeping with the results of Experiment 1. Further analysis demonstrated that this reduced inversion effect in the predictable condition was observed only when the facial expressions were positive. Another finding in Experiment 2 was that the superior processing of negative faces was eliminated with antecedent anticipation. GENERAL DISCUSSION Based on the top-down facilitation model (Kveraga, et al., 2007), the current two experiments tested hypotheses about the effects of anticipation on the perception of facial expressions. Results were consistent with the hypothesis: as an example of top-down processing, anticipation reduced susceptibility to negative facial expressions. In addition, a decreased inversion effect in predictable conditions was found only when
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the faces were positive, which might reflect a switch from feature-based to holistic processing. Anticipation Reduces Susceptibility to Negative Facial Expressions The outcomes of Experiment 2 showed that recognition accuracy rates for negative faces were superior to that for positive faces in the unpredictable condition, but not in the predictable condition. This finding suggests that unpredictable negative faces induced sustained engagement of visual attention in comparison with positive faces (Mangun, 1995). One possible reason could be due to the fact that negative faces (threatening stimuli) are biologically important. However, this superior processing of negative faces was eliminated when facial stimuli were predictable. Past studies (e.g., Ziv, Tomer, Defrin, & Hendler, 2010; Lin, et al., 2012) indicated that pre-awareness of incoming events facilitated reallocating of cognitive resources as well as pre-preparation of behavioral coping strategies. In that case, individuals are able to better cope with potential dangers in the environment. In this regard, anticipation might be thought of as an effective strategy of emotion regulation that dampens human susceptibility to negative faces. Another potential explanation for this reduced susceptibility could be that anticipation eliminates the extremity bias in evaluation. According to Cacioppo’s model of affective processing (Ito, Larsen, Smith, & Cacioppo, 1998; Cacioppo, Gardner, & Berntson, 1999), negative stimuli could be evaluated more extremely than positive stimuli. Given that top-down anticipation evokes experience to evaluate emotional stimuli, it is likely that individuals need not devote more attentional resources to negative faces than to positive ones. Consequently, this extremity bias in evaluation vanishes with antecedent anticipation. Anticipation Decreases Inversion Effect for Positive Facial Expressions The results of Experiment 2 were in line with the hypothesis that antecedent anticipation reduced the inversion effect for positive expressions. The predictive coding models of visual cognition assume the visual cortical hierarchy includes two different levels of processing units: representational units are responsible for encoding of anticipation probability, which will provide anticipation for next lower level input, while error units are responsible for encoding the mismatch between the anticipation and the bottom-up evidence, and can then send the anticipation error to the next higher level, where representations are adjusted to eliminate prediction error (Friston, 2005; Spratling, 2008; Egner, Monti, & Summerfield, 2010). According to predictive coding models, predictive encoding strategies are assumed to be parsimonious (concise). More precisely, the brain does not need to maintain the same information at different levels of the processing hierarchy. In this way, the resources needed for representing
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perceptual input are minimized, so predictable stimuli elicit lower level activity compared to unpredictable stimuli (Alink, Schwiedrzik, Kohler, Singer, & Muckli, 2010). It is widely accepted that perception of upright facial expressions depends on a holistic processing style that is parsimonious (McKelvie, 1995; Palermo, Willis, Rivolta, Wilson, & Calder, 2010). In contrast, inverted facial expressions are perceived in a feature-based manner that can not satisfy parsimonious processing of the cognitive system (Narme, Bonnet, Dubois, & Chaby, 2011). It should be noted that inverted negative faces might involve mostly parsimonious processing as in upright facial recognition because humans tend to react automatically to negative (threatening) faces (Smith, et al., 2006). Based on the parsimony predictive coding strategy, individuals employ a parsimonious processing manner to identify inverted positive faces when they are able to predict the future emotional stimuli. Therefore, the face inversion effect for positive faces is reduced with antecedent anticipation. Upright facial expressions are believed to be processed holistically. However, if those same facial expressions are turned upside-down, the holistic processing will be disrupted (Caharel, et al., 2011). In other words, inverted facial expressions are perceived in a feature-based processing manner. Interestingly, the reduced face-inversion effect for positive faces observed in the predictable condition might reflect a switch from feature-based to holistic processing. If that is true, the authors hypothesize that anticipation could facilitate the perception of visual stimuli which involve mostly feature-based processing, e.g., anticipation may eliminate the other-race effect (ORE). It is necessary to emphasize that the anticipation effect under investigation here is specifically related to faces, rather than being an effect of more general processes. According to previous studies on face-inversion effect (Bahrick, Bahrick, & Wittlinger, 1975; Gaspar, et al., 2008), faces are processed differently from other visual stimuli because humans are experts at recognizing faces and have extensive experience with faces. In current study, only the anticipation effect relating to faces was examined. It would be useful to include a comparison condition in which non-face visual stimuli are presented in future research, which would test for possible differences between face and non-face anticipation. The authors would predict that such a difference would be observed. Although the results of Experiment 2 showed that anticipation reduced brain susceptibility to negative facial expressions, this effect was not found in Experiment 1. The lack of evidence of this reduced susceptibility in Experiment 1 could be due to the fact that the number of female participants was disproportionally larger than that of males. In support of this explanation, Jin, Yan, Zhang, Jiang, Tao, and Zheng (2013) found that anticipation was modulated by gender.
