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Understanding emotions from standardized facial expressions in autism and normal development

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The study investigated the recognition of standardized facial expressions of emotion (anger, fear, disgust, happiness, sadness, surprise) at a perceptual level (experiment 1) and at a semantic level (experiments 2 and 3) in children with autism (N = 20) and normally developing children (N = 20). Results revealed that children with autism were as able as controls to recognize all six emotions with different intensity levels, and that they made the same type of errors. These negative findings are discussed in relation to (1) previous data showing specific impairment in autism in recognizing the belief-based expression of surprise, (2) previous data showing specific impairment in autism in recognizing fear, and (3) the convergence of findings that individuals with autism, like patients with amygdala damage, pass a basic emotions recognition test but fail to recognize more complex stimuli involving the perception of faces or part of faces.
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428
Understanding emotions
from standardized facial
expressions in autism and
normal development
FULVIA CASTELLI California Institute of Technology, USA
ABSTRACT The study investigated the recognition of standardized
facial expressions of emotion (anger, fear, disgust, happiness, sadness,
surprise) at a perceptual level (experiment 1) and at a semantic level
(experiments 2 and 3) in children with autism (N = 20) and normally
developing children (N = 20). Results revealed that children with
autism were as able as controls to recognize all six emotions with
different intensity levels, and that they made the same type of errors.
These negative findings are discussed in relation to (1) previous data
showing specific impairment in autism in recognizing the belief-based
expression of surprise, (2) previous data showing specific impairment
in autism in recognizing fear, and (3) the convergence of findings that
individuals with autism, like patients with amygdala damage, pass a
basic emotions recognition test but fail to recognize more complex
stimuli involving the perception of faces or part of faces.
ADDRESS Correspondence should be addressed to: FULVIA CASTELLI, PhD,
California Institute of Technology, HSS 228–77, Pasadena, CA 91125, USA. e-mail:
fulvia@hss.caltech.edu
Introduction
Since Kanner’s (1943) original clinical account of children with autism first
described their profound lack of affective contact with other people, psy-
chologists have been evaluating the social and affective impairments in
autism. The empirical research on affective impairment of children and
adults with autism is wide and varied so that it is not surprising that the
findings are extremely mixed. Hypotheses of a general affective deficit
(Hobson, 1986a; 1986b; Hobson et al., 1988), and a selective emotion
recognition deficit (Baron-Cohen et al., 1999; Howard et al., 2000) have
been explored. In addition, the theory of mind (ToM) deficit account of
autism allowed investigations of selective emotion processing impairment
by contrasting recognition tasks that do and do not necessitate the ability
autism © 2005
SAGE Publications
and The National
Autistic Society
Vol 9(4) 428–449; 056082
1362-3613(200510)9:4
www.sagepublications.com
DOI: 10.1177/1362361305056082
KEYWORDS
amygdala;
autism;
emotion;
facial
expressions;
mentalizing
07 CASTELLI (bc-t) 22/8/05 2:20 pm Page 428
to represent mental states (Baron-Cohen et al., 1993). The present investi-
gations attempt to replicate and extend these findings with children with
autism.
A general affective deficit in children with autism has been investigated
by Hobson and colleagues using cross-modal matching tasks with vocal and
facial expressions of emotion (Hobson, 1986a; 1986b; Hobson et al.,
1988), and by Tantam et al. (1989) using naming and discriminating tasks
with facial expressions. By contrast, Ozonoff et al. (1990) demonstrated in
a literature review that children with autism do not show a general deficit
in emotion perception if compared with controls of the same language level.
Studies based on semi-naturalistic settings reported that children with
autism have difficulties in responding to an adult displaying negative
emotions (Bacon et al., 1998; Sigman et al., 1992) and positive emotions
(Kasari et al., 1993), but they can distinguish adults’ displays of anger, or
distress, from a neutral expression (Corona et al., 1998; Dissanayake et al.,
1996). While all these studies measure a lack of social referencing abilities
in children with autism, they also index difficulties in mentalizing (e.g.
understanding that other people may have different mental states from their
own) and executive functions (e.g. switching attention from a salient toy to
distant vocal or visual emotional cues). Recently, Grossman et al.s (2000)
study indicated that children and adolescents with autism have difficulties
in naming facial expressions of emotions that are incorrectly labelled (e.g.
happy face labelled either as ‘angry’ or as ‘orange’) as opposed to expressions
associated with correct labels (e.g. happy face labelled as ‘happy’). However,
the study also indicated that the autism group’s negative performance was
significantly correlated with difficulties in executive function tasks. Thus, the
question of whether children with autism have general emotion processing
impairments remains open to further investigations.
The neuroscience of emotion is beginning to be understood and neuro-
imaging studies have investigated differential neural responses to emotion-
ally relevant material in adults with high-functioning autism/Asperger
syndrome (HFA/AS). An fMRI study by Baron-Cohen et al. (1999) indicated
that adults with HFA/AS showed reduced activation of the inferior frontal
gyrus and no amygdala activation while understanding complex mental
states from people’s eyes compared to judging their gender. The authors
suggested that the amygdala is a key neural region that is abnormal in autism
(Baron-Cohen et al., 2000). The amygdala hypothesis has acquired further
support from structural imaging showing enlarged amygdala volume in
adults with HFA/AS (Abell et al., 1999; Howard et al., 2000). Howard et
al.s (2000) study also reported that the autism group showed a selective
impairment in fear recognition. This behavioural finding is in line with the
cognitive profile of patients with amygdala lesions (Adolphs et al., 1999;
CASTELLI: UNDERSTANDING EMOTIONS
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Fine and Blair, 2000). However, Adolphs et al. (2001) showed that adults
with autism performed better than amygdala patients on recognizing simple
emotions, including fear, but showed a severe impairment, like the amygdala
patients, in a task involving the judgement of trustworthiness and approach-
ability of a person by watching their faces only. It seems, therefore, that
Adolphs et al.s (2001) study indicates a dissociation in adults with autism
between intact perceptual processing of simple affective signals and
impaired retrieval of social knowledge based on facial cues. Thus, it seems
that the amygdala hypothesis of autism does not predict a selective impair-
ment in emotion recognition, but rather predicts more general difficulties
with complex social judgements, e.g. judgement of facial expressions’ trust-
worthiness and judgement of subtle mental states from eye gaze. This con-
clusion is compatible with the theory of mind deficit hypothesis of autism,
i.e. an impairment in the ability to understand and predict behaviour of
others on the basis of their mental states such as beliefs and intentions.
Baron-Cohen et al. (1993) adopted a methodological approach that
assumes that an affective deficit might be secondary to a theory of mind
impairment. They tested children with autism on the ability to recognize
expressions of happiness and sadness (i.e. reality-based emotions) versus
surprise (i.e. belief-based emotion). Results indicated that the children
with autism had more difficulties in understanding surprised expressions
than happy and sad faces. In a later study, Baron-Cohen et al. (1997a)
showed that adults with autism have more difficulties both in recognizing
feelings from the eye region than from the whole face, and in understand-
ing complex mental states (e.g. thoughtfulness, interest) than simple
emotions. Unlike children with autism, the adults with autism did not
show any difficulties in recognizing surprise. However, the recognition task
necessitated making a forced choice between two expressions which are
almost never confused, namely, surprise and happiness, and never between
the two most confusable expressions, namely, surprise and fear (Young
et al., 1997). More recently, Buitelaar et al. (1999) showed that children
with autism had no difficulties in recognizing either simple or complex
emotional expressions (surprise, shame, contempt and disgust were cate-
gorized by the authors as complex emotions, and happiness, sadness, anger,
and fear as simple emotions). Taken together, it seems that all these studies
on autism based on recognition of basic emotions – emotions character-
ized as rapid, failsafe responses to stimuli correlated with basic survival
needs (see Ekman, 1992) – have adopted different paradigms with differ-
ent sets of stimuli and different age groups, yielding some inconsistent data.
