responses to nonverbal behaviour of dynamic virtual characters in high-functioning autism
TRANSCRIPT
ORIGINAL PAPER
Responses to Nonverbal Behaviour of Dynamic VirtualCharacters in High-Functioning Autism
Caroline Schwartz Æ Gary Bente Æ Astrid Gawronski ÆLeonhard Schilbach Æ Kai Vogeley
Published online: 4 August 2009
� Springer Science+Business Media, LLC 2009
Abstract We investigated feelings of involvement evoked
by nonverbal behaviour of dynamic virtual characters in 20
adults with high-functioning autism (HFA) and high IQ as
well as 20 IQ-matched control subjects. The effects of
diagnostic group showed that subjects with autism experi-
enced less ‘‘contact’’ and ‘‘urge’’ to establish contact across
conditions and less ‘‘interest’’ than controls in a condition
with meaningful facial expressions. Moreover, the analyses
within groups revealed that nonverbal behaviour had less
influence on feelings in HFA subjects. In conclusion, dis-
turbances of HFA subjects in experiencing involvement in
social encounters with virtual characters displaying non-
verbal behaviour do not extend to all kinds of feelings,
suggesting different pathways in the ascription of involve-
ment in social situations.
Keywords Mentalizing �High-functioning autism (HFA) � Nonverbal behaviour �Virtual characters
Introduction
Social and emotional peculiarities are crucial for the
understanding of autism spectrum disorders (hereafter:
ASD). The processing of gaze and other nonverbal facial
cues has been of particular interest. There is a large body of
research focusing on the effects of gaze behaviour in
healthy subjects on variables related to person perception,
such as the attractiveness of the interaction partner (e.g.
Williams and Kleinke 1993) or personality ratings (e.g.
Larsen and Shackelford 1996). For example, Mason et al.
(2005) showed that people whose gaze addressed the
viewer received higher likeability-ratings than persons who
showed averted gaze. Facial expressions are another
important nonverbal cue with an impact on person per-
ception, e.g. a smile leads to more positive evaluations than
neutral expression (Otta et al. 1994), whereas crying per-
sons are judged to be less aggressive and evoke stronger
feelings of sadness in the observer (Hendriks and Vinge-
rhoets 2006). Such processing of nonverbal cues is held
to occur mostly automatically and intuitively in healthy
subjects (Lakin 2006).
Previous studies on nonverbal behaviour processing in
ASD focused on the investigation of basic constituents of
social cognition such as gaze direction detection and face
processing. For example, ASD subjects have been found to
be impaired in spontaneous gaze following (Leekam et al.
1997). Swettenham et al. (2003) and Kylliainen and Hie-
tanen (2004) showed that control children as well as chil-
dren with ASD reacted faster to a target stimulus which had
been indicated before by the gaze direction of another
person. However, this so-called validity effect (Nation and
Penny 2008) does not necessarily imply that persons with
ASD process gaze behaviour as a social cue. Vlamings
et al. (2005) showed that arrows and eye stimuli triggered
attention in the same way in autistic persons whereas
control subjects showed different reaction times for social
cues. This absence of a preferential reaction to gaze in
contrast to geometric cues has been found repeatedly
(e.g. Senju et al. 2004; Ristic et al. 2005) and might be
C. Schwartz (&) � G. Bente
Humanwissenschaftliche Fakultat, Department of Social
Psychology, University of Cologne, Herbert-Lewin Street 2,
50931 Cologne, Germany
e-mail: [email protected]
A. Gawronski � L. Schilbach � K. Vogeley
Department of Psychiatry, University of Cologne,
Kerpener Street 62, 50924 Cologne, Germany
123
J Autism Dev Disord (2010) 40:100–111
DOI 10.1007/s10803-009-0843-z
indicative of a less intuitive processing of social cues in
ASD. In contrast, gaze cues play a particularly salient role
in healthy subjects, suggestive of specialized brain systems
(Baron-Cohen 1995).
With respect to facial expressions as another constituent
of non-verbal behaviour, Braverman et al. (1989) found
deficits in matching facial expressions in autistic subjects.
Impaired processing of emotionally salient expressions in
others is reported by many authors (e.g. Loveland et al.
1995; Celani et al. 1999). However, Ozonoff et al. (1990)
did not find differences between autistic children and
controls matched on verbal age in tasks such as matching
emotional expressions to sounds. Other researchers used
dynamic instead of static face cues and did not find deficits
in autistic subjects in inferring mental states from the eyes
(Back et al. 2007) or in matching videotaped emotional
expressions with photographs (Gepner et al. 2001). The use
of different paradigms might account for those conflicting
results. Dynamic and thus more realistic stimuli correspond
more to what has been learned in everyday life and might
thus probe the deficits of autistic subjects in processing
socio-emotional information more effectively.
Since Baron-Cohen’s influential theory-of-mind (ToM)
hypothesis of autism (Baron-Cohen 1995; Bruning et al.
2005) much research was performed on the capacity to
attribute mental states to others. While disturbances in
solving ToM tasks are a well-established finding (e.g.
David et al. 2008), autistic persons have also been shown to
perform normally in spite of exhibiting severe social
problems in their everyday life (e.g. Klin et al. 2003).
Despite the ability to acquire skills of mental state attri-
bution related to inferential and reflective processing of
social rules, deficits in spontaneous, intuitive and reflexive
mentalizing abilities or ‘‘undermentalizing’’ (Frith 2004)
are regarded as an important aspect for the explanation of
social impairments in autism. Indeed, it has also been
suggested that automatic and reflexive as compared to
controlled and reflective modes of understanding other
minds (e.g. Lieberman 2007) may rely upon different
neuronal networks which could be differentially disturbed
in ASD (Kennedy and Courchesne 2008). Moreover,
Campbell et al. (2006) found gaze processing and the
attribution of mental states to be associated in healthy
children whereas children with ASD were impaired in both,
hinting to a common neural network for intuitive gaze
processing and mental state attribution which might be
impaired in ASD.