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Conclusion In summary, the present study investigated the effects of anticipation on facial expression perception by employing a modified cuing paradigm. It was found that anticipation reduced susceptibility to negative facial expressions, which implied that anticipation might be regarded as an effective emotion regulation strategy. In addition, a decreased inversion effect in predictable conditions was found only when the faces were positive, which might reflect a switch from feature-based to holistic processing. REFERENCES
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EFFECTS OF ANTICIPATION ON PERCEPTION OF FACIAL EXPRESSIONS1, 2 GUANG MING RAN, XU CHEN, YAN GU PAN, TIAN QIANG HU, AND JING MA Southwest University, Chongqing, China Summary.—Human beings do not passively perceive the facial expressions of other people, but predict observed facial expressions by employing past experiences. The aim of the current study was to investigate whether and how anticipation affected the perception of facial expressions. A 3-way repeated-measures ANOVA on anticipation, orientation, and facial expression was performed on RTs and recognition accuracy in Experiments 1 and 2. The results showed that anticipation reduced susceptibility to negative facial expressions. In this regard, anticipation might be considered as an effective emotion-regulation strategy. In addition, a decreased inversion effect for positive facial expressions was found in the predictable condition, which might reflect a switch from feature-based to holistic processing.
As fundamental emotional stimuli, facial expressions play a significant role in social exchanges (Itier, Latinus, & Taylor, 2006; Luo, Feng, He, Wang, & Luo, 2010). The ability to perceive the facial expressions of other people enables an individual to identify both safe and dangerous situations. Considered from an evolutionary perspective, negative (threatening) faces are powerful visual stimuli to activate the human fear system (Öhman, 1986; Öhman, Lundqvist, & Esteves, 2001). Supporting this viewpoint, Eastwood, Smilek, and Merikle (2001) concluded that negative facial expressions guided attention more effectively than positive facial expressions (see also Eastwood, Smilek, & Merikle, 2003; Feldmann-Wüstefeld, Schmidt-Daffy, & Schubö, 2011). Therefore, it is not surprising that numerous behavioral and neurophysiological studies (e.g., Fox, Russo, & Dutton, 2002; Pourtois, Grandjean, Sander, & Vuilleumier, 2004; Righart & de Gelder, 2008) showed that negative facial expressions were processed more efficiently than positive expressions. Humans are perceptual experts in face processing and can identify thousands of facial expressions (emotional faces) at a single glance (Gaspar, Sekuler, & Bennett, 2008; Hasegawa & Unuma, 2010). Unlike other visual stimuli, facial expressions are perceived in a configural/holistic manner (Tanaka & Farah, 1993). Using a composite paradigm, Calder, Young, Keane, and Dean (2000) concluded that their experiments provided direct evidence for configural processing of facial expressions. However, only Address correspondence to Xu Chen, Faculty of Psychology, Southwest University Beibei, Chongqing 400715, China or e-mail ([email protected]). 2 The authors thank anonymous reviewers for their careful reading and constructive comments on previous versions of this paper. 1
DOI 10.2466/24.PMS.118k13w4
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adults were examined in their experiments, leaving the question as to how much of the effect is due to extensive experience and maturation. To assess this, Mondloch, Pathman, Maurer, Le Grand, and de Schonen (2007) tested 6-year-old children, and found that these children showed an adult-like composite facial expression effect. In addition, individuals with genetic and developmental prosopagnosia showed weaker configurational processing for facial expressions, which further supported the perspective of configural processing (Palermo, Willis, Rivolta, McKone, Wilson, & Calder, 2011). While individuals can easily identify upright facial expressions, their performance worsens when those same facial expressions are turned upside-down. This phenomenon is called the Face Inversion Effect (Yin, 1969). Interestingly, inverted and upright facial expressions contain the same amount of visual information, but individuals