This area is in need of clarification by further experiments.
The aim of the present study is to investigate specific emotion recog-
nition processes in children with autism and normally developing children
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by using fine-grained visual stimuli and both perceptual and semantic tasks.
The paradigm adopted for the three experiments is based on computer-
generated stimuli derived from a standard set of pictures of the six basic
emotions, i.e. anger, disgust, fear, happiness, sadness and surprise (Calder
et al., 1996; Ekman and Friesen, 1976; Young et al., 1997).
According to the theory of mind hypothesis, it is predicted that children
with autism fail to recognize the belief-based emotion of surprise as
opposed to the reality-based emotions of anger, disgust, fear, happiness and
sadness. Unlike Baron-Cohen et al.s (1993) paradigm, which was based on
the recognition of the expressions of surprise, happiness and sadness, the
present study adopted a broader range of stimuli, including expressions that
are more difficult to recognize (i.e. fear, anger and disgust) than happiness
and sadness. In addition, the wide range of stimuli allows for monitoring
children’s performance in relation to the amygdala hypothesis of autism.
This hypothesis suggests a correlation between amygdala abnormality and
socioaffective impairments. Since the studies reported above (Adolphs
et al., 2001; Howard et al., 2000) were contradictory in their findings of
face recognition in adults with autism, the additional purpose of the present
study is to observe the performance of children with autism in relation to
the expression of fear. The study comprises three different experiments.
Experiment 1 (matching task) investigates the perceptual ability to discrim-
inate basic emotions. The challenge for the child is determined by the
difference in intensity level of the emotions displayed in the stimuli
expressions. The task requires a more abstract ability to extract the salient
invariance of the six emotional expressions across different intensity
degrees rather than matching fixed stereotypical features. The higher inten-
sity of the facial expression is expected to facilitate the matching task across
all emotions, whereas the expressions combining equal intensity of two
emotions (e.g. fear mixed with surprise) are expected to elicit responses
regularly distributed between the two possible emotions (e.g. fear and
surprise). However, evidence that normal adults tend to interpret combined
expressions in other different ways (e.g. surprise combined with happiness
seen more as happiness; sadness combined with disgust seen more as
sadness; anger combined with disgust seen more as disgust; fear combined
with surprise seen more as fear) has been reported in a study of patients
with brain lesions (Calder et al., 1996). It is therefore of interest to inves-
tigate whether children with autism show a preferential bias towards only
one target emotion within each combination pair.
Experiment 2 and 3 (naming task) investigate the semantic ability of children
with autism to discriminate emotions from a wide range of facial
expressions. Both the absence of a target and the heterogeneity of the test
stimuli control for the possibility that children’s performance relies on
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perceptual matching strategies without a clear understanding of the
meaning of the expression. The difference between the second and third
studies is that the latter combines the difficulty of the ‘fine-grained’ stimuli
of experiment 1 – facial expressions of emotions with different levels –
with the naming task of experiment 2.
In all three experiments it is expected that happiness is the easiest
emotion to recognize, and that the expressions of surprise and fear are the
most confused emotions, together with anger and disgust (Young et al.,
1997). Interestingly, Young et al.s (1997) study on adults’ categorical per-
ception of facial expressions indicated that the expression of surprise was
sometimes identified as fear, and disgust as anger, but when this happened,
it was usually because one adult subject consistently did this. It is therefore
of interest specifically to investigate whether the error pattern relative to
surprise and fear of children with autism differs from that of normally
developing children.
Experiment 1: discriminating facial expressions of emotions
with different intensity levels
Design
The experiment involves a 2 (group) 6 (emotion type) 3 (intensity
type) design. The emotion variable consists of ‘morphed’ facial expressions
of six emotions: anger, disgust, fear, happiness, sadness and surprise. The
intensity type consists of three intensity levels for each emotion: 90, 70 and
50 per cent. The task consists of matching each emotion stimulus with one
of the six displayed emotion targets (at 100 per cent intensity level).
1
Participants
These comprised a group of 20 children resident in a special school for
children with autism diagnosed formally with either autism or Asperger
syndrome prior to this study by independent clinicians, and a group of 20
normally developing children attending mainstream schools. Children with
autism were assessed using the VIQ score of the WISC (Wechsler Intelli-
gence Scale for children, third edition UK, 1992), whereas normally
developing children were assessed by the BPVS II test (British Picture Vocab-
ulary Scale, 1997) (Table 1). The choice between the two IQ tests was
entirely determined by the time available for testing each child. The test was
not used as a matching criterion, but rather to check that the control
subjects were at a developmentally normal language level. For matching
purposes, the group of children with autism was divided into subgroups
according to their verbal mental age (VMA) (6–7 years, 7.1–9 years,
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9.1–12 years, 12.1–14 years) and matched with the same number of
controls of the same CA in each subgroup, assuming that the chronologi-
cal age of the non-autistic children was roughly equivalent to their VMA.
However, the results were analysed relative to the performance of the whole
group.
Materials
The stimuli consisted of laminated cards (6.5 9 cm) representing
computer-manipulated photographic quality images of ‘morphed’ facial
expressions of an adult male model with different levels of emotion
intensity, obtained by blending two prototype expressions from the Ekman
and Friesen (1976) series, e.g. anger–happiness, with different proportions
(i.e. 90:10, 70:30, 50:50, 30:70, 10:90) (see Calder et al., 1996 for full
details of the ‘morphing’ technique). The target cards represented
expressions at 100 per cent intensity level (original prototypes) of six
different adult female models. There were four stimuli cards in each
emotion at level 90 per cent and 70 per cent, and two stimuli cards for each
pair of emotions at 50 per cent of intensity. For each subject there were two
sets of 30 stimuli cards each. The target cards were pasted on plastic boxes
sized 10 15 3 cm.
Procedure
Each child was tested individually in a separate room of the school. In the
training phase the experimenter showed each target emotion (female
model) to the child, asking her to say how she was feeling and to provide
an example of the displayed emotion (e.g. ‘Tell me about a time when you
were surprised’). If the child showed uncertainty, giving no example, the
experimenter provided a standard example (e.g. ‘I was surprised when I
opened my birthday present’). Each target emotion was then fixed on an
empty box in front of the child, making sure that she/he had a full view
of all targets. The display of the six targets was randomly arranged across
CASTELLI: UNDERSTANDING EMOTIONS
433
Table 1 Subjects’ verbal and performance ability scores, chronological age
(CA), and verbal and performance mental ages (MA)
Group Score CA (years) MA (years)
Mean (SD) Mean (SD) Mean (SD)
Autism WISC: 12.3 (2.3) Verbal = 9.2 (2.6)
(N = 20) Verbal IQ = 75.2 (16.9) Performance = 10.1 (3.2)
Performance IQ = 82.5 (21.3)
Control BPVS = 98.0 (18.3) 9.2 (2.4) Verbal = 9.11 (2.7)
(N = 20)
07 CASTELLI (bc-t) 22/8/05 2:20 pm Page 433
subjects. During the practice session the experimenter showed one at a time
the expressions of happiness or sadness at 90 per cent intensity level, asking
the child to place the card in the box with the similar expression. After
practice, the child started the experiment (two sessions with 30 cards
each). The cards were given one at a time, and the experimenter kept asking
‘Where does it go?’ until the routine was established. At the end of the first
session, the display of the targets on the boxes was randomly rearranged in
order to control for biases due to a preference of a particular position (e.g.
central positions versus lateral). At the end of the two sessions, the cards in
each box were counted and coded.
Results
The analysis of the score with emotions at 90 and 70 per cent intensity level
was carried out separately from the score with 50 per cent emotions (i.e.
stimuli eliciting two correct scores). The error patterns of each group were
also analysed to identify consistent mismatches between the expressions of
surprise and fear.
