PSYCHIATRY AND PRECLINICAL PSYCHIATRIC STUDIES - ORIGINAL ARTICLE

Impairment in face processing in autism spectrum disorder:a developmental perspective

Ellen Greimel • Martin Schulte-Ruther •

Inge Kamp-Becker • Helmut Remschmidt •

Beate Herpertz-Dahlmann • Kerstin Konrad

Received: 6 December 2013 / Accepted: 25 March 2014

� Springer-Verlag Wien 2014

Abstract Findings on face identity and facial emotion

recognition in autism spectrum disorder (ASD) are incon-

clusive. Moreover, little is known about the developmental

trajectory of face processing skills in ASD. Taking a

developmental perspective, the aim of this study was to

extend previous findings on face processing skills in a

sample of adolescents and adults with ASD. N = 38 ado-

lescents and adults (13–49 years) with high-functioning

ASD and n = 37 typically developing (TD) control sub-

jects matched for age and IQ participated in the study.

Moreover, n = 18 TD children between the ages of 8 and

12 were included to address the question whether face

processing skills in ASD follow a delayed developmental

pattern. Face processing skills were assessed using com-

puterized tasks of face identity recognition (FR) and

identification of facial emotions (IFE). ASD subjects

showed impaired performance on several parameters of the

FR and IFE task compared to TD control adolescents and

adults. Whereas TD adolescents and adults outperformed

TD children in both tasks, performance in ASD adolescents

and adults was similar to the group of TD children. Within

the groups of ASD and control adolescents and adults, no

age-related changes in performance were found. Our find-

ings corroborate and extend previous studies showing that

ASD is characterised by broad impairments in the ability to

process faces. These impairments seem to reflect a devel-

opmentally delayed pattern that remains stable throughout

adolescence and adulthood.

Keywords Autism spectrum disorder � Development �Age � Face recognition � Emotion

Introduction

When interacting with other persons, an individuals face is

an important source of information that gives insight into

personality traits, demographic characteristics and the

emotional state of an individual (Flowe 2012). Individuals

with autism spectrum disorder (ASD), a neurodevelop-

mental disorder characterized by restricted interests,

impaired communication and deficits in social interaction

(American Psychiatric Association 1994), often have

marked difficulties in reading faces. These difficulties

involve problems in recognizing a persons emotional

expression in a face or even the person’s identity (Schultz

2005).

In the past decades, a large number of studies have

examined deficits in face processing in ASD. The majority

of these studies focused on emotional face processing and

employed emotion matching or labelling tasks. These

studies have provided evidence for deficient recognition of

facial expressions in children and adults with ASD (Boelte

E. Greimel � M. Schulte-Ruther � K. Konrad

Child Neuropsychology Section, Department of Child and

Adolescent Psychiatry, Psychosomatics and Psychotherapy,

University Hospital of the RWTH Aachen, Aachen, Germany

E. Greimel � B. Herpertz-Dahlmann

Department of Child and Adolescent Psychiatry, Psychosomatics

and Psychotherapy, University Hospital of the RWTH Aachen,

Aachen, Germany

E. Greimel (&)

Department of Child and Adolescent Psychiatry, Psychosomatics

and Psychotherapy, University Hospital Munich,

Pettenkoferstraße 8a, 80336 Munich, Germany

e-mail: Ellen.Greimel@med.uni-muenchen.de

I. Kamp-Becker � H. Remschmidt

Department of Child and Adolescent Psychiatry, University

Hospital Giessen and Marburg, Campus Marburg, Germany

123

J Neural Transm

DOI 10.1007/s00702-014-1206-2

and Poustka 2003; Boraston et al. 2007; Kuusikko et al.

2009), although results remain inconsistent (Adolphs et al.

2001; Gepner et al. 2001). A number of studies have

investigated whether the impairment in emotional face

recognition applies to all basic emotions or is specific to

certain emotion categories. Results of these studies sug-

gests that ASD individuals are predominantly impaired in

recognizing negative emotions (e.g., sadness, anger or

fear), whereas deficits in the recognition of happy faces

seem to be less robust (for a recent review see Harms et al.

2010; but see also Wright et al. 2008; Humphreys et al.

2011).

Facial identity recognition in ASD has also been

extensively studied. Again, results are inconclusive: while

a number of studies have found impairments (Klin et al.

1999; Wolf et al. 2008; Weigelt et al. 2012), others report

intact facial identity recognition skills (Deruelle et al.

2004; Celani et al. 1999). It is of interest that even in

studies reporting intact performance, subtle peculiarities in

face identity processing were often revealed. For example,

a number of these studies found that ASD subjects do not

show a decrement in performance when asked to identify

inverted faces, which can be typically found in controls

(Langdell 1978; Hobson et al. 1988; but see Weigelt et al.