cannot extract that information from inverted faces as effectively as from upright faces (Gaspar, et al., 2008). The recognition impairment observed for inverted facial expressions could be due to a qualitative switch from configural to featural processing (Caharel, Montalan, Fromager, Bernard, Lalonde, & Mohamed, 2011). More precisely, inverted facial expressions may involve mostly featurebased processing. In support of this explanation, researches on prosopagnosia reported that inverted facial expressions were processed more like objects (Stephan, Breen, & Caine, 2006; Sato, Kochiyama, & Yoshikawa, 2011). To explore potential factors influencing the perception of upright and inverted facial expressions, previous studies have examined the influence of some bottom-up factors, such as the influence of spatial frequency (Gaspar, et al., 2008; Kikuchi, Senju, Hasegawa, Tojo, & Osanai, 2013). To date, however, anticipation (a form of top-down processing) has not been explored. It seems likely that humans do not passively perceive the facial expressions that they encounter, but predict observed facial expressions by employing experience. If that is true, the perception of facial expressions may be influenced by anticipation. According to the top-down facilitation model (Bar, 2003; Kveraga, Ghuman, & Bar, 2007), anticipation could speed up the perception process by reducing the range of possibilities from among which the perceiver chooses the identity of the objects, e.g., when one is looking for a stove in a kitchen, prior experience can be employed to predict the most likely identity of a square object which is standing on the floor. Because facial expression perception relies more strongly on configural information than object perception (Yin, 1969, 1970; Calder & Jansen, 2005), it is likely that anticipation affects the recognition of facial expressions and objects differently. Therefore, exploring the effects of anticipation on facial expressions may further clarify the perception process of facial expressions. Considerable study has indicated that negative facial expressions are preferentially processed relative to positive facial expressions, which
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implies that the human brain is especially sensitive to negative facial expressions (e.g., Fox, Lester, Russo, Bowles, Pichler, & Dutton, 2000; Suslow, Junghanns, & Arolt, 2001; Fox, et al., 2002; Pourtois, et al., 2004; Righart & de Gelder, 2008). According to the theory of emotional regulation (Gross, 2001), individuals can modulate their emotional response before the occurrence of emotional stimuli. Pre-awareness of forthcoming emotional events may help the brain to prepare cognitive resources in daily life (Lin, Gao, Ye, Wang, Tao, Ke, et al., 2012). In other words, individuals need not devote more attentional resources to negative events than to positive events. Therefore, it was assumed that anticipation would reduce susceptibility to negative facial expressions. Given that individuals tend to react automatically to negative (threatening) faces (Smith, Larsen, Chartrand, Cacioppo, Katafiasz, & Moran, 2006), inverted negative faces may be processed more like upright faces. However, inverted positive faces might be perceived in a feature-based manner that is not parsimonious (Caharel, et al., 2011). It has been shown that antecedent anticipation evokes past experiences to perceive external stimuli and interpret the sensory environment (Kveraga, et al., 2007). In that case, inverted positive faces might be processed holistically when individuals are able to predict the future emotional stimuli. Thus, it was expected that a reduced inversion effect for positive expressions should be found in the predictable condition compared to in the unpredictable condition. In the present work, two experiments were conducted to test the effects of anticipation on the perception of facial expressions. In Experiment 1, participants were asked to identify the emotion portrayed in each facial picture. Four types of facial pictures (upright and inverted positive, upright and inverted negative) were randomly presented in each block. In Experiment 2 the procedure was the same except that a no-arrow condition was added, in which a white screen was presented rather than an arrow. Experiment 1 METHOD Participants Thirty undergraduates (20 women, 10 men; M age = 21.1 yr., SD = 2.4) took part in the experiment. All participants were right-handed with normal or corrected-to-normal vision. None had any history of affective disorder. Each participant was asked to sign an informed consent form and received remuneration after the trial. The experimental procedure was in accordance with Helsinki guidelines as per the World Health Organization (Gilder, 1964). Stimuli and Apparatus Two sets of 192 facial pictures (192 upright and 192 inverted faces) were selected from the Chinese Facial Affective Picture System (CFAPS; Wang &