Analysis of correct performance with emotion stimuli at 90 and 70
per cent levels of intensity Non-parametric analyses were performed
on the groups’ correct matching of each emotion stimulus with its
emotion target, with emotions split into higher (90 per cent) and lower
(70 per cent) levels of intensity (Table 2). Group-comparison analyses
(Mann–Whitney tests) revealed no significant group effect on each
emotion beyond intensity level (anger, z = 0.68; disgust, z = 0.14; fear, z = 0.12;
happiness, z = 0.11; sadness, z = 0.66; surprise, z = 0), no intensity-level
effect beyond groups on each emotion at 90 per cent intensity (z scores for
anger, disgust, fear, happiness, sadness and surprise were all 0), and no
intensity-level effect beyond groups on each emotion at 70 per cent inten-
sity (again z scores for all emotions were 0). A Friedman test of all
emotions’ correct matching revealed a significant effect (chi-square = 32.6,
p < 0.0001). Planned comparisons revealed that, as predicted, the correct
score for happiness was the highest (F
(1)
= 14.5, p < 0.001), and the scores
for fear and surprise were the lowest (F
(1)
= 21, p < 0.0001). The results
failed to support the ToM prediction of a specific impairment in children
with autism in recognizing surprise. In addition, the data revealed no
specific difficulty with fear.
Analysis of correct performance with emotion at 50 per cent inten-
sity level Table 3 shows the score for the groups’ correct matches of the
emotions at 50 per cent intensity level, and Figure 1 shows the overall per-
formance. There are two correct responses for each of the six emotion
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CASTELLI: UNDERSTANDING EMOTIONS
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Table 2 Overall correct performance in discriminating emotions regardless of intensity level, and groups’ correct performance
in discriminating emotions at 90% and 70% intensity levels (max. score = 4)
Emotion Anger Disgust Fear Happiness Sadness Surprise Total
Mean 3.1 3.3 2.7 3.8 3.3 2.5 11
SD 1.1 1.1 1.2 0.6 1.6 1.4 11
Intensity level 90% 70% 90% 70% 90% 70% 90% 70% 90% 70% 90% 70% 90% 70%
Autism
Mean 3.2 3.1 3.3 3.2 3.0 2.6 3.7 3.8 3.3 2.9 2.8 2.4 3.2 3.0
SD 1.2 1.1 1.1 1.2 1.1 1.3 0.9 0.5 1.3 1.5 1.3 1.7 0.8 0.8
Control
Mean 2.9 3.1 3.5 3.3 2.5 2.9 4.0 3.8 3.5 3.5 2.4 2.7 3.1 3.2
SD 1.2 0.9 0.9 1.1 1.2 1.3 0.2 0.4 0.9 0.8 1.4 1.2 1.7 0.6
07 CASTELLI (bc-t) 22/8/05 2:20 pm Page 435
stimuli which represent the combination of two equally blended emotions.
The data analysed consist of two different target emotions for each emotion
stimulus at 50 per cent (e.g. the stimulus fear–surprise matched with fear,
or matched with surprise). A non-parametric analysis (Mann–Whitney
test) was performed on the groups’ correct matching and no significant
effect was revealed (z = 0.23). In addition, in order to investigate possible
group bias towards only one emotion target, a series of Mann–Whitney
tests were performed on each pair of correct matching (e.g. the autism
group matching more frequently surprise–fear with surprise rather than
with fear). No significant difference in a group preference towards only
one of the two correct emotion targets was revealed (anger–disgust
matched with anger, z = 1.4, or with disgust, z = 0.7; anger–happiness
AUTISM 9(4)
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Figure 1 Overall correct (N = 40) performance with emotions at 50% intensity
level: subject’s score (max. = 2) for each pair of facial expressions combining two
equally intense emotions (50% intensity level)
happiness
happiness
anger
surprise
sadness
sadness
fear
disgust
fear
surprise
disgust
anger
2
0
2
PAIRWISE EMOTIONS
)
2 = xam( erocs naeM
more frequent choice less frequent choice
Table 3 Groups’ correct performance in discriminating expressions blending
together two different emotions (at 50% intensity level) (max. score = 2)
Combination of Anger Anger Surprise Surprise Sadness Sadness
two emotions Disgust Happiness Happiness Fear Disgust Fear
(intensity level 50%)
Autism
Mean 1.8 1.6 1.7 1.6 2.0 1.7
SD 0.4 0.5 0.5 0.7 0.2 0.7
Control
Mean 1.6 1.6 1.9 1.9 2.0 1.7
SD 0.7 0.6 0.4 0.3 0.2 0.6
07 CASTELLI (bc-t) 22/8/05 2:20 pm Page 436
matched with anger, z = 1.4, or with happiness, z = 1.6; surprise–
happiness matched with surprise, z = 0.66, or with happiness, z = 0.16;
surprise–fear matched with surprise, z = 0.38, or with fear, z = 0.76;
sadness–disgust matched with sadness, z = 0.74, or with disgust, z = 0.49;
sadness–fear matched with sadness, z = 0.71, or with fear, z = 0.62).
Analysis of groups’ error pattern in matching emotions regardless of
intensity level Since possible confusions between emotions are also
likely to occur with morphed expressions matching emotions at 90 and
70 per cent intensity levels, a further analysis was carried out on perform-
ance relative to the incorrect matching between emotion stimuli and
emotion targets (with the exclusion of expressions morphed at 50 per
cent) regardless of intensity level. Non-parametric group-comparison tests
(Mann–Whitney) were carried out separately on each type of error made
with each emotion stimulus. The results indicated no differential error
pattern in the two groups. Non-parametric paired comparisons (Wilcoxon
tests) indicated that the most frequent errors were due to confusion
between fear and surprise (Figure 2).
2
Experiment 2: naming facial expression of emotions with
natural intensity
Design
The experiment involves a 2 (group) 7 (expression type) design. The
expression type independent variable consists of the six basic emotions and
one neutral expression. The experimental task consists of naming each
single facial expression with one emotion label, or the neutral expression
with a ‘non-emotion’ label. The dependent variable is the number of correct
responses.
3
Subjects
The same groups of participants were tested as in experiment 1.
Materials
The stimuli consisted of laminated cards (9 11.5 cm) representing photo-
graphic quality images of facial expressions derived from Ekman and Friesen
(1976). The pictures represented the facial expressions of 10 different
models (four adult males and six adult females) each displaying the emotions
with natural intensity (i.e. 100 per cent intensity level). The cards were
arranged randomly into two decks of 35 cards, each composed of pictures
of seven expressions displayed by five models (three females and two males).
437
DUARTE ET AL.: STRESS IN MOTHERS
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Procedure
Experiment 2 was always carried out after experiment 1, on the same day.
Subjects were asked to name each expression (e.g. ‘How is she feeling?’),
and were informed that there was an additional expression (i.e. neutral) that
showed no particular emotion. If the child provided a different but correct
label for the emotion target (e.g. ‘smiling’ instead of ‘happy’; ‘crying’ or
‘upset’ for ‘sad’; ‘sick’ instead of disgusted; ‘annoyed’ or ‘cross’ instead of
‘angry’) the experimenter accepted them as substitutes, and recorded them
for each subject. Definitions pertaining to non-basic emotional states were
classified as unclear (e.g. ‘grumpy’,‘disappointed’,‘bored’,‘confused’). The
pre-naming session was followed by the session during which the child was
presented with one card after the other and asked to say how the person in
the picture was feeling until routine was established. Each answer was
recorded and coded as ‘correct’, ‘incorrect’ or ‘unclear’.
Results
An initial analysis of the correct naming score was carried out, followed by
an additional analysis of the erroneous labelling performance, with the aim
of exploring groups’ consistent errors across emotions.