In social encounters not only other-directed mentalizing
is important, but also the ability of attributing mental states
to oneself. Some authors propose that one’s own mental
experiences are a precondition for the capacity to attribute
mental states to others (e.g. Harris 1992), although this is
currently under debate (Carruthers 2009). As suggested by
the so-called simulation theory, the ascription of mental
states to others is essentially based on internal simulations
of mental states based on the observation of others’
expressive behaviours (Goldman 2006). In this process, the
ability to adequately perceive, judge and categorize one’s
own emotions is as important as perceiving and processing
the relevant cues in others’ behaviour. With regard to
autism, it has been proposed that not only other-directed
mentalizing is impaired but also the reflection on one’s
own mental states. Hill et al. (2004) investigated the pro-
cessing of one’s own emotions in ASD. They used a self-
report measure and found that ASD subjects reported more
problems in identifying and describing feelings than their
biological relatives and control subjects.
To our knowledge, no study so far addressed own
emotions in ASD in response to social stimuli. In the
present study we therefore investigated feelings of
involvement which were operationalised by measuring the
degree to which the subjects felt bored, interested,
addressed, delighted, annoyed, relaxed and nervous when
confronted with nonverbal behaviour of virtual characters.
These mental states cover the basic dimensions of evalu-
ation (e.g. ‘‘delighted’’) and activation (e.g. ‘‘relaxed’’)
according to the terminology of Osgood et al. (1957) and
reflected how involved the subjects are when confronted
with the virtual characters. Moreover, as a second set of
dependent variables, we measured the amount of ‘‘contact
experienced’’ and the ‘‘urge to establish contact’’ with the
virtual character, thereby covering involvement on a more
action-based level. As stimuli we made use of short ani-
mated video sequences containing virtual characters sys-
tematically varying gaze direction and facial expressions.
As described above, gaze and facial expressions are crucial
nonverbal behavioural cues for social cognition and most
probably also play an important role in attributing own
feelings of involvement. We used virtual stimulus material
since virtual characters allow for full experimental control
and elicit social responses similar to those evoked by real
humans (Bente et al. 1999). In contrast to this, even trained
human actors have been found to show subtle variations in
their nonverbal behaviour which are not intended by the
experimenter and are possible confounders. As own feel-
ings of involvement in autism in reaction to nonverbal cues
have not been studied so far, we prioritized experimental
control over ecological validity and opted for virtual
stimulus material.
On the basis of literature suggesting other- and self-
directed undermentalizing in autism we expected signifi-
cantly less experiences of ‘‘involvement’’, ‘‘contact’’ and
‘‘urge’’ to establish contact in ASD subjects compared to
control persons. In addition, we expected no effect of gaze
direction on the dependent measures within the ASD
group, as gaze and direct gaze processing in particular have
J Autism Dev Disord (2010) 40:100–111 101
123
been found to be impaired in autism. At the same time we
hypothesized a significant positive effect of direct gaze (as
opposed to averted gaze) in the control group in response to
the same stimuli. With respect to facial expression we
expected no effect on the dependent measures within the
HFA group, but a positive effect of meaningful facial
expressions (as opposed to arbitrary ones) on the dependent
measures in the control group.
Methods
Study Participants
The clinical group for this study consisted of 20 subjects
aged 20–53 (11 males, 9 females) with the diagnosis of
high-functioning autism (HFA) or Asperger syndrome
(AS). Since research has not provided clear differences
between HFA and AS so far we do not differentiate between
HFA and AS in this study (in concordance with Frith and de
Vignemont 2005; David et al. 2008). In the following, we
therefore use HFA as an umbrella term for both. We
recruited all subjects at the autism outpatient clinic at the
Department of Psychiatry of the University of Cologne.
Control subjects were recruited through on-campus adver-
tisement. Twenty control subjects matched for gender,
years of education and IQ without any neurological or
psychiatric history were included in this study.
The study was embedded in a series of examinations
(clinical interviews, neuropsychological testings, structural
MRI) that were performed in four different sessions. Autistic
traits were confirmed by clinical interviews according to
ICD-10 criteria by two independent physicians. Addition-
ally, all HFA subjects were screened with the Autism
Spectrum Quotient (AQ; Baron-Cohen et al. 2001a). As
expected, the HFA group scored significantly higher on the
AQ (41.3 ± 3.7, data are mean ± standard deviation)
compared to controls (14.2 ± 5.3; F 1, = 347.85, p \ .01).
As depression is a common comorbid condition (Stewart
et al. 2006), the self-rating instrument Beck Depression
Inventory was applied (BDI: Beck and Steer 1987; Hautz-
inger et al. 1995). Subjects with HFA had significantly
higher BDI scores (F = 14.04; p \ .01). Demographic and
psychopathological variables for both groups are listed in
Table 1.
Participants with HFA were on average older than
control participants (39.3 ± 9.2 compared to 34 ± 7.2,
p \ .05). Emotional functioning as investigated in our
study is not known to deteriorate with age. On the contrary,
a longer learning history in the HFA group might be an
advantage for acquired mentalizing abilities emphasizing
even more possible deficits that occur in spite of older age.
Moreover, no significant changes in the capacity to ascribe
mental states to oneself are likely to occur in the age span
between ± 34 and ± 39 years. We thus assumed that the
group difference in age would not significantly influence
our results.
In addition to the experimental task, the intelligence test
WAIS-R and the ‘‘Reading the mind in the eyes’’ test
(ToM-Eyes: Baron-Cohen et al. 2001b) to assess mental-
izing abilities were conducted. The order of tests and
experiments was randomized across participants. The
questionnaire was answered by the participants before the
first clinical interview.