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Luo, 2005); within each set, half the faces depicted positive (happy) and half negative affects (angry, sad, fearful, disgusted or surprise), half female and half male targets. In accordance with the CFAPS scoring, comparison using t tests indicated that the positive and negative pictures differed in valence ratings (positive: 6.09 ± 0.67; negative: 2.94 ± 0.39; t190 = 40.31, twotailed p < .001) but were similar in arousal ratings (positive: 5.65 ± 0.75; negative: 5.74 ± 0.73; t190 = 0.81, two-tailed p = .42). All pictures were identical in size, background, spatial frequency, contrast, and brightness. The viewing angle (degrees subtended by an object at the lens of the eye) of each picture was 2.8 × 3.7⬚, with a screen resolution of 72 pixels per inch. Participants were seated comfortably 90 cm from the computer screen, and all the stimuli were presented in the center of the computer screen. The display was the DELL 17-in. color display, with a refresh rate of 75 Hz and a resolution 756 × 1024. The experimental procedure was organized by E-PRIME1.1. The software controlled stimulus presentations and recorded reaction times (RT) and recognition accuracy on each trial. Design and Procedure Three factors, anticipation (predictable, unpredictable), expression (positive, negative), and orientation (upright, inverted), were manipulated in the experiment. Thus, there were eight experimental conditions, with each experimental condition including 64 trials. Each trial started with a 500 msec. presentation of a red cross on a blank white screen, after which the cross disappeared and the screen remained empty for 500 msec. Next, a 200 msec. left-pointing or right-pointing red arrow was randomly presented, and when it disappeared, the white screen was presented again for 500 msec.3 After the white screen, an upright or inverted facial picture was randomly presented. Half of the participants were asked to press the “F” key with the left thumb if a positive facial picture was shown, or the “J” key with the right thumb if a negative facial picture was shown, whereas the other half of the participants were asked to use a reversed key arrangement. There were two types of experimental trials—consistent and inconsistent. On consistent trials, the left-pointing arrows were always accompanied by negative facial pictures, and the right-pointing arrows were always accompanied by positive facial pictures. On inconsistent trials, however, the orientations of the arrows were reversed and thus were exactly contrary to the consistent trials.
Past work (Hill, Strube, Roesch-Ely, & Weisbrod, 2002) suggested that prime-face sequence would be likely to decrease participants’ reaction time (RT). To avoid this unwanted effect, left-pointing or right-pointing arrows were used to anticipate forthcoming facial expressions. This was due to the fact that there was no semantic association between arrow and facial expressions. 3
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In the predictable condition, 75% of trials were consistent trials and the remaining 25% of trials were inconsistent trials. As a consequence, participants were able to anticipate the expression (positive/negative) of the next face to appear, e.g., when seeing a left-pointing arrow, participants were led to think that a negative face would more likely appear (Todorovic, van Ede, Maris, & de Lange, 2011). In contrast, in the unpredictable condition, participants could not predict the expression of the face to appear next because half the trials were consistent and half inconsistent. Each participant completed both blocks, with the sequence in which they were offered randomized across participants. TABLE 1 MEANS AND STANDARD DEVIATIONS OF REACTION TIME (RT) AND ACCURACY IN EXPERIMENT 1 BY ANTICIPATION CONDITION Reaction Time (msec.)