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Figure 2 Overall performance in matching each emotion regardless of intensity
level (N = 40)
fearanger disgust surprise sadness happiness
8
6
4
2
0
2
4
6
8
correct matching = upper portion of the bar
incorrect matching = lower portion of then bar
anger disgust fear happiness sadness surprise
mean score (max = 6)
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Analysis of correct naming of emotions Group-comparison analyses
(Mann–Whitney tests) were performed on the groups’ correct naming of
each expression stimulus with its emotion label (Table 4). Results revealed
no significant group effect (anger, z = 0.45; disgust, z = 1.4; fear, z = 0.2;
happiness, z = 0.3; sadness, z = 2.3; surprise, z = 0.84; neutral, z = 0.45).
A Friedman test on all emotions’ correct naming score revealed a signifi-
cant effect (chi-square = 89.8, p < 0.0001). As predicted, all children found
the expression of happiness the easiest emotion to name (planned com-
parison, F
(1)
= 72, p > 0.0001). Figure 3 shows the correct score for each
emotion in order of difficulty: a series of Wilcoxon tests revealed that
children named surprise correctly more often than fear (z = 3, p < 0.003)
and named correctly equally often fear and disgust (z = 1.8, n.s.). They also
named correctly equally often surprise and anger (z = 0.5, n.s.), neutral
CASTELLI: UNDERSTANDING EMOTIONS
439
Table 4 Overall correct score and groups’ correct score for naming neutral and
emotional expressions (max. score = 10)
Target label
Neutral Anger Disgust Fear Happiness Sadness Surprise Total
Autism
Mean 7.8 8.0 5.7 5.9 9.9 7.7 7.6 7.5
SD 2.4 1.5 3.3 2.4 0.4 1.9 2.6 2.6
Control
Mean 6.7 7.7 4.4 6.0 9.9 6.2 7.4 6.9
SD 3.6 1.3 2.1 2.8 0.3 2.4 2.0 2.8
Total
Mean 7.2 7.8 5.0 5.9 9.9 6.9 7.5 //
SD 3.1 1.4 2.8 2.6 0.3 2.3 2.3 //
Figure 3 Overall correct score for naming each emotion in order of difficulty
(N = 40)
9.9 7.8 7.5
7.2
6.9
5
0
2
4
6
8
10
12
1
E m o t i o n
happiness anger surprise neutral sadness fear disgust
5
.
9
mean score
(max = 10)
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and sadness (z = 0.5, n.s.), and neutral and anger (z = 1.2, n.s.). They found
it easier to name anger than sadness (z = 1.9, p < 0.05). This experiment
did not indicate any particular verbal difficulty of children with autism with
labelling the emotional expression of either surprise or fear.
Analysis of error patterns in naming emotions Non-parametric
group-comparison tests (Mann–Whitney) were carried out separately on
each type of error made with each expression stimulus. In line with the
results of the matching task of experiment 1, there were no differences
between the two groups in the naming task. A series of non-parametric
paired comparisons (Wilcoxon test) showed that the most frequent
mistakes were to say that the expression of fear was a surprised face, and
that the expression of disgust was an angry face.
4
This result is in line with
Young et al.s (1997) findings with healthy adults who found the pairs
‘fear–surprise’ and ‘disgust–anger’ equally confusing.
Experiment 3: naming facial expressions of emotions with
different intensity levels
The aim of this third part of the study was to compare the ability of children
with autism and controls to name emotions using more difficult stimuli
than in the previous experiment.
Design
The experiment involves a 2 (group) 6 (emotion type) 2 (intensity
type) design. The emotion type consists of the same six basic emotions as
the discriminating task of experiment 1. The intensity type consists in only
two emotion levels of intensity (90 per cent and 70 per cent). The exper-
imental task consists in naming each emotional expression with one of the
six basic emotions labels.
Subjects
Participants of this study were the same as in experiments 1 and 2, except
that the number of children with autism was reduced to 19.
Materials
The stimulus cards were the same as that for the matching task (experiment
1), with the exclusion of the facial expressions that combined emotions at
50 per cent intensity. The cards were assembled in two blocks of 24 cards
(two stimuli at each level for six emotions). The presentation order of the
two blocks was counterbalanced across subjects.
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Procedure
Children performed this experiment immediately after the naming task of
experiment 2 and therefore there was no need to repeat the pre-labelling
procedure. Children were invited to take a pause between the two experi-
ments and then were simply asked to do the same as in the previous naming
task. Each answer was recorded and coded as ‘correct’,‘incorrect’ or ‘unclear’.
Results
As in the two previous experiments, the data were analysed relative to the
groups’ correct and incorrect performance.
Analysis of correct naming emotions with different levels of intensity
Group-comparison analyses (Mann–Whitney tests) were performed on the
groups’ correct naming of each expression stimulus with its emotion label
with emotions split into higher (90 per cent) and lower (70 per cent) levels
of intensity (Table 5). Results revealed no significant group effect (anger,
z = 0.5; disgust, z = 0.5; fear, z = 0; happiness, z = 0.1; sadness, z = 0.6;
surprise, z = 0.7). A Friedman test of all emotions’ correct naming (com-
bining the two levels of intensity) revealed a significant effect (chi-square
= 37.8, p < 0.0001). Figure 4 shows the correct label for each emotion
expression in order of difficulty, regardless of intensity level. As predicted,
all children performed at ceiling in naming the expression of happiness
(happiness compared to all other emotions, planned comparison, F
(1)
=
25.5, p < 0.0001). Again, as in the previous naming task, children with
autism did not perform differently to the controls, indicating that neither
the expression of surprise nor the expression of fear constitutes a verbal
obstacle at any level of intensity for both groups.
Analysis of errors pattern in naming emotions with different levels
of intensity Non-parametric group-comparison tests (Mann–Whitney)
were carried out separately on each type of naming errors with each
emotion stimulus. The results indicated no differential errors patterns in the
two groups. Additional series of non-parametric analyses (paired compari-
son, Wilcoxon tests) were carried out in order to investigate the type of
errors occurring most frequently in the overall sample. The analyses
revealed that disgust was commonly mistaken and named either unclearly
or as ‘sad’ or as ‘angry’.
5
As in the previous tasks, children also made sig-
nificantly more errors of saying that fear was a surprised face and surprise
was a fearful face.
6
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07 CASTELLI (bc-t) 22/8/05 2:20 pm Page 441
AUTISM 9(4)
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Table 5 Overall sample and groups’ correct score for naming emotions with different levels of intensity (max. score = 4)
Emotion Anger Disgust Fear Happiness Sadness Surprise Total
Mean (max. = 8) 6.6 4.7 5.4 7.9 6.6 6.2 11
SD 1.8 3.4 2.7 0.2 2.6 2.4 11
Intensity level 90% 70% 90% 70% 90% 70% 90% 70% 90% 70% 90% 70% 90% 70%
Autism
Mean (max. = 4) 3.5 3.3 2.3 2.1 2.7 2.7 4.0 4.0 3.2 3.0 3.2 3.0 3.1 3.0
SD 0.9 0.9 1.8 1.8 1.6 1.5 0.0 0.2 1.6 1.5 1.2 1.1 1.4 1.4
Control
Mean (max. = 4) 3.4 3.2 2.6 2.5 2.8 2.5 4.0 4.0 3.5 3.6 3.3 2.9 3.3 3.1
SD 0.9 1.0 1.8 1.6 1.5 1.5 0.0 0.2 1.1 1.0 1.5 1.4 1.3 1.3
07 CASTELLI (bc-t) 22/8/05 2:20 pm Page 442
Discussion
The present study sought to investigate both the perceptual and semantic
abilities of children with autism and normally developing children in
recognizing basic emotional states of others through their facial expressions.
The results revealed that children with autism were as able as controls to
recognize all six basic emotions from facial expressions. This was shown
not only when they were required to match pictures of emotional
expressions with different intensity levels (i.e. ‘morphed’ expressions with
90, 70 and 50 per cent intensity), but also when they were asked to provide
a label for emotional expressions with natural intensity (prototype
expressions, with 100 per cent intensity level).
The findings of the present study contrast with at least two previous
studies indicating specific emotion recognition impairment in autism.
