The development of facial gender discrimination in typically. developing individuals and individuals with autism

Transcription

1 Gender 1 Running head: GENDER DISCRIMINATION AND AUTISM The development of facial gender discrimination in typically developing individuals and individuals with autism Mark S. Strauss 1, Lisa C. Newell 2, Joyce Giovannelli 1, Catherine A. Best 1, Nancy J. Minshew 1 1 University of Pittsburgh 2 Florida International University In Submission

2 Gender 2 Abstract The current study examined the effect of exemplar typicality and the presence of hair cues on reaction time and accuracy to discriminate facial gender. High-functioning children (ages 5-7 and 8-12), adolescents (age 13-16), and adults with autism (age 17-48) and matched controls were tested with naturalistic videos on their ability to discriminate gender. Both groups showed improved abilities to discriminate gender with development. However, while typically developing children reached a level of expertise similar to the adults by 8 to 12 years of age, individuals with autism never reached this level of expertise, even as adults. The results are discussed in terms of potential differences in the type of processing that may be required for discriminating typical and atypical exemplars of gender. Parallels are also drawn to the results of previous studies of categorization of objects in individuals with autism.

3 Gender 3 Autism is a pervasive developmental disorder with onset prior to age three. It is characterized by qualitative impairments in social interaction and communication, as well as the presence of restricted, repetitive, and stereotyped patterns of behavior, interests and activities. Recent epidemiological evidence suggests that the incidence of pervasive developmental disorder in the general population ranges from 1 in 300 to as high as 1 in 200 (Fombonne, 2003). While the intellectual functioning of individuals with autism varies widely, they all demonstrate reciprocal social difficulties that have a substantial impact on their ability to interact with other people, and in particular, their ability to perceive and interpret social information. One aspect of this impairment identified relatively recently is their capacity to perceive and recognize facial information (Dawson, Webb, McPartland, 2005; Schultz, 2005). These studies indicate that, by at least middle childhood, people with autism have significant deficits in perceiving faces (Grelotti, Gauthier, & Shultz, 2002; Joseph & Tanaka, 2002; Deruelle, Rondan, Gepner, & Tardif, 2004) and consequently demonstrate difficulties relative to typically developing children and adults in recognizing facial identity (Langdell, 1978; Hobson, 1986; Hobson, Ouston, & Lee, 1988; Boucher & Lewis, 1992; Teunisse & Degelder, 1994; Klin, et al., 1999; Dawson, et al., 2002). How early do these difficulties in perceiving and remembering faces develop? It is known that typically developing infants from birth appear to have a preference for normal facelike patterns compared to random arrangements of facial features and that facial recognition abilities emerge within the first six months of life (Barrera & Maurer, 1981; Easterbrook, Kisilevsky, Muir, & Laplante, 1999; Johnson 1999; Mondloch, et al., 1999; Bushnell 2001; Cohen & Cashon, 2001; de Haan, Johnson, Maurer, Perrett, 2001). Thus, it is logical to assume that face processing deficits in children with autism emerge very early. Unfortunately, there are

4 Gender 4 very few behavioral studies of face processing abilities in young children with autism, although it is clear that deficits do exist by at least the age of seven years (Dawson, et al., 2005). Research with typically developing infants and children has also demonstrated that, while facial perceptual and recognition abilities emerge during infancy, children continue to acquire expertise in processing faces throughout most of childhood. For example, it is not until adolescence that children recognize faces as well as adults (Carey, Diamond, & Woods, 1980; Bruce, et al., 2000). Several studies suggest that, to some extent, children s developing expertise at perceiving and remembering faces can partially be explained by changes in the way younger versus older children process faces. With development, typically developing children slowly shift from a predominant reliance on processing featural aspects of faces to having adult expertise at processing configural or spatial aspects of faces (Mondloch, Le Grand, Maurer, 2002; Mondloch, Dobson, Parsons, & Maurer,2004; Schwartzer, Huber, & Dummler, 2005). However, there are no autism face studies that carefully compare children of different ages to determine if, with development, there is any improvement in face processing abilities. While this lack of developmental data is due in part to difficulty recruiting sufficient numbers of individuals with autism, it is also because the vast majority of existing studies have focused exclusively on facial recognition abilities. Within a face recognition task, it is difficult to separate developmental changes in how faces are processed from what may be general improvements in memory. It is also difficult to equate parameters such as study time, numbers of stimuli, and general procedures for children of very different ages. In contrast a relatively simple aspect of face perception that can readily be studied in younger children, older children and adults, is the ability to discriminate facial gender. To test