2012).

Inconsistent findings on face processing abilities in ASD

might be due to methodological differences between the

studies. An important factor that might influence results is

the specification of ASD subjects that were included. While

many studies with low-functioning subjects with ASD

reported deficits in face processing (Celani et al. 1999;

Hobson 1986), studies with high-functioning ASD subjects

often found intact face processing skills (Adolphs et al.

2001) or detected only deficits in more demanding condi-

tions, e.g., inferring emotional states from the eye region

(Baron-Cohen et al. 1997). Differential findings for ASD

subtypes are in line with studies that found that face pro-

cessing abilities and autism severity are negatively corre-

lated (Uono et al. 2011; Bal et al. 2010). Importantly, the

vast majority of studies that have found intact abilities in

facial identity and emotion recognition in individuals with

ASD only reported accuracy rates (and not response times).

This approach might not be sensitive enough to detect

abnormalities in face processing in high-functioning ASD

subjects due to ceiling-effects. Finally, inconclusive data

on face processing skills in ASD might also be related to

differences between the age groups investigated. The latter

might be particularly important when assessing ASD, as

there is evidence for deviant developmental trajectories of

face processing in affected subjects. Although data are

scarce, results from a small number of cross-sectional

studies suggest that ASD individuals show no or less age-

dependent improvement in face processing abilities beyond

late childhood compared to typically developing individ-

uals (O‘Hearn et al. 2010; O’Connor et al. 2005; Rump

et al. 2009). Consequently, studies may have found intact

or deficient face recognition abilities in ASD depending on

the age group investigated.

In typically developing (TD) individuals, face process-

ing skills continue to improve after the childhood years

(Herba 2004), although the ability to discriminate faces and

facial emotions emerges early in live (Walker-Andrews

1997; Blass and Camp 2004). The majority of studies on

typical development in face processing have focused on

infancy and early childhood. However, the limited number

of studies examining age-related influences on the ability to

read faces beyond childhood suggests increased accuracy

and faster processing of facial expressions and identity

from childhood to adolescence (Carey et al. 1980;

O’Connor et al. 2005; Batty and Taylor 2006; Thomas

et al. 2007; but see, e.g., Durand et al. 2007). The

improvement in identity and facial emotion recognition in

TD individuals beyond the childhood period is closely

paralleled by age-related structural and functional changes

in brain structures involved in face processing (Aylward

et al. 2005; Wang et al. 2006; Greimel et al. 2010). For

example, is has been shown that the fusiform gyrus grad-

ually increases in size and becomes more face selective

from childhood to adulthood (Peelen et al. 2009). By

contrast, studies in ASD subjects have shown that matu-

ration of temporal brain structures subserving face pro-

cessing is disrupted in affected adolescents and adults

(Wallace et al. 2010; Raznahan et al. 2010; Lee et al.

2007). Taken together with behavioural studies reporting a

lack of age-related improvement of face processing skills

in ASD, these findings underscore the importance of

studies that take a developmental perspective. Comparing

face processing abilities in ASD individuals to the typical

course of development provides important further insights

into the developmental trajectory of these skills in affected

persons. Such approaches might also be helpful to identify

critical time periods when intervention is particularly

important for individuals with ASD.

The aims of the present study were twofold. First, we

aimed to extend previous studies on face processing in

high-functioning ASD subjects in a large and homogenous

sample covering a wide age-range. Second, we aimed to

characterize the developmental course of face processing

abilities in ASD relative to typical development. We

included ASD and control subjects aged 13–49, thereby

extending the age range that has been typically investigated

in studies of face recognition in ASD. Additionally, a

group of younger TD children was included to address the

question whether face processing abilities in ASD follow a

delayed developmental course relative to TD individuals.

To comprehensively assess face processing skills, an

E. Greimel et al.

123

emotional face recognition and an face identity recognition

task were employed.

Based on previous studies in ASD adolescents and

adults (Boraston et al. 2007; Kirchner et al. 2011; Bor-

mann-Kischkel et al. 1995), we hypothesized that subjects

with ASD would show deficits in the ability to process both

facial identity and emotion. Moreover, in line with previ-

ous studies on age-related changes in face processing in

ASD (O’Connor et al. 2005; O‘Hearn et al. 2010), we

expected that these deficits follow a delayed developmental

pattern relative to TD individuals.

Methods

Participants

A total of 93 male subjects participated in the study. The

sample included 38 adolescents and adults with ASD (ASD

group), and 37 TD adolescents and adults (control group).