Baron-Cohen et al. (1993) found a specific impairment in autism in recog-
nizing the belief-based expression of surprise as opposed to the reality-
based expressions of happiness and sadness. Howard et al.s (2000) study
showed a specific impairment in recognizing the expression of fear.
Some differences between the Baron-Cohen et al. research and the
present study have to be taken into account. First, in the Baron-Cohen study
children with autism had a considerably lower verbal mental age (CA mean
12.6 years,VMA 5.3 years) than those in the present study (CA mean 12.3
years, VMA 9.2 years), and thus may have been less familiar with surprise
than happiness and sadness. In fact, typically developing 5-year-olds find
CASTELLI: UNDERSTANDING EMOTIONS
443
Figure 4 Overall correct score for naming each emotion in order of difficulty
regardless of intensity level (N = 40)
Note: Nonparametric paired comparisons (Wilcoxon tests, p < 0.0025 corrected for multiple
comparisons) revealed that the scores for surprise and fear did not differ significantly (z = 1.5,
p = not sig.) as well as fear and disgust (z = 1, p = not sig.). The equal scores for anger and sadness
were both higher than fear (z = 2.3, p < 0.05; z = 2.7, p < 0.01, respectively) and disgust (z = 3, p < 0.01;
z = 2.4, p < 0.05; respectively). Finally, the comparison between the scores of surprise and disgust
revealed the latter as the most difficult expression to name (z = 2.1, p < 0.05).
7.9
6.6
6.6
3.1
5.4 4.7
0
1
2
3
4
5
6
7
8
)8=xam( erocs naem
Happiness Anger Sadness Surprise Fear Disgust
07 CASTELLI (bc-t) 22/8/05 2:20 pm Page 443
surprise the most difficult emotion to recognize, tending to confuse it with
happiness while at the same time associating it with the semantic category
of ‘feeling bad’ (Kestenbaum, 1992). Second, the stimuli used by Baron-
Cohen et al. were also different: they used drawings and pictures of indi-
viduals showing facial expressions, whereas the present study adopted
Ekman and Friesen’s (1976) standardized series of facial affect. It is possible
that the standardized expression of surprise is easier to recognize than
drawings and pictures. Third, the Baron-Cohen study focused only on a
limited range of emotions, i.e. happiness, sadness and surprise, rather than
all six basic emotions including fear, which has been found highly confus-
able with surprise. It might be that an effect of featural complexity accounts
for the Baron-Cohen result. In fact, the expression of surprise involves
coding both eyes and mouth whereas happy and sad expressions can be
coded simply by reference to the mouth alone. The wide range of
expressions investigated in the present study might have contributed to
eliminate this effect.
Another point of discussion concerns the theoretical distinction
between belief-based emotions and reality-based emotions upon which the
Baron-Cohen et al. study and the present study based their prediction. The
expression of surprise can be primarily characterized as a ‘basic emotion’,
in the sense of a rapid reaction response to certain events. It can also be
considered an ‘approach emotion’ (Davidson, 1992), which is associated
with a call for further information. In the latter case, it would be of interest
to explore the ability of individuals with autism to associate the expression
of surprise with an appropriate response behaviour.
A final issue regards the clinical samples used in both studies, which
were taken from children based in specialized schools. Given the hetero-
geneity of individuals diagnosed with high-functioning autism/Asperger
syndrome it is an open question how far it is possible to generalize from
these results to individuals with autism more generally. Future research on
emotion recognition abilities in autism needs to employ much larger
samples of individuals, with diagnosis ascertained using standardized
instruments.
One purpose of the present study was to assess the performance of
children with autism with regard to the hypothesis that amygdala abnor-
mality could contribute to social and emotional processing deficit in autism
(Baron-Cohen et al., 1999; 2000). In particular, Howard et al.s (2000)
study showed concomitant evidence of amygdala abnormality and selective
fear recognition impairment in high-functioning individuals with autism.
However, children in the present study showed no impairment in fear
recognition. This finding is unlikely to be attributable to the type of test
materials used since these have been shown to be sensitive enough to reveal
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selective emotion impairments in different clinical populations other than
individuals with autism (Adolphs et al., 1999; Blair and Coles, 2000; Calder
et al., 1996; Stevens et al., 2001). Again it is possible that diagnostic
heterogeneity could explain the differing results in this and the Howard
et al. study. A replication of these findings, along with a description of each
subject’s pattern of performance, is clearly needed.
A convergence of findings also show that individuals with autism, as
well as patients with amygdala damage, can pass tests of basic emotions
recognition but fail to recognize more complex stimuli, i.e. judging trust-
worthiness and approachability of people from their faces (Adolphs et al.,
2001), judging mental states from people’s eye gaze (Baron-Cohen et al.,
1997b) or identifying emotions by watching people’s face associated with
inappropriate labels (Grossman et al., 2000). Interestingly, both the trust-
worthiness and approachability task and the eye task rely on the ability to
understand the mental states of others, and to predict their behaviour on
the basis of their appearance. It is likely, therefore, that a mentalizing
deficit accounts for these results. In conclusion, both the role of the
amygdala within the distributed neural system involving mentalizing
(Castelli et al. 2000; 2002; Fletcher et al., 1995; Gallagher et al., 2000)
and the mentalizing ability of patients with amygdala damage need to be
further investigated.
Although the theory of mind hypothesis was not supported by the
present findings on basic emotion recognition, other studies have found
impairments on tasks that tap mentalizing processing. It is plausible that
individuals with autism used compensatory strategies to bypass their basic
deficit in emotion recognition. Everyday exposure to such basic stimuli is
a constant source of information for learning the association of facial
expressions and feelings or needs. It is also common for adults to provide
reinforcement cues to children in order to decode emotional signals (e.g.
a parent pretending to be crying because she wants the child to understand
he did something upsetting). On the other hand, it is possible that indi-
viduals with autism have no impairment in recognizing those emotion
expressions that have evolved with adaptive functions, but have difficulties
in linking the perceptual level of emotion recognition with the higher level
of understanding the social meaning of different expressions. In this sense,
it is important that research on basic emotion recognition should be
oriented towards investigating very young children, and possibly with
stimuli that bypass compensatory strategies by controlling for both execu-
tive function deficit and mentalizing deficit, which are theoretically distinct
from the process to be investigated.
In conclusion, a final note relative to children’s performance in both
groups. The results showed that, consistent with both cross-cultural data
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07 CASTELLI (bc-t) 22/8/05 2:20 pm Page 445
(Ekman, 1992) and adult data (Young et al., 1997), all children found both
surprise and fear the two most difficult expressions to discriminate at a per-
ceptual level. The close relationship between these two expressions was
noted early by Darwin (1872/1998) who considered these emotions as
part of the same continuum, pointing out that fear is often preceded by and
sometimes mixed with surprise. Data from children’s performance with the
expressions combining 50 per cent level of surprise and fear showed no
particular preferences towards one expression or the other, indicating that
the two expressions display ambiguous/unambiguous features to the same
extent. Confusion cannot be attributed to the ambiguity of the 50 per cent
stimuli in general, since when children had to decide to match the 50 per
cent expression of surprise–happiness, they chose more often the expression
of happiness, as expected on the basis of the categorical perception study
by Etcoff and Magee (1992) and on the results from Calder et al.s (1996)
study. Overall, the close resemblance between surprise and fear confused
the children with autism no more than the controls.
Notes
1 The dependent variable is the number of correct matches of emotion stimuli with
the emotion targets placed on top of the boxes. The types of errors are defined
henceforth as ‘name of emotion stimuli’ in ‘name of emotion target’ (e.g. ‘fear in
surprise’ means that the card representing the expression of fear has been
incorrectly matched with surprise). Each emotion stimulus at 90 and 70 per cent
intensity level has one correct emotion target to be matched with, whereas each
emotion stimulus with 50 per cent intensity level, which represents the
combination of two different emotions, has two equally correct emotion targets.