5 Gender 5 gender discrimination, participants must merely be able to indicate whether they perceive a face as male or female a task that is suitable for any aged verbal child. Adults are very good at classifying the gender of faces, and they do so very quickly (O' Toole, et al., 1998). The discrimination of facial gender is based on a very fine-grained discrimination of the features that are maximally distinctive between male and female faces. These features include, among others, nose length, chin width, and eye to eyebrow distance (Brown & Perrett, 1993; Chronicle et al., 1995; Yamaguchi, Hirukawa, & Kanazawa, 1995). Not only are adults very good at classifying gender, they are also quicker to identify the gender of a face, if that face has been rated as being very typical of its gender. For instance, a male face that has been rated by adults as being very masculine is classified as male in a gender identification task significantly faster than a male face that has been rated as being somewhat less masculine (O Toole et al., 1998). This typicality effect may also be explained according to what Valentine (2001) has called the face-space framework. Research with adults has suggested that we store faces in a multidimensional space that Valentine has labeled a face space. This framework is proposed to be an n-dimensional space representing all possible aspects of a face that includes both features (e.g., noses) and configural information (e.g., eye separation) within a normal distribution of faces. The center of this space represents the central tendency or prototype of all facial features. Faces with more typical features lie closer to the center than faces that contain distinctive features. This model has been used successfully to explain several known aspects of face processing including why distinctive faces are remembered better then typical faces; why caricatures are remembered better then veridical representations of faces; and why faces of one s own racial group are remembered better than groups with which someone has had little experience.

6 Gender 6 O Toole et al. (1998) further suggests that individuals actually store faces according to two gender-specific prototypes. The distance of a particular face from the prototype is indicative of how masculine/feminine a face is. Hence, faces that are more gender-typical are closer to the prototype and more quickly classified. Studies with adults also indicate that the information that must be perceived in order to discriminate facial gender is very similar to the information used for recognizing identity (Rossion, 2002; Rossion, Gauthier, Goffaux, Tarr, & Crommelinck, 2002; Schyns, Bonnar, & Gosselin, 2002; Bulthoff & Newell, 2004). Similarly, neuroimaging studies indicate that facial identity and gender discrimination both activate common areas of the fusiform gyrus (Rossion, 2002). Thus, for several reasons, gender discrimination or categorization tasks provide an excellent way of studying the development of face expertise. First, facial gender categories have a typicality distribution and thus allow researchers to investigate children s developing perception of typicality and, hence, their developing face-space model. Second, since common information must be perceived in both gender discrimination and identity tasks, it provides a simple way of studying the development of critical aspects of facial perception. Third, the stimuli used for gender discrimination tasks can be very naturalistic. That is, actual videos of people can be used as stimuli. Finally, gender categorization tasks do not tax memory. Discrimination of gender is dependent on memory abilities only to the extent that the individual must compare the target face to an internalized prototype or average face based on all previous experiences with faces. Studies with infants indicate that the ability to discriminate gender begins sometime within the first year of life (Leinbach & Fagot, 1993; Lewkowicz, 1996; Yamaguchi, 2000).