HFA subjects showed a similar level of education (years
of education: 18 ± 3.28 years) as controls (20 ± 4.36
years; F = 2.615, n.s.). Accordingly, the HFA group
yielded verbal (125.3 ± 11.3), performance (123.2 ±
13.4) and total IQ scores (127.2 ± 12) that were not sig-
nificantly different from the control group (verb. IQ:
125.8 ± 8; perf. IQ: 127.7 ± 11.1; tot. IQ: 131.6 ± 8.3;
all F \ 2, all p [ 0.05, n.s.) as assessed with the Wechsler
Intelligence Scale for Adults (WAIS-R, German version
HAWIE-R: Tewes 1991). As expected, control subjects
reached significantly higher scores on the ToM-Eyes test
(16.2 ± 4.07, HFA: 18.7 ± 3.01, F = 4.88, p \ .05). IQ
and mentalizing results are listed in Table 1. Furthermore,
the two groups were matched for handedness (F = 0.49,
n.s.) as assessed with the Edinburgh Handedness Inventory
(EHI: Oldfield 1971).
Table 1 Demographic, psychopathological, IQ and mentalizing
results
HFA Control Statistics
M (SD) M (SD)
Age (years) 39.3 (9.2) 34 (7.2) F1 = 4.22*
Gender (female: male) 9:11 9:11 v2 = .40 (n.s.)
EHIa 81.1 (22.3) 82.4 (16.2) F1 = .49 (n.s.)
BDIa 11.2 (7) 4.8 (3.1) F1 = 14.04**
AQ2 41.3 (3.7) 14.2 (5.3) F1 = 347.85**
WAIS-Rb verbal IQb 125.3 (11.3) 125.8 (8) F1 = .03 (n.s.)
WAIS-Rb performance
IQb123.2 (13.4) 127.7 (11.1) F1 = 1.34
(n.s.)
WAIS-Rb IQ (total)b 127.2 (12) 131.6 (8.3) F1 = 1.87
(n.s.)
ToM-Eyesa 16.2 (4.07) 18.7 (3.01) F1 = 4.88*
M mean, SD standard deviation, n.s. not significant, EDI = EHIEdinburgh Handedness Inventory, BDI Beck Depression Inventar, AQAutism Spectrum Quotient, WAIS-R Wechsler Intelligence Scale for
Adults, ToM-Eyes Reading the Mind in the Eyes Test
* p \ .05, ** p \ .01a Raw scoreb Standardized score
102 J Autism Dev Disord (2010) 40:100–111
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Stimulus Material, Experimental Design and Procedure
Stimulus material consisted of animated video sequences
which had been designed using the software package
Poser 4.0 (Curious Lab�). The material has already been
used before and was extensively studied with respect to
their neural correlates in healthy control volunteers before
(Schilbach et al. 2006; Schilbach et al. 2008; Mojzisch
et al. 2006). These short video sequences depict virtual
characters with head and shoulders (Fig. 1; for example
stimuli see http://www.medizin.uni-koeln.de/kliniken/psy
chiatrie/Bildgebung/schilbach.htm). The virtual characters
appeared on screen and exhibited dynamic facial
expressions resembling real-life approach situations when
initiating social interaction. Sequences systematically
varied in the following respects (for further details see
Schilbach et al. 2006): (1) Facial expressions of the vir-
tual characters are perceived by healthy control persons
as socially relevant [SOC] in that they are indicative of
someone’s intention to establish interpersonal contact
while facial movements are perceived as arbitrary and
socially irrelevant [ARB], thus systematically varying the
degree with which the virtual character expressed his/her
intention to communicate with the addressee; (2) Virtual
characters shown in the experiment either gazed directly
at the study participant [ME] or looked aside towards an
invisible addressee situated at an angle of approximately
30� [OTHER] to the left or to the right, thus systemati-
cally manipulating the observer’s self-involvement. The
two factors (1) GAZE DIRECTION [ME vs. OTHER]
and (2) FACIAL EXPRESSION [SOC vs. ARB] consti-
tuted a two-factorial-design. Condition-specific dynamic
changes in facial expression were modeled according to
the Facial Action Coding System (FACS) (Ekman and
Friesen 1978). Animations were realized by interpolating
images between the neutral and condition-specific facial
expressions as well as body positions of the virtual
characters. Video sequences were generated simulating a
100 mm focal width camera view. In the video files the
virtual characters appeared with a light grey background.
The temporal order of each video clip adhered to a
standard pattern of 7.5 s. Each sequence began with the
entrance of a virtual character (‘‘walk in’’), followed by
positioning (‘‘turn’’) either towards the observer or
towards someone else who is out of view following a
rigid time course (Schilbach et al. 2006, 2008). Previous
studies employing the same stimulus material yielded
reliable effects in test persons with respect to judgment of
the degree of social interaction and were associated with
the recruitment of anterior medial prefrontal cortex as key
region of social cognition (Schilbach et al. 2006). In the
present study, we presented a subset of the original
stimulus material with four male and four female virtual
characters to every participant, expressing either a
socially meaningful facial expression (SOC, a smile alone
or a smile combined with eye-lid movement) or an
arbitrary facial expression (ARB, cheak or mouth move-
ment). Half of them oriented their gaze towards the
viewer and thus addressed the subject (ME), half of them
oriented their gaze to a third invisible person to the left or
right of the participant (OTHER) in a two-by-two-design.
The systematic permutation of gender (male versus
female), facial expression (SOC versus ARB) and gaze
direction (ME versus OTHER) resulted in eight animated
Fig. 1 Stimulus examples
taken from Mojzisch et al.