2 Fear in surprise (mean = 1.5, SD = 1.6) versus fear in sadness, z = 2.7, p = 0.006;
versus fear in happiness, z = 3.9, p < 0.0025; versus fear in disgust, z = 3.6,
p < 0.0025; versus fear in anger, z = 3.5, p < 0.0025. Surprise in fear (mean =
2.2, SD = 2.4) versus surprise in anger, z = 3.9, p < 0.0025; versus surprise in
disgust, z = 4.0, p < 0.0025; versus surprise in happiness, z = 4.2, p < 0.0025;
versus surprise in sadness, z = 3.7, p < 0.0025 (all p values corrected for multiple
comparisons).
3 Similarly to experiment 1, the stimulus cards that subjects have to name are
defined as ‘expression stimuli’, whereas the labels they provide are defined as
‘expression label’. The types of error are defined henceforth as ‘stimulus labelled as
target’ (e.g. ‘fear as surprised’ indicates that the expression of fear is labelled
incorrectly as surprised).
4 Fear as surprised (mean = 2.5, SD = 1.9) versus fear as neutral, z = 5, p < 0.0001;
versus fear as angry, z = 3.8, p = 0.0002; versus fear as disgusted, z = 5,
p < 0.0001; versus fear as happy, z = 4.3, p < 0.0001; versus fear as sad, z = 4.7,
p < 0.0001; versus fear as unclear, z = 5, p < 0.0001. In addition, the other most
frequent error was to say that the expression of disgust was an angry face, i.e.
disgust as angry (mean = 3.4; SD = 2) versus disgust as neutral, z = 5.2,
p < 0.0001; versus disgust as fearful, z = 5.2, p < 0.0001; versus disgust as happy,
z = 5.2, p < 0.0001; versus disgust as sad, z = 5.2, p < 0.0001; versus disgust as
AUTISM 9(4)
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surprised, z = 5, p < 0.0001; versus disgust as unclear, z = 5.2, p < 0.0001.
(Results reported with p value corrected for multiple comparisons, p < 0.002.)
5 Disgust as angry = disgust as unclear, z = 0.06, p = n.s.; disgust as sad = disgust as
angry, z = 1.6, p = n.s.; disgust as sad = disgust as unclear, z = 1.5, p = n.s. (Results
reported corrected for multiple comparisons, p < 0.0025.)
6 Fear as surprised versus fear as angry, z = 3.3, p < 0.0025; fear as disgusted,
z = 3.4, p < 0.0025; fear as happy, z = 3.3, p < 0.0025; fear as sad, z = 2.8,
p < 0.0025; fear as unclear, z = 3.6, p < 0.0025. Surprise named as a fearful face
versus surprise as angry, z = 3.2, p < 0.0025; surprise as disgusted, z = 3.1,
p < 0.0025; surprise as happy, z = 2.2, p < 0.0025; surprise as sad, z = 3.7,
p < 0.0025; surprise as unclear, z = 2.7, p < 0.0025. (Results reported corrected
for multiple comparisons, p < 0.0025.)
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Emotion recognition skills and the ability to understand the mental states of others are crucial for normal social functioning. Conversely, delays and impairments in these processes can have a profound impact on capability to engage in, maintain, and effectively regulate social interactions. Therefore, this study aimed to compare the performance of 42 autistic children (Mage = 8.25 years, SD = 2.22), 45 unaffected siblings (Mage = 8.65 years, SD = 2.40), and 41 typically developing (TD) controls (Mage = 8.56 years, SD = 2.35) on the Affect Recognition (AR) and Theory of Mind (TOM) subtests of the Developmental Neuropsychological Assessment Battery. There were no significant differences between siblings and TD controls. Autistic children showed significantly poorer performance on AR when compared to TD controls and on TOM when compared to both TD controls and unaffected siblings. An additional comparison of ASD, unaffected sibling and TD control subsamples, matched on full-scale IQ, revealed no group differences for either AR or TOM. AR and TOM processes have received less research attention in siblings of autistic children and remain less well characterized. Therefore, despite limitations, findings reported here contribute to our growing understanding of AR and TOM abilities in siblings of autistic children and highlight important future research directions.
... As such, differences in neural response between ASD and TD groups may provide insight into distinct processing patterns. Task performance data on the active matching task align with prior reports of non-significant differences (ASD vs. TD) in behavioral performance on face tasks (Castelli, 2016). It should be noted that neither task requires the overt identification or verbal labeling of emotions; participants are asked to match the two faces that "feel the same way" or to simply "watch the faces" and these instructions do not necessitate act of recognition. ...
... Despite general accordance that emotional-face-processing is a domain of significant challenge in ASDs, no consensus has been reached regarding the extent of these deficits (Lozier et al., 2014). In fact, several studies reported no differences in accuracy or reaction time when ASD and TD participants perform emotional-face tasks (Castelli, 2016;Tracy et al., 2010) while others suggest that only a subset of the ASD population experience difficulty with facial emotion (Nuske et al., 2013). These disparate findings have been attributed to a variety of participant and experiment-related factors including demographic characteristics (e.g., age, sex), intellectual capacity, comorbid conditions, and task demands (Nuske et al., 2013). ...
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Few studies have used task-based functional connectivity (FC) magnetic resonance imaging to examine emotion-processing during the critical neurodevelopmental period of adolescence in Autism Spectrum Disorders (ASDs). Moreover, task designs with pervasive confounds (e.g., lack of appropriate controls) persist because they activate neural circuits of interest reliably. As an alternative approach to “subtracting” activity from putative control conditions, we propose examining FC across an entire task run. By pivoting our analysis and interpretation of existing paradigms we may better understand neural response to non-focal instances of socially-relevant stimuli that approximate real-world experiences more closely. Hence, using two well-established affective tasks (face-viewing, face-matching) with diverging social-cognitive demands, we investigated extrinsic FC from amygdala (AMG) and fusiform gyrus (FG) seeds in typically-developing (TD; N = 17) and ASD (N = 17) male adolescents (10–18 yo) and clinical correlations (Social Communication Questionnaire; SCQ) of group FC differences. Participant data (4TD, 6ASD) with excessive head-motion were excluded from final analysis. Direct between-group comparisons revealed significant differences between groups for neural response but not task performance (accuracy, reaction time). During face-viewing, we found greater FC from AMG and FG seeds for ASD participants (ASD > TD) in regions involved in the Default Mode and Fronto-Parietal Task Control Networks. During face-matching, we found greater FC from AMG and FG seeds for TD participants (TD > ASD), in regions associated with the Salience, Dorsal Attention, and Somatosensory Networks. SCQ scores correlated positively with regions with group differences on the face-viewing task and negatively with regions identified for the face-matching task. Task-dependent group differences in FC despite comparable behavioral performance suggest that high-functioning ASD may wield compensatory strategies; clinically-correlated FC patterns may associate with differential task-demands, ecological validity, and context-dependent processing. Employing this novel approach may further the development of targeted therapeutic interventions informed by individual differences in the highly heterogeneous ASD population.
... Difficulty in recognizing and understanding emotional expressions through multiple cues is one of the fundamental social impairments in the ASD population [150,151]. Children with ASD often show an atypical emotional development from TD children, manifested as a lack of empathy with other people and failure to react emotionally to other people's states of mind [141]. Learning emotion recognition in VEs could remove such emotional barriers and obstacles for the ASD population, as VR training programs have been proved to be particularly helpful for them regarding emotion recognition improvement. ...
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The worldwide rising trend of autism spectrum disorder (ASD) calls for innovative and efficacious techniques for assessment and treatment. Virtual reality (VR) technology gains support from rehabilitation and pedagogical theories and offers a variety of capabilities in educational and interventional contexts with affordable products. VR is attracting increasing attention in the medical and healthcare industry, as it provides fully interactive three-dimensional simulations of real-world settings and social situations, which are particularly suitable for cognitive and performance training, including social and interaction skills. This review article offers a summary of current perspectives and evidence-based VR applications for children with ASD, with a primary focus on social communication, including social functioning, emotion recognition, and speech and language. Technology- and design-related limitations, as well as disputes over the application of VR to autism research and therapy, are discussed, and future directions of this emerging field are highlighted with regards to application expansion and improvement, technology enhancement, linguistic diversity, and the development of theoretical models and brain-based research.