Face Orientation Expression Positive Negative
Predictable
Accuracy (%)
Unpredictable
Predictable
Unpredictable
M
SD
M
SD
M
SD
M
Upright
573.36
73.68
598.28
91.19
87.08
8.65
88.33
SD 8.18
Inverted
611.88
73.14
647.40
89.75
76.10
12.83
74.81
17.72
Upright
561.12
66.65
598.97
65.77
93.00
4.93
93.02
5.30
Inverted
590.24
69.77
640.59
66.67
85.94
8.58
85.12
9.12
RESULTS AND DISCUSSION For each participant, the mean correct RTs and accuracy rates were calculated for each condition (Table 1). RTs above 1,000 msec. were deleted prior to analysis as anticipatory errors and outliers. A repeated-measures ANOVA with expression (positive, negative), orientation (upright, inverted), and anticipation (predictable, unpredictable) as within-subject factors, was performed on the mean RTs and accuracy rates (Table 2). TABLE 2 RESULTS OF ANALYSIS OF VARIANCE IN EXPERIMENT 1 Source Anticipation (A) Expression (E) Orientation (O)
Reaction Time (msec.) MS
F1
82837.44 15.11 6000.30
0.75
94070.99 61.10
p
Accuracy (%) ηp2
MS
F1
p
ηp2 0.003
.001
0.34
2.57
0.09
.76
.40
0.03
3547.24
14.67
.001
0.34
< .001
0.68
5843.83
64.00
< .001
0.69
A×E
2890.58
1.68
.21
0.06
2.13
0.05
.83
0.002
A×O
1999.83
4.88
.04
0.14
42.88
3.04
.09
0.10
E×O
1069.90
1.075
.31
0.04
342.44
2.55
.12
0.08
0.05
.82
0.02
10.75
0.29
.60
0.01
A×E×O
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200 Response Time (Msec.)
G. M. RAN, ET AL. 800 Predictable
600
Unpredictable 400 200
800
Upright
Inverted
Inverted – Upright
FIG. 1. Means of reaction times (RT) for upright and inverted faces in both anticipation conditions (predictable, unpredictable) and the differences (inversion effect indexes) between the inverted and upright orientations (*p < .05).
Reaction Times A significant main effect of anticipation was found. The predictable facial expressions (M = 584.15, SD = 60.59) elicited faster RTs than unpredictable facial expressions (M = 621.31, SD = 66.25). There was also a significant main effect of orientation. Participants responded faster to upright facial expressions (M = 582.93, SD = 61.77) than to inverted facial expressions (M = 622.53, SD = 57.10). The main effect of expression was not statistically significant. There was a significant interaction between anticipation and orientation. Simple effects analyses showed that inversion effects were apparent in both anticipation conditions (predictable: p < .001; unpredictable: p < .001). To elaborate on the magnitude of inversion effects (Fig. 1), the inversion effect index (a metric for the inversion effect) was first calculated by subtracting the RTs elicited by inverted faces to those elicited by upright faces for each participant separately for the predictable and unpredictable conditions.4 Then a paired samples t test was used to compare the inversion effect indexes between both anticipation conditions. Interestingly, a reduced inversion effect was found in the predictable condition (M = 33.82, SD = 35.25) compared to the unpredictable condition (M = 45.37, SD = 26.58; t29 = 2.21, two-tailed p = .04, Cohen's d = 0.33). The other interactions were not statistically significant. Accuracy The main effects of orientation and expression were statistically significant. Participants were more accurate in the upright condition (M = 90.36, SD = 4.86) than in the inverted condition (M = 80.49, SD = 7.64). For expresThis analysis was also used by other researchers, e.g., Mondloch, Le Grand, and Maurer (2002), Vizioli, Foreman, Rousselet, and Caldara (2010), and Caharel, et al. (2011). 4
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201
sion, the accuracy rates of negative faces (M = 89.27, SD = 5.52) were higher than that of positive faces (M = 81.58, SD = 9.44). However, there was no main effect of anticipation. Furthermore, none of the interactions were statistically significant. Overall, anticipation exerted an influence on the perception of facial expressions. In this experiment, the authors provided direct evidence that anticipation could facilitate cognitive processing for human expressions. Furthermore, a reduced inversion effect was found in the predictable condition. However, this experiment is not without limitations. It is likely that the processing in the unpredictable condition might be disturbed by the arrow presentation. Therefore, the anticipation effect observed in Experiment 1 must be further verified. Experiment 2 To verify the anticipation effect, it is necessary to set a condition in which the arrow was not presented. Therefore, in Experiment 2 participants were asked to identify the emotion portrayed by each face in the three anticipation conditions (predictable, unpredictable, no arrow). METHOD Participants