In addition, 18 TD children between the ages of 8 and 12

were investigated. Only subjects with an IQ C 80 (WISC-

III (Wechsler 1991) or WAIS-III (Wechsler 1997) were

included. Groups did not differ in IQ. Moreover, there were

no significant differences in age between ASD subjects and

controls (see Table 1 for demographic characteristics).

ASD individuals had been diagnosed by experienced cli-

nicians according to ICD-10 (World Health Organization

1993) and DSM-IV (American Psychiatric Association

1994) for Asperger’s syndrome or high-functioning autism.

Diagnoses were confirmed by the Autism Diagnostic

Observation Schedule-Generic (ADOS-G) (Lord et al.

2000; Ruehl et al. 2004), which was conducted by certified

examiners (E. G.; I. K.-B.). In adolescents with ASD,

autism-specific assessment additionally included a semi-

structured parent interview (Autism Diagnostic Interview-

Revised; conducted by E. G.; I. K.-B.) (LeCouteur et al.

1989; Boelte et al. 2006a) and the Social Communication

Questionnaire (Rutter et al. 2003; Boelte and Poustka

2006). Adults with ASD additionally completed the Autism

Spectrum Questionnaire (Baron-Cohen et al. 2001) (see

Table 2 for clinical characteristics).

In ASD subjects aged \18 years, comorbid psychopa-

thology was screened using the Child Behavior Checklist

(CBCL) (Achenbach 1993) and the FBB-HKS (German

parental report on ADHD symptoms) (Doepfner et al.

1994). In ASD subjects aged C18 years, the Brief Symp-

tom Inventory (Derogatis 1993) and the ADHD Behavior

Checklist for Adults (Murphy and Barkley 1995) were

used. Moreover, in all ASD individuals comorbidity was

assessed based on an extensive psychiatric, psychological

and neurological examination. With regard to psychiatric

Table 1 Demographic characteristics (M, SD) of the study sample

TD

children

(n = 18)

Control group

(n = 37)

ASD group

(n = 38)

Group

difference

Age 10.5 (1.3) 20.6 (7.0) 21.1 (9.5) p \ 0.05a

Age

range

8.1–12.4 13.1–46.9 13.0–49.6

IQ 111.7

(15.6)

113.0 (10.2) 107.7 (13.2) n.s.

IQ

range

83–139 89–133 81–139

TD typically developing, ASD autism spectrum disordera Note that there was no significant difference in age between TD and

ASD adolescents or TD adults and ASD adults

Table 2 Clinical characteristics (M, SD) of the study sample

TD

children

Control

group

ASD

group

ADOS-G total n.a. n.a. 11.5

(3.9)

Communication n.a. n.a. 3.9 (1.9)

Social interaction n.a. n.a. 7.6 (2.3)

ADI-Ra

Social interaction n.a. n.a. 17.3

(5.2)

Communication n.a. n.a. 13.4

(4.5)

Restricted behaviors n.a. n.a. 6.3 (3.0)

Onset \36 months n.a. n.a. 2.0 (1.5)

SCQ totala 4.3 (3.2) 2.7 (2.0) 21.0

(7.4)

AQb n.a. 15.6 (4.6) 32.2

(10.3)

FBB-HKSa,c

Inattention 1.2 (1.3) 0.3 (1.3) 5.8 (2.6)

Hyperactivity 0.2 (0.5) 0.1 (0.3) 3.0 (2.6)

Impulsivity 0.2 (0.4) 0.3 (0.7) 2.2 (1.4)

ADHD behavior checklist for adultsb

Inattention n.a. 4.7 (2.9) 8.3 (4.8)

Hyperactivity/Impulsivity n.a. 4.2 (3.0) 6.6 (3.4)

CBCL total T-scorea 52.9

(9.8)

50.4 (13.8) 73.2

(7.8)

BSI positive symptom distress

indexbn.a. 1.3 (0.3) 1.6 (0.8)

n.a. not applicable, TD typically developing, ASD autism spectrum

disorder, ADOS-G Autism Diagnostic Observation Schedule-generic,

ADI-R Autism Diagnostic Interview-Revised, SCQ Social Commu-

nication Questionnaire, AQ Autism Spectrum Questionnaire, FBB-

HKS Fremdbeurteilungsbogen fur hyperkinetische Storungen (Ger-

man parental report on ADHD symptoms), CBCL Child Behavior

Checklist, BSI Brief Symptom Inventorya This instrument was only applied in subjects aged \18 yearsb This instrument was only applied in subjects aged C18 yearsc Number of elevated items

Face processing in autism spectrum disorder

123

comorbidities, n = 4 subjects showed symptoms of ADHD

and n = 1 subject had been diagnosed with chronic tic

disorder, and n = 1 subject with depressive disorder.