... This strategy is divided into baseline, intervention and maintenance phases. This model is widely used in medical, psychological and biological research, and especially for individuals with ASD as reported in [2,[13][14][15]38]. ...
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Among the main characteristics of an individual with autism spectrum disorder are repetitive behavioral patterns, deficiencies in social interaction and both verbal and nonverbal communication present since childhood. The ability to recognize mental states from facial expressions plays a vital role in social interaction and interpersonal communication. In recent years, several studies have been carried out with the aim of motivating individuals to use computer technologies to learn emotions in order to improve social interactions. In this paper, a game that can support the development of emotional and social skills is presented for people with autism spectrum disorder. Our game allows people to develop the ability to recognize and express basic emotions: joy, sadness, anger, disgust, surprise and fear. Experiments were performed on a public domain image database and with a group of individuals from an educational institution, in order to evaluate the performance of the proposed tool. The results showed that the use of our approach improved these capabilities in individuals with autism spectrum disorder.
... This begs questions about ecological validity because in real-world social communication, the lexical and the prosodic channels are intricately linked in natural speech. Similarly, individuals with ASD are known to have problems processing emotional facial expressions (Black et al., 2017;Castelli, 2005), and they also experience difficulties in body language such as pantomime execution/imitation and recognition (Fabbri-Destro et al., 2019;Fridenson-Hayo et al., 2016). However, within the visual modality, there is also a scarcity of multichannel studies examining ASD participants' abilities to handle multiple visual emotional cues simultaneously. ...
Article
Purpose Numerous studies have identified individuals with autism spectrum disorder (ASD) with deficits in unichannel emotion perception and multisensory integration. However, only limited research is available on multichannel emotion perception in ASD. The purpose of this review was to seek conceptual clarification, identify knowledge gaps, and suggest directions for future research. Method We conducted a scoping review of the literature published between 1989 and 2021, following the 2005 framework of Arksey and O'Malley. Data relating to study characteristics, task characteristics, participant information, and key findings on multichannel processing of emotion in ASD were extracted for the review. Results Discrepancies were identified regarding multichannel emotion perception deficits, which are related to participant age, developmental level, and task demand. Findings are largely consistent regarding the facilitation and compensation of congruent multichannel emotional cues and the interference and disruption of incongruent signals. Unlike controls, ASD individuals demonstrate an overreliance on semantics rather than prosody to decode multichannel emotion. Conclusions The existing literature on multichannel emotion perception in ASD is limited, dispersed, and disassociated, focusing on a variety of topics with a wide range of methodologies. Further research is necessary to quantitatively examine the impact of methodological choice on performance outcomes. An integrated framework of emotion, language, and cognition is needed to examine the mutual influences between emotion and language as well as the cross-linguistic and cross-cultural differences. Supplemental Material https://doi.org/10.23641/asha.19386176
... While some studies find no differences in the ability of individuals with ASD to recognize others' basic emotional expressions (e.g., Castelli, 2005), literature reviews and metaanalyses have generally reported deficits in facial emotion recognition in individuals with ASD compared to controls (see Harms et al., 2010;Uljarevic & Hamilton, 2013). In one such meta-analysis of facial emotion recognition, Lozier and colleagues (2014) found that individuals with ASD show facial emotion recognition deficits across different expres sions, and that the magnitude of the observed deficits increases with age, but is not ac counted for by cognitive ability. ...
Chapter
From the earliest descriptions, children with autism have been described as presenting with differences in emotional expression and regulation. However, autism spectrum disorder (ASD) diagnostic criteria do not include these emotional differences. More recently, research has begun to investigate the emotional impairments observed in individuals with ASD across the life span, including how it contributes to a range of poor outcomes. Atypical emotion development can be used to differentiate those at risk for ASD from typically developing children. Research has also identified differences in emotional awareness, expression, recognition, and regulation among children and adults with ASD. Priority areas for future research, such as longitudinal studies of emotion dysregulation beginning in early childhood; development of interventions targeting emotion awareness, recognition, and expression; and study and treatment of emotion dysregulation among adults, will be discussed.
... On the behavioral level, individuals with ASD have shown altered emotion recognition of positive and negative facial expressions with larger impairments in processing fear, anger, sadness, and disgust emotions as compared to happy emotions (Wong et al., 2008). However, in some previous studies there were no performance differences between individuals with ASD and typically developing (TD) children in facial emotion recognition tasks (Castelli, 2005;Jones et al., 2011;Fink et al., 2014). ...
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According to the shared signal hypothesis (SSH) the impact of facial expressions on emotion processing partially depends on whether the gaze is directed toward or away from the observer. In autism spectrum disorder (ASD) several aspects of face processing have been found to be atypical, including attention to eye gaze and the identification of emotional expressions. However, there is little research on how gaze direction affects emotional expression processing in typically developing (TD) individuals and in those with ASD. This question is investigated here in two multimodal experiments. Experiment 1 required processing eye gaze direction while faces differed in emotional expression. Forty-seven children (aged 9-12 years) participated. Their Autism Diagnostic Observation Schedule (ADOS) scores ranged from 0 to 6 in the experiment. Event-related potentials (ERPs) were sensitive to gaze direction and emotion, but emotion processing did not depend on gaze direction. However, for angry faces the gaze direction effect on the N170 amplitude, as typically observed in TD individuals, diminished with increasing ADOS score. For neutral expressions this correlation was not significant. Experiment 2 required explicit emotion classifications in a facial emotion composite task while eye gaze was manipulated incidentally. A group of 22 children with ASD was compared to a propensity score-matched group of TD children (mean age = 13 years). The same comparison was carried out for a subgroup of nine children with ASD who were less trained in social cognition, according to clinician's report. The ASD group performed overall worse in emotion recognition than the TD group, independently of emotion or gaze direction. However, for disgust expressions, eye tracking data revealed that TD children fixated relatively longer on the eyes of the stimulus face with a direct gaze as compared with averted gaze. In children with ASD we observed no such modulation of fixation behavior as a function of gaze direction. Frontiers in Human Neuroscience | www.frontiersin.org 1 February 2022 | Volume 16 | Article 733852 Bagherzadeh-Azbari et al. Eyegaze, Facial Expressions, and Autism Overall, the present findings from ERPs and eye tracking confirm the hypothesis of an impaired sensitivity to gaze direction in children with ASD or elevated autistic traits, at least for specific emotions. Therefore, we conclude that multimodal investigations of the interaction between emotional processing and stimulus gaze direction are promising to understand the characteristics of individuals differing along the autism trait dimension.
... This strategy is divided into baseline, intervention, and maintenance phases. This assessment model is widely used in medical and psychological research and for individuals with ASD, as reported in [34,35,[59][60][61]. ...
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Autism spectrum disorder refers to a neurodevelopmental disorders characterized by repetitive behavior patterns, impaired social interaction, and impaired verbal and nonverbal communication. The ability to recognize mental states from facial expressions plays an important role in both social interaction and interpersonal communication. Thus, in recent years, several proposals have been presented, aiming to contribute to the improvement of emotional skills in order to improve social interaction. In this paper, a game is presented to support the development of emotional skills in people with autism spectrum disorder. The software used helps to develop the ability to recognize and express six basic emotions: joy, sadness, anger, disgust, surprise, and fear. Based on the theory of facial action coding systems and digital image processing techniques, it is possible to detect facial expressions and classify them into one of the six basic emotions. Experiments were performed using four public domain image databases (CK+, FER2013, RAF-DB, and MMI) and a group of children with autism spectrum disorder for evaluating the existing emotional skills. The results showed that the proposed software contributed to improvement of the skills of detection and recognition of the basic emotions in individuals with autism spectrum disorder.