Thirty undergraduates (15 women, 15 men; M age = 21.3 yr., SD = 1.4) participated in the experiment. All participants were right-handed with normal or corrected-to-normal vision and had no history of any affective disorder. Stimuli and Apparatus In addition to the facial pictures of Experiment 1, another 192 facial pictures (96 upright and 96 inverted faces) were employed in Experiment 2. All pictures were significantly different in valence (positive: 5.86 ± 0.75; negative: 3.11 ± 0.57; t286 = 34.89, two-tailed p < .001), but were similar in arousal (positive: 5.39 ± 0.93; negative: 5.54 ± 1.05; t286 = –1.29, two-tailed p = .20). The apparatus were the same as those used in Experiment 1. Design and Procedure A 2 × 2 × 3 within-subject design was adopted. The three factors were expression (positive, negative), orientation (upright, inverted), and anticipation (predictable, unpredictable, no arrow). The procedure was the same as Experiment 1, except that a no arrow condition was added, in which a white screen rather than an arrow was presented. RESULTS AND DISCUSSION For each participant, the mean correct RTs and accuracy rates were calculated for each condition (Table 3). RTs above 1,000 msec. were deleted
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Negative
Positive
Expression
539.52
518.99
547.12
Inverted
Upright
Inverted
509.53
M 110.31 118.78
102.28 627.26
597.42
628.15
591.86
M
60.82
79.72
79.72
77.70
SD
Unpredictable M 633.17 632.64
608.07 55.07
49.89
62.32
64.03
SD
No Arrow 606.56
Reaction Time (msec.)
100.50
SD
Predictable
Upright
Orientation
83.80
92.09
84.06
90.32
M
14.22
12.17
13.59
11.05
SD
Predictable
79.11
84.67
66.41
82.97
M
16.99
18.70
26.71
19.49
SD
Unpredictable
Accuracy (%)
TABLE 3 MEANS AND STANDARD DEVIATIONS OF REACTION TIME AND ACCURACY IN EXPERIMENT 2 BY ANTICIPATION CONDITION
79.22
84.06
66.27
80.42
12.73
8.57
19.58
15.23
SD
No Arrow M
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ANTICIPATION, FACIAL EXPRESSION TABLE 4 RESULTS OF ANALYSIS OF VARIANCE IN EXPERIMENT 2 Source
Reaction Time (msec.) df
Anticipation (A)
2
Expression (E)
1
Orientation (O)
1
Accuracy (%) ηp2
df
MS
304111.91 16.48 < .001 0.36
MS
F
p
F
p
ηp2
2
3765.82
8.00
.001 0.22
0.01
1
2639.00
5.55
.03
76941.26 38.36 < .001 0.57
1
7740.08 49.54 < .001 0.63
1290.53
.33
.57
0.16
A×E
2
532.36
.60
.55
0.02
2
498.94
5.22
.01
0.15
A×O
2
420.15
.58
.56
0.02
2
108.60
4.58
.01
0.14
E×O
1
268.17
.31
.58
0.01
1
836.80
3.99
.06
0.12
A×E×O
2
50.75
.08
.92
0.003
2
375.92
7.36
.001 0.20
prior to analysis as anticipatory errors and outliers. A repeated-measures ANOVA with expression (positive, negative), orientation (upright, inverted), and anticipation (predictable, unpredictable, no arrow) as within-subject factors, was performed on the mean RTs and accuracy rates (Table 4). Reaction Times The analysis of RT data revealed significant main effects for anticipation and orientation. Participants responded faster in the predictable condition (M = 528.79, SD = 105.28) than in the no arrow (M = 620.11, SD = 48.45; p < .001) and unpredictable (M = 611.17, SD = 61.17; p = .001) conditions, while the latter two were not significantly different from each other (p = .26). Upright faces (M = 572.07, SD = 49.11) were processed faster than inverted ones (M = 601.30, SD = 56.72). However, there was no main effect of expression. Furthermore, none of the interactions were statistically significant. Accuracy The analysis of accuracy data showed statistically significant main effects for anticipation, orientation, and expression. Participants performed at higher accuracy rates in the predictable condition (M = 87.57, SD = 10.58) than in the no arrow (M = 77.49, SD = 9.33; p < .001) and unpredictable (M = 78.29, SD = 17.78; p = .02) conditions, while the latter two conditions did not show significant differences (p = .79). For orientation, human faces were recognized more accurately in the upright condition (M = 85.76, SD = 10.03) than in the inverted condition (M = 76.48, SD = 10.59). For expression, negative faces (M = 83.83, SD = 10.25) led to the higher accuracy rates, as compared with positive faces (M = 78.41, SD = 12.68). The interaction between anticipation and expression was significant. Simple effects analyses showed that recognition accuracy rates for negative faces were superior to that for positive faces in the unpredictable