Seven participants were medicated at the time of testing

(atomoxetine n = 2; atypical neuroleptics n = 3, typical

neuroleptics n = 1; antidepressant medication n = 1).

Since the inclusion of these participants did not change the

result pattern, findings are reported based on the full

sample. If subjects received stimulants (n = 3), these were

discontinued 48 h before testing.

TD subjects were extensively screened to exclude psy-

chiatric disorders using a semi-structured interview (K-

SADS-PL) (Kaufman et al. 1997) and the Child Behavior

Checklist (Achenbach 1993) for subjects aged \18 years

and the Brief Symptom Inventory (Derogatis 1993) for

subjects aged C18 years. Moreover, in TD subjects, ASD

symptoms were screened using the Social Communication

Questionnaire (Rutter et al. 2003; Boelte and Poustka

2006) for participants aged \18 years and the Autism

Spectrum Questionnaire (Baron-Cohen et al. 2001) for

participants aged C18 years. ADHD symptoms were

screened in TD subjects based on the FBB-HKS (Doepfner

et al. 1994; in subjects\18 years) and the ADHD behavior

checklist for adults (Murphy and Barkley 1995; in subjects

C18 years). Descriptive data from clinical questionnaires

are summarized in Table 2.

The study was approved by the institutional review board

of the University Hospital of the RWTH Aachen and has been

performed in accordance with the Declaration of Helsinki. All

participants were informed in detail about the aims and the

protocol of the study and provided written informed consent

(participants C18) or assent (participants \18). For partici-

pants\18, additional written informed consent was obtained

by the parents/legal custodians, after the parents/legal custo-

dians had been informed about all aspects of the study.

Procedure

A standardized computerized assessment was conducted

based on two tasks from an established neuropsychological

test battery (DeSonneville 2001). The testing procedure

lasted about 15 min. All participants received identical

spoken instructions. To make sure that all participants were

able to perform the tasks, all tasks were preceded by

standardized practice trials.

Measures

Face identity recognition

Face identity recognition skills were assessed using the

face recognition (FR) task from the Amsterdam Neuro-

psychological Task battery (DeSonneville 2001). The face

stimulus set of this task consisted of color photographs of

20 individuals (5 boys, 5 girls, 5 men 5 women) with a

neutral expression. The task involved the continuous

presentation of 40 target faces (target duration 2.5 s), each

followed by a post-target interval of 500 ms and a display

set of four faces. Each individual photograph was pre-

sented twice as a target picture. The age and the gender of

the faces shown in the display set always matched the age

and gender of the target face. Participants were instructed

to push the ‘yes’ button of a mouse with the dominant

hand whenever the target was presented in the display set

(20 target trials) and to press the ‘no‘ button with the non-

dominant hand if the target was absent in the consecutive

display set (20 non-target trials). The display set disap-

peared from the screen when a response was given, i.e.,

the display duration was identical with the reaction time.

The post-response interval was set to 1,000 ms.

Dependent measures of the FR task included mean

reaction times (RT) of hits in target trials and the total

number of errors (false alarms and misses).

Identification of facial emotion

Emotional face recognition skills were assessed using the

Identification of Facial Emotion (IFE) task from the

Amsterdam Neuropsychological Task battery (DeSonne-

ville 2001). In each of four emotion conditions (happy, sad,

angry and fearful), subjects were first shown a face

expressing the target emotion for 2,500 ms. After a post-

target interval of 500 ms, emotional face stimuli were

shown and subjects had to press the ‘yes‘ button with the

dominant hand whenever a face with the target expression

appeared (20 target trials) and to press the ‘no‘ button with

the non-dominant hand if a face with a non-target emo-

tional expression appeared (20 non-target trials). The face

stimulus set of this task consisted of color photographs of

four individuals (2 males, 2 females), each showing the

four emotions. The face expressing the target emotion also

appeared in the following series of emotional faces. The

four individuals presented in IFE task overlapped with four

(of 20) individuals expressing a neutral face in the FR task.

Face stimuli remained on the screen until a response key

was pressed. Thus again, the display duration was variable

and identical with the reaction time. The post-response

interval was 1,000 ms.

Dependent measures of the IFE included mean RTs of hits

in target trials and the total number of errors (false alarms,

misses), both separately for the four emotion conditions.

Statistical analysis

The data were analyzed using SPSS 16 (SPSS Inc. 2008). A

one-way multivariate analysis of variance (MANOVA) with

E. Greimel et al.

123

group (ASD, control group) as between-subject factor was

conducted for the parameters (RT, errors) of the FR task. For

the parameters of the IFE task (RTs, errors for the four

emotion conditions), a two-way repeated measures MA-

NOVA with group (ASD, control group) as between-subject

factor and emotion (happy, sad, angry, fearful) as within-

subject factor was calculated. A multivariate approach was

chosen for the analysis of task performance in the FR and

IFE, respectively, since the parameters within the tasks

correlated substantially (p \ 0.05) across subjects.