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Summary Ten able adults with autism or Asperger syndrome and 10 normal volunteers were PET scanned while watching animated sequences. The animations depicted two triangles moving about on a screen in three different conditions: moving randomly, moving in a goal-directed fashion (chasing, fighting), and moving interactively with implied intentions (coaxing, tricking). The last condition frequently elicited descriptions in terms of mental states that viewers attributed to the triangles (mentalizing). The autism group gave fewer and less accurate descriptions of these latter animations, but equally accurate descriptions of the other animations compared with controls. While viewing animations that elicited mentalizing, in contrast to randomly moving shapes, the normal group showed increased activation in a previously identified mentalizing network (medial prefrontal cortex, superior temporal sulcus at the temporoparietal junction and temporal poles). The autism group showed less activation than the normal group in all these regions. However, one additional region, extrastriate cortex, which was highly active when watching animations that elicited mentalizing, showed the same amount of increased activation in both groups. In the autism group this extrastriate region showed reduced functional connectivity with the superior temporal sulcus at the temporo-parietal junction, an area associated with the processing of biological motion as well as with mentalizing. This finding suggests a physiological cause for the mentalizing dysfunction in autism: a bottleneck in the interaction between higher order and lower order perceptual processes.
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We take a fresh look at emotion recognition in autistic children, by testing their recognition of three different emotions (happy, sad, and surprise). The interest in selecting these is that whereas the first two are typical “simple” emotions (caused by situations), the third is typically a “cognitive” emotion (caused by beliefs). Because subjects with autism have clear difficulties in understanding beliefs, we predicted they would show more difficulty in recognising surprise. In contrast, as they have no difficulty in understanding situations as causes of emotion, we predicted they would not show deficits in recognising happy and sad. These predictions were borne out, in a comparison with a group of normal children and in a group of subjects with mental handicap. This result shows the importance of fine-grain analysis in emotion-recognition tasks, and is discussed in relation to affective and theory of mind models of autism.
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This article presents a model of the structure of emotion developed primarily from a consideration of neuropsychological evidence and behavioural data which have bearing on neuropsychological theories. Valence is first considered and highlighted as a defining characteristic of emotion. Next, the use of facial behaviour and autonomic nervous system patterns as defining characteristics of discrete emotions is questioned on empirical and conceptual grounds. The regulation of emotion is considered and proposed to affect the very structure of emotion itself. If there is an invariant pattern of biological activity across different instantiations of the same emotion, it is likely to be found in higher-order associative networks of central nervous system activity, the very same networks that subserve goal-directed behaviour and other cognitive functions. Drawing upon evolutionary considerations, it is argued that what is basic about emotion are the dimensions of approach and withdrawal. The nature of the linkage between such action tendencies and emotion is discussed.
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Although the amygdala is widely believed to have a role in the recognition of emotion, a central issue concerns whether it is involved in the recognition of all emotions or whether it is more important to some emotions than to others. We describe studies of two people, DR and SE, with impaired recognition of facial expressions in the context of bilateral amygdala damage. When tested with photographs showing facial expressions of emotion from the Ekman and Friesen (1976) series, both DR and SE showed deficits in the recognition of fear. Problems in recognising fear were also found using photographic quality images interpolated ("morphed") between prototypes of the six emotions in the Ekman and Friesen (1976) series to create a hexagonal continuum (running from happiness to surprise to fear to sadness to disgust to anger to happiness). Control subjects identified these morphed images as belonging to distinct regions of the continuum, corresponding to the nearest prototype expression. However, DR and SE were impaired on this task, with problems again being most clearly apparent in the region of the fear prototype, An equivalent test of recognition of morphed identities of six famous faces was performed normally by DR, confirming the dissociability of impairments affecting the recognition of identity and expression from the face. Further two-way forced-choice tests showed that DR was unable to tell fear from anger, but could tell happiness from sadness without difficulty. The finding that the recognition of fear can be differentially severely affected by brain injury is consistent with reports of the effects of bilateral amygdala damage in another case (Adolphs, Tranel, Damasio, & Damasio, 1994, 1995). The recognition of facial expressions of basic emotions may therefore be linked, to some extent, to specific neural substrates.
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Using computer-generated line-drawings, Etcoff and Magee (1992) found evidence of categorical perception of facial expressions. We report four experiments that replicated and extended Etcoff and Magee's findings with photographic-quality stimuli. Experiments 1 and 2 measured identification of the individual stimuli falling along particular expression continua (e.g. from happiness to sadness) and discrimination of these stimuli with an ABX task in which stimuli A, B, and X were presented sequentially; subjects had to decide whether X was the same as A or B. Our identification data showed that each expression continuum was perceived as two distinct sections separated by a category boundary. From these identification data we were able to predict subjects' performance in the ABX discrimination task and to demonstrate better discrimination of cross-boundary than within-category pairs; that is, two faces identified as different expressions (e.g. happy and sad) were easier to discriminate than two faces of equal physical difference identified as the same expression (e.g. both happy).
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The use of analytic and holistic modes of processing in the recognition of emotional expressions was explored. Five- and 7-yr-old children as well as adults were presented with slides of emotional expressions with different parts of the faces exposed. In Condition 1 (discrete categories), individuals were asked to press a button for each of the target emotions: happiness, surprise, fear, and anger. In Condition 2 (global categories), the target terms were feels good and feels bad. Individual features were better for identifying global categories than discrete categories, and younger children relied more on single than on combinations of features. The classification of emotional expressions may not fit a classic hierarchical model of categorization, and recognition of each emotion appears to follow different courses of development. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Compared expressions of pride and mastery in 90 preschool children who were autistic (mean age 42.40 mo), mentally retarded (mean age 41.67 mo), and normal (mean age 19.83 mo). A paradigm was used in which Ss completed developmentally appropriate puzzles with and without praise. Compared to the other Ss as many autistic Ss smiled on completion of the task, but many fewer looked up to share their pleasure with the parent or experimenter or drew attention to the task. Significantly more autistic Ss showed avoidant responses, particularly in response to praise. (Japanese abstract) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Attention, facial affect, and behavioral responses to adults showing distress, fear, and discomfort were compared for autistic, mentally retarded, and normal children. The normal and mentally retarded children were very attentive to adults in all 3 situations. In contrast, many of the autistic children appeared to ignore or not notice the adults showing these negative affects. As a group, the autistic children looked at the adults less and were much more engaged in toy play than the other children during periods when an adult pretended to be hurt. The autistic children were also less attentive to adults showing fear, although their behavior was not different from the normal children. Few of the children in any group showed much facial affect in response to these situations. The results are discussed in terms of the importance of affect in the social learning experiences of the young child.
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The behavior of preschool children from five groups (developmental language disordered, high-functioning autistic, low-functioning autistic, mentally retarded, and normally developing) were coded in three situations: presentation of a nonsocial orienting stimulus (an unfamiliar noise) and two social situations involving simulated distress on the part of an adult with whom they were playing. Cognitive level was correlated with level of responsiveness to stimuli only for the two retarded groups (mentally retarded and low-functioning autistic). Girls showed more prosocial behavior than boys in both social situations, independent of diagnosis. The language-disordered children showed only mild and subtle social deficits. The low-functioning autistic children showed pronounced deficits in responding in all situations. The mentally retarded and high-functioning autistic children showed good awareness of all situations, but were moderately impaired in their ability to respond prosocially; they rarely initiated prosocial behavior, but did respond to specific prompts. The behavioral feature that marked both autistic groups, in contrast to all other groups, was a lack of social referencing; they did not tend to look toward an adult in the presence of an ambiguous and unfamiliar stimulus. Results are discussed in terms of variability between and among high- and low-functioning autistic children, and implications for the core deficits in autism.