(2006). Time axis in
milliseconds. The virtual
character walks in, shows direct
(ME) or averted (OTHER) gaze,
then shows a meaningful (SOC)
or not meaningful (ARB) facial
expression, then turns and walks
off
J Autism Dev Disord (2010) 40:100–111 103
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sequences that were presented in a randomized order to
every participant.
All subjects received standardized verbal instructions.
Study participants were told to be part of a scene with two
virtual characters, one of which would appear on the screen
throughout the experiment (as illustrated in Fig. 1). The
other person on the right or left side could not be seen at
any time during the experiment from the participants’ point
of view, but was told to stand close to the participant. The
virtual character on the screen could therefore address the
study participant (ME) or the invisible other (OTHER).
Subjects were further instructed to watch eight sequences
with the virtual character and to answer the questionnaire
that appeared on the screen after each sequence. The
questionnaire was computer-based. The next sequence was
started via mouse click by the participant.
Data Analysis
As dependent variables (4-point Lickert scale) served the
following emotion items: ‘‘During the sequence I felt
annoyed, bored, interested, addressed, relaxed, nervous,
delighted’’. The points of the Lickert scale were: ‘‘strongly
disagree’’, ‘‘disagree’’, ‘‘agree’’ and ‘‘strongly agree’’.
Responses were coded so that higher values represent
agreement. The first step of data analysis was a factor
analysis (main component analysis with varimax rotation)
for the seven emotional items. As described in the results
section these items load on two separate factors, namely
‘‘interest’’ and ‘‘ease’’, which were used subsequently as
dependent variables in the first MANOVA. In addition,
participants were asked how strongly they experienced
‘‘contact’’ with the virtual character and how strong their
‘‘urge’’ was to establish contact with the person represented
by the virtual character (4-point scale). ‘‘Contact’’ experi-
enced and the ‘‘urge’’ to establish contact were used as
dependent variables in a second MANOVA. One between-
subjects factor (diagnostic group: HFA versus control
group) and three within-subjects factors (gaze: directed
versus averted, ME versus OTHER; facial expression:
socially meaningful versus arbitrary, SOC versus ARB;
gender of the virtual character: male versus female)
constituted the independent variables for both analysis,
leading to two 2 9 2 9 2 9 2 MANOVAs as key analysis
instruments. Age, depression and ToM measures were
considered as potentially influencing the dependent vari-
ables. Therefore, we calculated correlations of these mea-
sures with all dependent variables. As these correlations
failed significance (see Table 2), age, BDI depression
values and ToM-Eye scores were not included as covari-
ates in the MANOVAs.
Our hypotheses also focus on the effects of the inde-
pendent variables within the HFA versus control group.
Whereas the main effect of group in MANOVAs shed light
on differences in amount of feelings, the analyses within
groups can reveal whether effects are absent in HFA. We
therefore conducted Bonferroni-corrected pairwise com-
parisons for the factors ‘‘gaze’’ and ‘‘facial expression’’
within each group, even when the interaction of group and
‘‘gaze’’ or group and ‘‘facial expression’’ had not reached
significance.
Results
The factor analysis for the seven emotion items revealed
two components (Table 3). The first component can be
labelled ‘‘interest’’ whereas the second component covers
feelings of ‘‘ease’’. Based on these results from factor
analysis, separate values for the two factors ‘‘interest’’ and
‘‘ease’’ were calculated for each subject and served as
dependent measures in the following analyses.
Main Effects of Group (HFA Versus Control)
The first MANOVA did not reveal a significant effect of
group, neither on ‘‘interest’’ (F1,37 = .905, p = .348,
Eta2 = .024) nor on ‘‘ease’’ (F1,37 = .597, p = .444.
Eta2 = .016). The second MANOVA showed a decrease in
the HFA group both of ‘‘contact’’ (HFA: M = 1.974,
SD = .102; control group: M = 2.294, SD = .100;
F1,37 = 5.011, p = .031, Eta2 = .119) and of ‘‘urge’’ (HFA:
Table 2 Pearson correlations between dependent variables and age,
ToM-Eye Data and BDI
‘‘Interest’’ ‘‘Ease’’ ‘‘Contact’’ ‘‘Urge’’
Age (years) .185 (n.s.) .042 (n.s.) -.029 (n.s.) .100 (n.s.)
ToM-Eyes2 -.032 (n.s.) .202 (n.s.) .141 (n.s.) .092 (n.s.)
BDI -.283 (n.s.) -.131 (n.s.) -.112 (n.s.) -.193 (n.s.)
n.s. not significant, ToM-Eyes Reading the Mind in the Eyes Test,
BDI Beck Depression Inventar
Table 3 Rotated matrix of factors for feelings
Variance explained ‘‘Interest’’ ‘‘Ease’’
41.4% 22.0%
Interested .8 .3
Addressed .8 -.0
Bored -.7 .1
Delighted .7 .4
Relaxed .0 .9
Nervous .0 -.8
Annoyed -.3 -.6
104 J Autism Dev Disord (2010) 40:100–111
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M = 1.645, SD = .130; control group: M = 2.194, SD =
.126; F1,37 = 9.205, p = .004, Eta2 = .199).
Main Effects of Gaze, Facial Expression and Gender
of the Virtual Character
Both MANOVAs revealed significant main effects of gaze
and facial expression on all dependent measures, irre-
spective of diagnostic groups (see Tables 4, 5). Gender of
the virtual character did not have a significant effect on any
dependent measure (see Tables 5, 6).
Interactions
The first MANOVA showed a significant 2-way-interaction
between group and facial expression for ‘‘interest’’
(F = 10.101, p = .003, Eta2 = .214), but no significant
interaction between group and gaze (see Table 6).