MANOVAs were followed by univariate analyses of

variance (ANOVAS). Where appropriate, degrees of free-

dom were adjusted using Greenhouse-Geisser’s procedure.

Effect sizes were calculated using partial eta square (gp2). If

significant emotion or interaction (group by emotion)

effects in the ANOVA were obtained, further post hoc

comparisons were conducted adjusting p values (p0)according to the Holm procedure.

In the case of worse performance of the ASD group in

FR or IFE parameters compared to controls, we examined

whether these group differences can be accounted for by a

developmental delay in the ASD group. For this purpose,

the control and the ASD group were compared to the group

of TD children using independent t tests, again applying

Holm’s adjustment for multiple comparisons for parame-

ters of the FR and IFE task, respectively.

To examine the possibility of linear and quadratic age-

related changes in face processing abilities within the

groups of adolescent and adult ASD and control subjects,

respectively, linear and quadratic regression curve fitting

analyses were conducted for parameters of the FR and IFE

(separately for both groups). To reduce the number of

comparisons, these analyses were restricted to the follow-

ing parameters: RT and errors in the FR task, RT and errors

in the IFE task collapsed across emotion conditions. Again,

Holms procedure was used to adjust for multiple testing.

Results

Group differences between controls and ASD subjects

Face identity recognition

Descriptive data for all FR parameters are summarized in

Figs. 1 and 2. The MANOVA for the two parameters of the

FR (RT, errors) task revealed a significant main effect of

group (F(2, 72) = 17.0, p \ 0.001, gp2 = 0.31). In follow-

up ANOVAs, significant group differences emerged for RT

(F(1, 73) = 9.8, p \ 0.01, gp2 = 0.12) and the number of

errors (F(1, 73) = 25.0, p \ 0.001, gp2 = 0.26), with faster

RTs and less errors in controls compared to ASD

individuals.

Identification of facial emotions

Mean IFE parameters are summarized in Figs. 3 and 4. The

MANOVA for the IFE parameters (RTs, errors) revealed a

significant main effect of group (F(2, 72) = 13.0, p \ 0.001,

gp2 = 0.27) and emotion (F(6, 68) = 54.9, p \ 0.001,

gp2 = 0.83). Moreover, the interaction group by emotion was

found to be significant (F(6, 68) = 3.2, p \ 0.01, gp2 = 0.22).

In the follow-up ANOVA for RT in the IFE, a signifi-

cant main effect of group (F(1, 73) = 8.3, p \ 0.01,

gp2 = 0.10) emerged, with faster RTs in the control com-

pared to the ASD group. Moreover, a significant main

effect of emotion (F(2.6, 188.0) = 54.5, p \ 0.001,

gp2 = 0.43) was revealed. The interaction group by emotion

was found to be significant (F(2.6, 188.0) = 3.4, p \ 0.05,

gp2 = 0.04). Post-hoc comparisons (applying the Holm

adjustment for multiple comparisons) of the four emotions

showed that, irrespective of group, RTs to happy faces

were faster compared to sad, angry and fearful faces (all

p’s \ 0.05). RTs for sad faces were significantly slower

compared to fearful faces (p0\ 0.05). To follow up the

interaction between group and emotion, the ASD and

control group were compared for each of the four emotion

categories using independent t tests (again applying the

Holm adjustment). These analyses revealed that TD control

subjects responded faster to angry and fearful faces (all

p’s \ 0.05) than ASD individuals, whereas performance of

Fig. 1 Reaction times in the face recognition (FR) task. TD typically

developing, ASD autism spectrum disorder

Fig. 2 Errors in the face recognition (FR) task. TD typically

developing, ASD autism spectrum disorder

Face processing in autism spectrum disorder

123

the two groups were comparable for the remaining emotion

categories (p’s [ 0.05) (see Fig. 3).

The univariate test procedure for the number of errors

revealed a significant main effect of group (F(1,

73) = 17.4, p \ 0.001, gp2 = 0.19); ASD subjects com-

mitted more errors compared to controls. Moreover, a

significant main effect of emotion (F(2.5, 182.2) = 51.3,

p \ 0.001, gp2 = 0.41) emerged. Irrespective of group,

subjects were more accurate in the happy emotion condi-

tion compared to the other emotion conditions (all

p’s \ 0.05). Sad faces were recognized worse than angry

and fearful faces (all p’s \ 0.05). Moreover, angry faces

were recognized worse than fearful faces (p0\ 0.05).