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(negative: M = 81.90, SD = 17.14; positive: M = 74.69, SD = 21.25; p = .01) and no arrow (negative: M = 81.64, SD = 9.76; positive: M = 73.75, SD = 15.50; p = .02) conditions. However, participants recognized faces of both emotions (valences) equally well in the predictable condition (negative: M = 87.84, SD = 12.45; positive: M = 87.20, SD = 11.30; p = .71). There was also a statistically significant interaction between anticipation and orientation. Simple effects analyses showed that inversion effects were apparent in three anticipation conditions (predictable: p < .001; unpredictable: p < .001; no arrow: p < .001). As in Experiment 1, the inversion effect index was first calculated by subtracting the accuracy rates of upright faces to those of inverted faces for each participant separately for each anticipation condition. Then the inversion effect indexes were submitted to a repeated-measures analysis with anticipation as within-subject factor. A statistically significant main effect of anticipation revealed that the face inversion effect was decreased in the predictable condition (M = 7.27, SD = 7.75) compared to the unpredictable (M = 11.06, SD = 9.80; p = .02) and no arrow (M = 9.49, SD = 6.89; p = .05) conditions, while the latter two conditions displayed equivalent inversion effects (p = .20). It was found that there was a significant three-way interaction between expression, orientation, and anticipation, which suggested that the reduced inversion effect in the predictable condition was found only for positive faces (F2, 58 = 9.68, p < .001, ηp2 = 0.25) but not for negative faces (F2, 58 = 1.66, p = .20, ηp2 = 0.05). The results of Experiment 2 indicated that the predictable condition was significantly different from the no arrow and unpredictable conditions, but the latter two were not significantly different from each other. As in Experiment 1, participants were more accurate with the negative faces than with the positive ones. This finding is consistent with the hypothesis that emotional processing, especially potentially threatening stimuli, can occur automatically (Meng, Yuan, Li, 2009). Interestingly, a reduced inversion effect was found in the predictable condition, which is also in keeping with the results of Experiment 1. Further analysis demonstrated that this reduced inversion effect in the predictable condition was observed only when the facial expressions were positive. Another finding in Experiment 2 was that the superior processing of negative faces was eliminated with antecedent anticipation. GENERAL DISCUSSION Based on the top-down facilitation model (Kveraga, et al., 2007), the current two experiments tested hypotheses about the effects of anticipation on the perception of facial expressions. Results were consistent with the hypothesis: as an example of top-down processing, anticipation reduced susceptibility to negative facial expressions. In addition, a decreased inversion effect in predictable conditions was found only when
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the faces were positive, which might reflect a switch from feature-based to holistic processing. Anticipation Reduces Susceptibility to Negative Facial Expressions The outcomes of Experiment 2 showed that recognition accuracy rates for negative faces were superior to that for positive faces in the unpredictable condition, but not in the predictable condition. This finding suggests that unpredictable negative faces induced sustained engagement of visual attention in comparison with positive faces (Mangun, 1995). One possible reason could be due to the fact that negative faces (threatening stimuli) are biologically important. However, this superior processing of negative faces was eliminated when facial stimuli were predictable. Past studies (e.g., Ziv, Tomer, Defrin, & Hendler, 2010; Lin, et al., 2012) indicated that pre-awareness of incoming events facilitated reallocating of cognitive resources as well as pre-preparation of behavioral coping strategies. In that case, individuals are able to better cope with potential dangers in the environment. In this regard, anticipation might be thought of as an effective strategy of emotion regulation that dampens human susceptibility to negative faces. Another potential explanation for this reduced susceptibility could be that anticipation eliminates the extremity bias in evaluation. According to Cacioppo’s model of affective processing (Ito, Larsen, Smith, & Cacioppo, 1998; Cacioppo, Gardner, & Berntson, 1999), negative stimuli could be evaluated more extremely than positive stimuli. Given that top-down anticipation evokes experience to evaluate emotional stimuli, it is likely that individuals need not devote more attentional resources to negative faces than to positive ones. Consequently, this extremity bias in evaluation vanishes with antecedent anticipation. Anticipation Decreases Inversion Effect for Positive Facial Expressions The results of Experiment 