The simple main effect of group within the condition
SOC turned out to be significant (F = 4.684, p = .037,
Eta2 = .112). In this condition, HFA showed significantly
lower levels of ‘‘interest’’ than control subjects (see also
Table 9).
There was no significant interaction between gaze
and facial expression. The second MANOVA revealed a
significant 2-way-interaction between group and facial
expression for ‘‘urge’’ to establish contact (F1,37 = 4.962,
p = .015, Eta2 = .150).
In addition, there was a significant 2-way-interaction
between gaze and facial expression on ‘‘contact’’. Simple
main effects showed that the effect of facial expression
was not reversed by the interaction. Meaningful facial
Table 4 Main effects first
MANOVA
M mean, SD standard deviation
Effect of group HFA: M (SD) Control: M (SD) F(1,37) p Eta2
‘‘Interest’’ -.10 (.67) -.10 (.71) .91 [.20 .02
‘‘Ease’’ .10 (.42) .09 (.62) .60 [.20 .02
Effect of gaze ME: M (SD) OTHER: M (SD) F(1,37) p Eta2
‘‘Interest’’ .29 (.10) -.26 (.11) 31.79 \.001 .46
‘‘Ease’’ -.13 (.11) .15 (.12) 8.29 \.05 .18
Effect of facial expression SOC: M (SD) ARB: M (SD) F(1,37) p Eta2
‘‘Interest’’ .42 (.10) -.40 (.10) 92.26 \.001 .71
‘‘Ease’’ .12 (.11) -.11 (.13) 5.74 \.05 .13
Effect of gender of virtual character Male: M (SD) Female: M (SD) F(1,37) p Eta2
‘‘Interest’’ .05 (.64) .06 (.72) 2.03 [.20 .05
‘‘Ease’’ -.05 (.55) -.06 (.70) 2.39 [.20 .06
Table 5 Main effects second
MANOVA
M mean, SD standard deviation
Effect of group HFA: M (SD) Control: M (SD) F(1,37) p Eta2
‘‘Contact’’ 1.97 (.10) 2.29 (.10) 5.01 \.05 .12
‘‘Urge’’ 1.65 (.13) 2.19 (.13) 9.21 \.05 .20
Effect of gaze ME: M (SD) OTHER: M (SD) F(1,37) p Eta2
‘‘Contact’’ 2.66 (.10) 1.61 (.08) 70.41 \.001 .67
‘‘Urge’’ 2.14 (.11) 1.70 (.10) 18.90 \.001 .34
Effect of facial expression SOC: M (SD) ARB: M (SD) F(1,37) p Eta2
‘‘Contact’’ 2.37 (.08) 1.89 (.09) 32.19 \.001 .47
‘‘Urge’’ 2.12 (.11) 1.71 (.10) 17.26 \.001 .32
Effect of gender of virtual character Male: M (SD) Female: M (SD) F(1,37) p Eta2
‘‘Contact’’ 2.14 (.52) 1.93 (.71) 008 [.20 .00
‘‘Urge’’ 2.13 (.53) 2.12 (.52) .368 [.20 .01
J Autism Dev Disord (2010) 40:100–111 105
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expressions led to higher contact feelings in the condition
OTHER as well (F = 3.270, p = .049, Eta2 = .150).
None of the 3-way-interactions between group, facial
expression and gaze reached significance (see Tables 6, 7).
Pairwise Comparisons of Gaze Within HFA and
Control Group
Planned pairwise comparisons within the HFA group
showed that the effect of gaze direction was significant for
the dependent measures ‘‘interest’’ (t = 4.065, p = \ .001),
‘‘contact’’ (t = 5.320, p = \ .001),) and ‘‘urge’’ (t = 2.724,
p = .010), but not for ‘‘ease’’ (t = 1.691, p = .099). In the
control group, gaze direction had a significant effect on all
dependent measures: ME led to an increase of ‘‘interest’’
(t = 3.904, p = \ .001), a decrease of ‘‘ease’’ (t = 2.386,
p = .022), an increase of ‘‘contact’’ (t = 6.578, p = \ .001)
and a decrease of ‘‘urge’’ (t = 3.437, p = .001) (see Table 8
for means and standard deviations). Thus, the gaze variation
had less influence on the experiences as empirically
addressed by the four factors of ‘‘interest’’, ‘‘ease’’, ‘‘con-
tact’’ and ‘‘urge’’, notably, ‘‘ease’’ was not influenced in
HFA.
Pairwise Comparisons of Facial Expression Within
HFA and Control Group
The pairwise comparisons in the HFA group revealed a
significant positive effect of SOC (as opposed to ARB)
only for ‘‘interest’’ (t = 4.472, p = \ .001) and ‘‘contact’’
(t = 3.479, p = .001), but neither for ‘‘ease’’ (t = 0.522,
p = .605) nor for ‘‘urge’’ (t = 1.121, p = .271). In the
control group SOC (versus ARB) significantly impacted
all dependent measures, namely ‘‘interest’’ (t = 9.125,
p = \ .001), ‘‘ease’’ (t = 2.902, p = .006), ‘‘contact’’
(t = 4.560, p = \ .001), and ‘‘urge’’ (t = 4.804,
p = \ .001) in a positive way (see Table 9 for means and
standard deviations).