The interaction effect group x emotion also proved to be

significant (F(2.5, 182.2) = 4.1, p \ 0.05, gp2 = 0.05). To

further investigate the interaction between group and

emotion, the two groups were compared for each of the

four emotion categories using independent t tests. These

analyses revealed that TD control subjects made less error

in the three negative emotion categories (all p’s \ 0.05),

whereas no group difference emerged for the happy emo-

tion condition (p0[ 0.05) (see Fig. 4).

Comparison of ASD and control subjects with TD

children

Face identity recognition

RTs in the FR task did not differ between TD children and

the ASD group (t(54) = 1.2, p0[ 0.05). By contrast,

comparison of TD children and the TD control group

revealed significantly faster RTs in the older age group

(t(20.7) = 4.3, p0\ 0.05). While the number of errors in

the FR task was comparable between TD children and the

ASD group (t(44.9) = -0.3, p0[ 0.05), significant dif-

ferences emerged between the TD groups, with less errors

in TD adolescents and adults (t(20.2) = 4.5, p0\ 0.05; for

descriptive statistics, see Figs. 1 and 2).

Identification of facial emotions

RT to angry (t(49.7) = -1.1; p0[ 0.05) and fearful faces

(t(54) = 0.7; p0[ 0.05) were comparable between TD

children and the ASD group. By contrast, the TD control

group responded faster to both angry (t(53) = 4.9;

p0\ 0.05) and fearful faces (t(25.9) = 3.7; p0\ 0.05) than

TD children. Similarly, while the number of errors for all

three negative emotion conditions did not differ between

TD children and the ASD group (tsad(54) = 1.0;

tangry(54) = 0.6; tfear(54) = 0.5, all p’s [ 0.05), the older

TD group outperformed the younger TD group in all

three parameters (tsad(53) = 4.1; tangry(22.9) = 3.9;

tfear(53) = 3.8; all p’s \ 0.05; for descriptive statistics, see

Figs. 3 and 4).

Linear and quadratic effects on age on face processing

performance

In the control group, no linear or quadratic relationships

between age and performance in the FR (errors and RT)

and IFE task (errors and RT collapsed across emotions)

were found (all p’s [ 0.05). In the ASD group, a positive

linear relationship between age and RT in the IFE task was

revealed (r = 0.30, p = 0.047; p [ 0.05 for linear or

quadratic effects of age on all remaining parameters)

indicating slowing of RTs with increasing age. However,

after correcting for multiple comparisons, this correlation

was non-significant.

Discussion

The aim of the present study was twofold. First, we sought

to extend previous studies on face processing in ASD.

Second, we aimed to explore whether deficits in face

Fig. 3 Reaction times in the identification of facial emotion (IFE)

task for the four emotion conditions. TD typically developing, ASD

autism spectrum disorder

Fig. 4 Errors in the identification of facial emotion (IFE) task for the

four emotion conditions. TD typically developing, ASD autism

spectrum disorder

E. Greimel et al.

123

processing abilities in ASD individuals might reflect a

developmental delay relative to TD subjects.

In sum, we found evidence for deficits in face identity

recognition abilities and the identification of facial emo-

tions in the ASD compared to the control group. Perfor-

mance in ASD adolescents and adults was similar to a

group of TD children, suggesting that face processing

abilities in ASD follows a delayed developmental

trajectory.

Group differences in face processing between controls

and ASD subjects

Our findings on deficits in face identity recognition and

identification of facial emotions in ASD individuals add to

the growing body of literature on face processing abnor-

malities in ASD. Sample sizes of previous studies were

often small (but see Klin et al. 1999) and restricted to a

narrow age range. Moreover, the interpretation thereof was

further complicated by insensitive methodological

approaches. Our study included a large number of subjects

and extended the age range that has been typically inves-

tigated in studies of face processing in ASD to solidify and

extend previous results.

In the FR task, ASD subjects were slower and commited

more errors compared to TD adolescents and adults. Def-

icits in the ability to process facial identity in ASD have

been previously reported (Boucher and Lewis 1992; Klin

et al. 1999; Kirchner et al. 2011; Weigelt et al. 2012).

Previous studies have demonstrated that these deficits are

domain-specific and cannot be explained by impaired

attentional processes or general cognitive abilities (Bou-

cher and Lewis 1992; Klin et al. 1999). A number of

studies have also reported intact abilities in facial identity

recognition (Celani et al. 1999; Deruelle et al. 2004; Krebs

et al. 2011). However, most of these studies did only report

error parameters or used a face-matching task. Both

approaches might not be sensitive enough to capture

impairments in relatively able subjects with ASD, espe-

cially in studies with small sample sizes.