2 were in line with the hypothesis that antecedent anticipation reduced the inversion effect for positive expressions. The predictive coding models of visual cognition assume the visual cortical hierarchy includes two different levels of processing units: representational units are responsible for encoding of anticipation probability, which will provide anticipation for next lower level input, while error units are responsible for encoding the mismatch between the anticipation and the bottom-up evidence, and can then send the anticipation error to the next higher level, where representations are adjusted to eliminate prediction error (Friston, 2005; Spratling, 2008; Egner, Monti, & Summerfield, 2010). According to predictive coding models, predictive encoding strategies are assumed to be parsimonious (concise). More precisely, the brain does not need to maintain the same information at different levels of the processing hierarchy. In this way, the resources needed for representing
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perceptual input are minimized, so predictable stimuli elicit lower level activity compared to unpredictable stimuli (Alink, Schwiedrzik, Kohler, Singer, & Muckli, 2010). It is widely accepted that perception of upright facial expressions depends on a holistic processing style that is parsimonious (McKelvie, 1995; Palermo, Willis, Rivolta, Wilson, & Calder, 2010). In contrast, inverted facial expressions are perceived in a feature-based manner that can not satisfy parsimonious processing of the cognitive system (Narme, Bonnet, Dubois, & Chaby, 2011). It should be noted that inverted negative faces might involve mostly parsimonious processing as in upright facial recognition because humans tend to react automatically to negative (threatening) faces (Smith, et al., 2006). Based on the parsimony predictive coding strategy, individuals employ a parsimonious processing manner to identify inverted positive faces when they are able to predict the future emotional stimuli. Therefore, the face inversion effect for positive faces is reduced with antecedent anticipation. Upright facial expressions are believed to be processed holistically. However, if those same facial expressions are turned upside-down, the holistic processing will be disrupted (Caharel, et al., 2011). In other words, inverted facial expressions are perceived in a feature-based processing manner. Interestingly, the reduced face-inversion effect for positive faces observed in the predictable condition might reflect a switch from feature-based to holistic processing. If that is true, the authors hypothesize that anticipation could facilitate the perception of visual stimuli which involve mostly feature-based processing, e.g., anticipation may eliminate the other-race effect (ORE). It is necessary to emphasize that the anticipation effect under investigation here is specifically related to faces, rather than being an effect of more general processes. According to previous studies on face-inversion effect (Bahrick, Bahrick, & Wittlinger, 1975; Gaspar, et al., 2008), faces are processed differently from other visual stimuli because humans are experts at recognizing faces and have extensive experience with faces. In current study, only the anticipation effect relating to faces was examined. It would be useful to include a comparison condition in which non-face visual stimuli are presented in future research, which would test for possible differences between face and non-face anticipation. The authors would predict that such a difference would be observed. Although the results of Experiment 2 showed that anticipation reduced brain susceptibility to negative facial expressions, this effect was not found in Experiment 1. The lack of evidence of this reduced susceptibility in Experiment 1 could be due to the fact that the number of female participants was disproportionally larger than that of males. In support of this explanation, Jin, Yan, Zhang, Jiang, Tao, and Zheng (2013) found that anticipation was modulated by gender.
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Conclusion In summary, the present study investigated the effects of anticipation on facial expression perception by employing a modified cuing paradigm. It was found that anticipation reduced susceptibility to negative facial expressions, which implied that anticipation might be regarded as an effective emotion regulation strategy. In addition, a decreased inversion effect in predictable conditions was found only when the faces were positive, which might reflect a switch from feature-based to holistic processing. REFERENCES
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