Table 6 Interactions first
MANOVAGroup*Gaze F(1,37) p Eta2
‘‘Interest’’ .03 [.20 .00
‘‘Ease’’ .20 [.20 .01
Group*Facial expression F(1,37) p Eta2
‘‘Interest’’ 10.10 \.05 .21
‘‘Ease’’ 2.72 [.10 .07
Gaze*Facial expression F(1,37) p Eta2
‘‘Interest’’ 4.09 [.05 .10
‘‘Ease’’ .46 [.20 .01
Gaze*Facial expression*Group F(1,37) p Eta2
‘‘Interest’’ .18 [.20 .01
‘‘Ease’’ 1.16 [.20 .03
Table 7 Interactions second
MANOVAGroup*Gaze F(1,37) p Eta2
‘‘Contact’’ .25 [.20 .01
‘‘Urge’’ .14 [.20 .00
Group*Facial expression F(1,37) p Eta2
‘‘Contact’’ 1.00 [.20 .03
‘‘Urge’’ 7.74 \.05 .17
Gaze*Facial expression F(1,37) p Eta2
‘‘Contact’’ 8.84 \.05 .19
‘‘Urge’’ 1.85 [.05 .05
Group*Gaze*Facial expression F(1,37) p Eta2
‘‘Contact’’ .02 [.20 .00
‘‘Urge’’ .15 [.20 .00
106 J Autism Dev Disord (2010) 40:100–111
123
Discussion
Our study shows that deficits in processing socio-emotional
information not only relate to disturbances in person per-
ception and the ability to ascribe mental states to others but
additionally include disturbances in experiencing involve-
ment when employing virtual characters display nonverbal
behaviour. This is indicated by a significantly lower gen-
eral experience of ‘‘contact’’ and ‘‘urge’’ to establish con-
tact in HFA as well as less ‘‘interest’’ in HFA subjects
when confronted with socially meaningful facial expres-
sions. Moreover, the analyses within each group showed
that both gaze direction and facial expression had less
impact on the experience of involvement in HFA than in
control subjects.
Effect of the Diagnostic Group: ‘‘Undermentalizing’’
in HFA?
The impairment of mentalizing, i.e. attributing mental
states to other persons (Frith 2004; David et al. 2008), and
the impairment of the ability to process one’s own emo-
tions (Hill et al. 2004) are well-known findings in autism.
On this basis, we hypothesized a reduced level of feelings
of involvement in the HFA compared to the control group
in a social encounter mediated by a virtual character.
Corroborating our initial hypothesis, we found that HFA
persons generally experience less ‘‘contact’’ and are less
inclined to establish contact (decrease of ‘‘urge’’ to estab-
lish contact), regardless of the nature of the stimulus.
Reduced engagement in social interactions is among the
core symptoms of autism. Our findings suggest that a lower
impulse to get into contact with others or to be socially
entrained by others is a key component that can be dem-
onstrated also in social encounters conveyed by virtual
characters. Other researchers have found that autistic
children react more positively to humanoid robots than to
humans (Dautenhahn and Werry 2004). Difficulties that are
already present during such a confrontation with virtual
characters might therefore be even more pronounced when
interacting with real persons. Other findings suggest that
individuals with ASD are more reluctant to interpret virtual
characters as real social partners and to attribute social
meaning to ambiguous cues, whereas typically developing
subjects intuitively do so (Abell et al. 2000; Klin 2000). As
a consequence, virtual characters might not appear ‘‘real’’
enough for subjects with HFA, and the differences we
found might be less pronounced when they are dealing with
real humans. However, our data do not support this inter-
pretation. Pairwise comparisons actually showed signifi-
cant effects of the stimulus variations in HFA, even though
the effects were broader in controls (see below).
Contrary to our expectations, we did not find a generally
lower level of ‘‘interest’’ and ‘‘ease’’ in the HFA group.
Previous findings suggest that dynamic material can facil-
itate processing of social cues for autistic individuals (Back
Table 8 Means (standard deviations) of all dependent measures with respect to the independent variable gaze direction
Control group ‘‘Interest’’ ‘‘Ease’’ ‘‘Contact’’ ‘‘Urge’’
ME .36 (.46)a -.07 (.74)a 2.86 (.46)a 2.44 (.73)a
OTHER -.17 (.57)b .25 (.66)b 1.73 (.57)b 1.95 (.67)b
HFA ‘‘Interest’’ ‘‘Ease’’ ‘‘Contact’’ ‘‘Urge’’
ME .16 (.74)a -.25 (.66)a 2.49 (.80)a 1.84 (.60)a
OTHER -.36 (.73)b .05 (.85)a 1.48 (.47)b 1.43 (.54)b
a For ME versus, b For OTHER indicates a significant difference for this dependent measure, a For both indicates a non-significant difference
Table 9 Means (standard deviations) of the dependent variables with respect to the independent variable facial expression
Control group ‘‘Interest’’ ‘‘Ease’’ ‘‘Contact’’ ‘‘Urge’’
SOC .64 (.55)a .28 (.65)a 2.56 (.44)a 2.53 (.77)a
ARB -.45 (.47)b -.10 (.72)b 2.03 (.46)b 1.86 (.63)b
HFA ‘‘Interest’’ ‘‘Ease’’ ‘‘Contact’’ ‘‘Urge’’
SOC .15 (.74)a -.09 (.73)a 2.16 (.54)a 1.69 (.52)a
ARB -.35 (.68)b -.10 (.82)a 1.80 (.62)b 1.58 (.62)a
a For SOC versus, b For ARB indicates a significant difference for this dependent measure, a For both indicates a non-significant difference
J Autism Dev Disord (2010) 40:100–111 107
123
et al. 2007) which might have been the case in our study as
well. In addition, it might be relevant that we only included
adult individuals with high IQ values in our sample. It is
thus possible that our subjects have learned over lifetime to
adequately express and read out feelings of ‘‘interest’’ and
‘‘ease’’ when confronted with social stimuli even though
they might have been impaired in doing so during their
childhood. This is also corroborated by the observation in
interviews that the majority of HFA subjects has developed
idiosyncratic rules that allow them to ‘‘survive’’ in social
situations (e.g. look and smile at other persons). This issue
that HFA subjects might be able to learn and to acquire a
social skill–as opposed to the recruitment of an intuitive,
prereflexive, presumably inborn capacity–has already been
previously proposed with respect to ToM (Klin et al. 2003).