Various studies have shown that ASD subjects process

faces differently from healthy subjects. Evidence from

behavioural studies and studies using eye-tracking suggest

that ASD individuals tend to focus more on the lower (i.e.,

the mouth) than on the upper part of the face, whereas TD

subjects predominantly focus on the eye region (Dalton

et al. 2007; Langdell 1978; Neumann et al. 2006). As the

eye region provides the most salient information about a

person’s identity, this peculiarity may in part explain

problems of ASD persons in recognizing faces. Moreover,

some studies have shown that, unlike TD persons (Rossion

2002), ASD individuals do no not show a decrease in

performance when asked to recognize faces upside down

(Tantam et al. 1989; Hobson et al. 1988). Because the

recognition of inverted faces relies predominantly on the

extraction of local features, the absence of a ‘‘face inver-

sion effect’’ in ASD has been taken as evidence for a local

and less holistic processing style (but see, e.g., Lahaie et al.

2006 and the review from Weigelt et al. 2012 for con-

flicting results on the face inversion effect), which is pre-

sumed to be less effective when recognizing faces.

In the IFE task, ASD subjects exhibited longer RTs to

fearful and angry faces compared to controls. Moreover,

ASD subjects committed more errors in the negative

emotion conditions of the IFE than TD controls. Our results

are in line with a large body of literature showing impaired

performance in ASD individuals in emotional face recog-

nition (for a review see Harms et al. 2010). It is of interest

that some studies have also found that ASD individuals are

as accurate as TD subjects in recognizing emotional

expressions. As the majority of these studies included

adults with high-functioning ASD (Adolphs et al. 2001;

Neumann et al. 2006), it has been claimed that these

individuals may have developed compensatory mecha-

nisms for processing faces (Harms et al. 2010). Compen-

satory mechanisms in ASD individuals might explain the

longer RTs in the ASD group in the IFE task, as such

compensatory processes may involve explicit verbal or

cognitive strategies to recognize emotional expressions in

contrast to a more intuitive, rapid and automatic processing

style in TD subjects. In support of this claim, a number of

studies have shown that in ASD, general cognitive and

language abilities are more strongly related to performance

in emotional face recognition than in TD individuals (Dyck

et al. 2006). Our finding that ASD subjects committed

more errors in negative emotion conditions but not in the

happy emotion condition might also support the idea that

affected subjects may possess compensatory mechanisms

for processing emotional faces: unlike negative emotional

expressions, a happy face can be identified on a rule-based

strategy to focus on the angle of a mouth. Moreover, the

differential results for the negative and positive emotion

conditions may also pertain to the fact that three negative

emotional expressions were presented in the IFE task along

with only one positive face. This may have resulted in

more difficulties (particularly for ASD subjects) in cor-

rectly recognizing the negative faces, as finer distinctions

had to be made for these emotion categories.

Face processing in typically developing controls

and in ASD subjects: a developmental perspective

TD adults and adolescents outperformed TD children in

parameters of the FR and IFE task. Our findings challenges

the older view that by late childhood, face processing abili-

ties reach adult levels (e.g., Durand et al. 2007) and are in line

Face processing in autism spectrum disorder

123

with other studies showing that face processing abilities

continue to develop well into adolescence (Carey et al. 1980;

O’Connor et al. 2005; Batty and Taylor 2006; Thomas et al.

2007). Several cognitive and neuropsychological explana-

tions have attempted to explain age-related changes in face

identity recognition and decoding of emotional faces during

childhood and adolescence. Among approaches focusing on

cognitive aspects, a prominent explanation is that children

and adolescents rely more strongly on configural compared

to featural processing of faces with increasing age. Among

other lines of evidence, support for this assumption is pro-

vided by studies showing that the face inversion effect

increases with age (Mondloch et al. 2002; Baudouin et al.

2010; but see also Crookes and McKone 2009).

Within the group of TD adults and adolescents, we

found no evidence of further age-related changes in the

ability to identify faces and recognize emotional expres-

sions. Thus, by adolescence, behavioral performance in

face processing seems to reach adult levels. This result is

consistent with previous findings which also show stability

of performance in the identification of faces and the rec-

ognition of prototypical emotional expressions from ado-

lescence into adulthood (Kolb et al. 1992; Greimel et al.

2010). Importantly, however, a number of studies suggest

that developmental changes in more fine-grained face

processing abilities (e.g., decoding of the intensity of an

emotional expression or recognition of mixed emotional

expressions) may also occur beyond the adolescent period

(Thomas et al. 2007; Rump et al. 2009). Moreover, the

absence of age-related differences on the behavioral level

does not exclude the possibility of developmental changes

in the neural substrates underlying face processing in TD

individuals. Indeed, evidence from functional and struc-

tural neuroimaging studies suggest that neural networks

known to be involved in the decoding of (emotional) faces

(e.g., the amygdala, the fusiform gyrus) continue to mature

from adolescence into adulthood (Aylward et al. 1999;

Monk et al. 2003; Guyer et al. 2008).