How can we explain that there are no general group dif-
ferences in feelings of ‘‘interest’’ and ‘‘ease’’ but at the same
time significantly lower ‘‘contact’’ and ‘‘urge’’ experiences
in HFA? An adequate use of words like the ones used as
items in this study (e.g. being ‘‘interested’’, ‘‘addressed’’,
‘‘delighted’’, ‘‘relaxed’’ etc.) can possibly be acquired as an
‘‘emotional vocabulary’’ without being necessarily experi-
enced emotionally to the same degree as by non-HFA sub-
jects. It is still unclear whether autistic persons suffer from a
lack of inner emotional experience on a lower level of
information processing or whether the problems arise on a
higher level, e.g. in reflections and in theorizing about ones
own inner states. In both cases, the acquisition of an emo-
tional vocabulary, e.g. via observation of other persons’
verbally expressed feelings or behaviour, might nevertheless
allow to adequately refer to such behavioural patterns usu-
ally indicating ‘‘common’’ feelings. In contrast to this, we
assume that experienced ‘‘contact’’ and ‘‘urge’’ to get into
contact are less verbalised by other persons in everyday life,
so that autistic subjects may have fewer opportunities to
learn their meaning. An alternative explanation is that
feelings of contact imply an action (that is related to actually
getting into contact with others) and thus bear consequences
for the relation with the interaction partner. To express those
feelings might therefore imply a higher threshold for HFA
subjects than to express the more ‘‘detached’’ feelings of
‘‘interest’’ and ‘‘ease’’.
However, when confronted with a meaningful facial
expression, HFA expressed less ‘‘interest’’ than controls.
Thus, the deficit in experiencing ‘‘interest’’ appears to be
specific to this condition. Given the high functional per-
formance of the group studied we assume that the subjects
were able to correctly identify the facial expressions and
that the differences we found are not due to cognitive, but
emotional ‘‘hypomentalizing’’ (Frith 2004). Why was there
less ‘‘interest’’ in HFA only in the condition of meaningful
facial expressions? A possible explanation might lie in the
employment of dynamic facial expressions which required
spontaneous reactions to changes in the mouth and eye
region, whereas the gaze variation only concerned the eye
region. Adequate reactions to gaze variations might
therefore be easier to acquire.
Generally speaking, the differences between HFA and
controls revealed by our study can be explained in two
ways. Either they represent experiential differences or
differences in the ability to report feelings (underreport-
ing). The relationship between the experience of an emo-
tion (qualia) and its explicit self-attribution or verbalisation
is discussed controversially in the field of philosophy (e.g.
Schwarz-Friesel 2007). In psychological research only the
outcome of emotional experience, i.e. the self-attribution,
can be measured. The fact that HFA subjects did not
exhibit generally lower levels of ‘‘interest’’ and ‘‘ease’’
than controls provides strong evidence for the assumption
that there is no bias towards underreporting and that our
findings represent differences in experience.
Effect of Gaze Direction Within Groups: No Effect
in HFA?
Contrary to our hypothesis, we found significant effects of
gaze in HFA subjects. Both HFA and control subjects
expressed higher feelings of ‘‘interest’’ and ‘‘contact’’ in
response to direct gaze (although—as revealed by the
MANOVA described above—the general level of ‘‘con-
tact’’ feelings was lower in HFA subjects). Different rea-
sons might account for this finding. First, it might be due to
the passive character that only required observation instead
of interactive engagement with the virtual character. A
passive observation is easier to handle than an interactive
situation and has decreased ecological validity (Boraston
and Blakemore 2007). In addition, our gaze variation was
not parametrically varied, but was clearly presented either
as directed or averted gaze. This might have facilitated the
detection and interpretation of this comparably easy social
cue for HFA, assuming that the interpretation of obvious
social cues can be learned by applying a ‘‘rational’’ or
‘‘theoretical’’ strategy, even if the intuitive processing is
impaired. More subtle and interactive gaze cues might be
needed to reveal different reactions of HFA subjects, e.g.
employing a systematic parametric variation of duration of
directed gaze (Kuzmanovic et al. 2009). Interestingly, and
in contrast to our hypothesis, we found negative feelings,
especially less experiences of ‘‘ease’’ in response to
directed gaze in control subjects whereas the gaze variation
did not influence feelings of ‘‘ease’’ in HFA subjects. The
negative effect of direct gaze in control subjects may be
explained by context factors. Most previous research has
focused on the influence of gaze cues on person perception
(e.g. Mason et al. 2005). So far little is known about the
feelings of involvement that are evoked in the passively
108 J Autism Dev Disord (2010) 40:100–111
123
observing viewer. In our study, the encounter with the
virtual character was instantiated in a highly controlled
fashion so that control subjects might have perceived more
pressure when being directly gazed at which might have
led to feelings of unease. However, with respect to the
purpose of this study, the fact that HFA subjects’ level of
‘‘ease’’ did not depend on gaze direction is more interesting
and relevant. Baron-Cohen et al. (2001) showed that HFA
subjects are impaired in attributing emotions to a person’s
representation that is based on the depiction of the person’s
eyes. Our results are in accordance with the reduced ability
to ‘mindread’ other persons’ gaze behaviour. As suggested
by Campbell et al. (2006), a common neural network might
be implied in gaze processing and mental state attribution,
however, a recent study of our own group showed differ-
ential neural mechanisms for gaze detection and gaze
evaluation (Kuzmanovic et al. 2009). Impairments of the
gaze evaluation component in autism might explain diffi-
culties in attributing mental states to the self when con-
fronted with gaze behaviour of a virtual character. An
alternative explanation for the lack of an effect on feelings
of ‘‘ease’’ might be the higher baseline in depression in our
HFA sample compared to controls. As the comorbidity of
depression and anxiety is high (e.g. Alloy et al. 1990),
higher anxiety levels in our clinical sample are probable.