Comparison of the ASD group with TD children revealed

that both groups performed equally on all face parameters in

which TD controls outperformed ASD individuals. This

finding implies that ASD subjects lag behind typical devel-

opment in the domain of face processing suggesting that face

abnormalities in ASD can be interpreted in terms of a

developmental delay. The notion of a developmental delay in

the ability to process faces in ASD is supported by recent data

from cross-sectional neuroimaging studies which show

atypical maturation of face sensitive brain regions in ado-

lescents affected by the disorder (Raznahan et al. 2010; Lee

et al. 2007; Wallace et al. 2010).

An important question that arises from our results is

whether comparable performance in the FR and IFE task in

young TD subjects and older ASD individuals also reflect

similar face processing mechanisms in both groups. Based

on studies in ASD (Tantam et al. 1989; Hobson et al. 1988)

and on developmental studies in TD individuals (Baudouin

et al. 2010; Mondloch et al. 2002), it seems plausible that the

processing style in both groups might be characterized by a

focus on facial features and to a lesser extent on configural

information in the face. However, this claim remains spec-

ulative and future developmental studies in ASD children

and adults that use tasks like the face inversion paradigm or

the composite face paradigm (Young et al. 1987) are needed

to further shed light on the delayed developmental pattern of

face processing abilities in ASD.

Within the group of ASD adolescents and adults, no

improvement of face processing abilities was evident with

increasing age. Indeed, there was a tendency that older

ASD subjects even exhibited longer RTs compared to

younger ones (not significant after correction for multiple

comparisons). In line with the compensation hypothesis,

one might speculate that subjects with ASD become more

aware of their deficits with increasing age and thus, meta-

cognitive strategies are more commonly applied during

tasks which are known to be difficult resulting in a more

cognitively controlled processing of faces and slower RTs.

Taken together, the results of our study are in accordance

with other studies showing that face processing in ASD does

not improve during the adolescent period (O’Connor et al.

2005; Rump et al. 2009; but see Kuusikko et al. 2009). In this

regard, it is worth stressing that the term ‘‘delay’’ used to

describe the result pattern of face processing in ASD subjects

in the present study does not imply that these individuals

catch up at some point of development, albeit some indi-

viduals may develop cognitive strategies to cope with their

impairments in identifying and reading faces.

It is yet unexplored which environmental factors might

impact on the developmental trajectory of face processing

in ASD. As similarly advocated by O’Hearn et al. (2010),

the apparent lack of improvement with increasing age

reported in a number of cross-sectional studies might in

part reflect that younger subjects with ASD may have

benefited from early intervention, whereas many adults

with ASD had been diagnosed late and had received only

limited support. Future longitudinal studies including

clinical trials are needed to further examine the develop-

mental trajectory of face processing in ASD and to assess

the impact of early intervention programs targeting deficits

in the ability to identify faces and facial emotions.

Limitations

Only ASD subjects with an IQ above 80 were studied to

allow for homogenous groups. By necessity, the general-

izability of our findings to the whole spectrum of autistic

E. Greimel et al.

123

disorders may be limited. Moreover, in future studies, it

would be important to also include children with ASD to

further gain insight into the developmental course of face

processing in ASD.

The FR task used in the present study resembles a 1-back

task and thus draws on working memory processes. Although

several studies have shown that ASD subjects are unimpaired

in n-back tasks (for a review see Kenworthy et al. 2008),

future studies should include a control condition where

objects/no face stimuli are presented to control for unspecific

(cognitive) processes. On a related note, future studies

should include a neutral condition in the emotional face

recognition task to rule out the possibility that the results

obtained might be explained by the mere presence of face

stimuli and not to the emotional expression per se.

Conclusions

Our findings corroborate and extend previous studies

showing that ASD is characterised by broad impairments in

the ability to process faces. These impairments seem to

reflect a developmentally delayed pattern relative to healthy

individuals that remains stable throughout adolescence and

adulthood. Longitudinal studies spanning a wide age range

are needed to further elucidate the developmental trajectory

of face processing and its underlying neural mechanisms in

ASD. In such studies, it would be particularly important to

examine the impact of intervention programs targeting social

impairments and face recognition abilities in individuals

affected by the disorder (Boelte et al. 2006b).

Acknowledgments We are grateful to all participants with their

families who took part in this study.

Conflict of interest B. H.-D. receives industry research funding

from Vifor Pharma. K. K. received speaking fees from Novartis and

Medice. All other authors declare that they have no conflicts of

interest.

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