On the other hand, as discussed above, our findings do not
show a group difference in the level of ‘‘ease’’, but the
problems of subjects with HFA seem to be connected to the
fine-tuning of these feelings in response to nonverbal sig-
nals. Therefore we assume that the differences between
HFA subjects and control persons in their responses to the
gaze variations are not related to the affective state of
participants. This assumption is supported by the fact that
we did not find significant correlations between BDI scores
and the dependent measures.
Effect of Facial Expression Within Groups
As expected, facial expressions of the virtual characters
had different effects on the HFA versus the control group,
thus corroborating our second hypothesis. Socially mean-
ingful facial expressions had a positive significant effect on
all dependent variables in the control group. The effect was
less prominent and not universal in HFA subjects, namely
without impact on ‘‘urge’’ to establish contact nor on
feelings of ‘‘ease’’. It is not plausible that the impaired
recognition of the meaningful facial expression was the
cause as in that case there would have been no effect on
feelings in HFA at all. This is in line with evidence for
intact identification of facial expressions in HFA (Gepner
et al. 2001). Similar to gaze variation, facial expression
influenced feelings of ‘‘ease’’ in the control group but not
in HFA subjects. Following the simulation theory’s
approach (Goldman 2006), this hypomentalizing phenom-
enon with respect to the attribution of mental states to
oneself might be closely related to the impairment in the
attribution of mental states to others.
Interestingly, we did not find a global deficit in the sense
of hypomentalizing with respect to feelings of ‘‘interest’’,
neither on a general level (no significant main effect of
group) nor in response to gaze direction or facial expres-
sions. The latter finding hints to intact fine-tuning in
response to nonverbal signals.
This pattern was different for feelings of ‘‘ease’’: there
was also no difference in the general amount, but when it
came to fine-tuning feelings of ‘‘ease’’ to nonverbal cues,
HFA subjects failed. For their level of ‘‘ease’’ it did not
make a difference whether they were gazed at or what
facial expression the virtual character expressed. Feelings
of ‘‘ease’’ (related to the adjectives ‘‘nervous’’, ‘‘relaxed’’,
‘‘annoyed’’) express an inner state without a concrete
object relation whereas feelings of ‘‘interest’’ are always
directed towards an object (interested by something). The
latter might therefore be easier to adopt in the usage of
concrete stimuli. Concerning ‘‘ease’’, HFA might have
learned to express an adequate amount on a general level,
but the adjustment to stimuli is possibly harder to deal
with. Generally speaking, there might be two pathways of
ascribing mental states to oneself. One might be intuitive
and spontaneous and allow for flexible adaptation to dif-
ferent stimuli. The second pathway might depend on
learning of external symbols such as observed facial
expressions and the association of verbal terms to such
external cues. Assuming that the intuitive, prereflexive
component of mentalizing is impaired in HFA, our findings
suggest that feelings of ‘‘ease’’ and ‘‘contact’’ might be
harder to acquire using the second pathway than feelings of
‘‘interest’’. Of course, our findings do not provide a formal
proof for this interpretation. Interestingly, however, recent
neuroimaging data suggests altered functional organization
of the large-scale neural network involved in social and
emotional processing in autism, but no alteration of the
functional organization of the network involved in sus-
tained attention and goal-directed cognition (Kennedy and
Courchesne 2008). Conceivably, intuitive mentalizing
related to the experience of ‘‘contact’’ or the ‘‘urge to
establish contact’’ as compared to more reflective mental-
izing with respect to ‘‘ease’’ and ‘‘interest’’ as part of the
task in our study could differentially recruit these networks
and might explain why autistic individuals perform dif-
ferently in these two respects. Neuroscientific approaches
might, therefore, help to shed light on possibly independent
processes which could have resulted in the findings
observed in our study.
J Autism Dev Disord (2010) 40:100–111 109
123
Limitations of the Study
A possible objection to the method of this paper is that we
are investigating deficits in the processing of feelings in a
way that presumes correct description of feelings. How-
ever, the fact that we found similar results in the HFA and
control group for some measures suggests that HFA sub-
jects actually can deal with the instrument. In addition,
higher BDI scores in the HFA group show that they are
able to use questionnaires to express feelings (see also Hill
et al. 2004). We can thus assume that our method yields
valid results.
Another critical point is the use of virtual stimulus
material. The advantage of high experimental control has
to be weighed against possibly reduced ecological validity
that has to be debated. Even though there is evidence that
virtual characters evoke ecologically valid social responses
(Bente et al. 1999), only a replication with human stimulus
material can show whether the effects of the variables we
focused on are alike.
Thirdly, both IQ and years of education were high in our
sample. Cognitive capacities above average might have
facilitated compensation of intuitive social cognitive skills
in subjects with HFA. The deficits we found might even be
more severe in persons with lower IQ.
Conclusion
Mentalizing deficits in autism spectrum disorders include
impairments in the ascription of feelings of involvement in
response to nonverbal behaviour of virtual characters.
Relative to controls HFA express less feelings and within
the HFA group certain effects are absent which are present
in control persons. However, this deficit is not universal.
Different pathways in mentalizing might explain this pat-
tern of results and future studies making use of functional
neuroimaging techniques that could elicit the underlying
neural mechanisms could help to investigate this in further
detail.
Acknowledgments This work was supported by a project grant of
the German ministry of Education and Research (BMBF ‘‘Social
Gaze: Phenomenology and neurobiology of dysfunctions in high-
functioning autism (HFA)) to Gary Bente and Kai Vogeley.
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