7 Gender 7 However, similar to identity, it may take significant development before children can discriminate gender with a level of expertise that approaches that of adults. Indeed, one study indicates that by the age of four years, children are still having significant difficulty at discriminating gender when the faces are not very typical male and female exemplars (Newell, Strauss, Best, & Gastgeb, 2004) In contrast to facial recognition, there are very few studies that have looked at the ability of individuals with autism to discriminate gender from internal facial features. Several early studies by Hobson and his colleagues suggest that when children with autism are asked to discriminate gender on the basis of just internal facial information without the benefit of hair cues, they have difficulty (Hobson, 1987; Weeks & Hobson, 1987; Hobson, et al., 1988). A more recent study by (Deruelle, et al., 2004) also found that, while their performance was well above chance, children with autism were worse then both verbal and chronological age matched controls at discriminating gender. Finally, a detailed study of three children with Asperger s Syndrome (Nijiokiktjien, et al., 2001) also found gender discrimination difficulties. The only study that has looked at the ability of adults with autism to discriminate gender (Behrmann, et al. 2006) found that while the participants with autism were just as accurate as matched controls at discriminating facial gender, their reaction times to make these discriminations were significantly slower, suggesting continued difficulty with gender discrimination into adulthood. Hence, the limited research thus far suggests that similar to facial identity, individuals with autism may have difficulty discriminating gender at least during childhood. However, because the studies with children included large age ranges, it remains unclear how early these difficulties emerge and whether there is any improvement with development as suggested by the results of Behrmann and colleagues (2006). Also, no previous studies have controlled for the

8 Gender 8 typicality of the exemplars. It may be that, while individuals can discriminate the gender of faces that are good exemplars of men and women, they may have greater difficulty with exemplars that are less typical of the two gender categories. Two recent studies with typically developing infants and preschool children found that while young children could categorize typical exemplars of gender, they had significant difficulty with less typical exemplars (Newell, Strauss, & Best, 2003; Newell, Strauss, Best, & Gastgeb, 2004). More specific to autism, a recent study (Gastgeb, Strauss, & Minshew, in press) of natural categories found that both children and adults with autism had particular difficulty categorizing boundary or atypical exemplars of objects. Similarly, none of the prior studies have systematically controlled for hair cues. Again, research with young children suggests that gender discriminations are enhanced by the presence of hair cues (Newell et al, 2004). Thus, the current set of studies was concerned with exploring whether or not individuals with autism demonstrate deficits in their ability to discriminate facial gender. Capitalizing on the fact that this is a simple task that can be used with even young children, these studies sought to explore this ability in participants ranging in age from early childhood to adulthood. Finally, there are no studies of either face recognition or gender discrimination in individuals with autism that have used naturalistic and dynamic videos of people. When combined with the simplicity of the task, this allowed us to study face perception in a manner very similar to what might be encountered by the participants in the real world. Thus, Experiment 1 was designed to study the ability of young (5- to 7-year-old) high-functioning children with autism to discriminate gender using naturalistic videos of people, but controlling for both the typicality of the stimuli and the use of hair as a cue.

9 Gender 9 Experiment 1 Method Participants Participants consisted of 19 children who were previously diagnosed with High Functioning Autism (HFA) by various psychologists in the community. The diagnosis of autism was confirmed by administrating the Autism Diagnostic Observation Schedule Generic (ADOS-G; Lord et al., 1989) to participants. The ADOS-G is a structured interaction set around tasks designed to elicit social interactions and communication that is then scored in a manner linked to DSM-IV criteria for Autistic Disorder and Pervasive Developmental Disorder Not Otherwise Specified. The staff administering the ADOS-G had extensive clinical experience with autism, and completed the week-long training and reliability course held by the first author of the ADOS-G. HFA is defined by a significant impairment in all three areas of the DSM-IV diagnostic triad (APA, 2000) without co-occurring mental retardation. High functioning children were chosen for this study because this allows for the examination of impairments that are specifically associated with autism rather than with mental retardation (Minshew, Goldstein, Muenz, & Payton, 1992). The age range of five to seven was chosen in order to fill a gap in the literature; no face processing data exists regarding children in this age group. Eighteen control participants were matched on chronological age and a standard score equivalent of Verbal Mental Age (VMA). The standard score equivalent of VMA was obtained by using the Peabody Picture Vocabulary Test Revised (PPVT-R; Dunn & Dunn, 1981), an instrument that has demonstrated adequate validity and reliability. Control participants were recruited by telephone solicitation, using names purchased from a company that provides such information. No

10 Gender 10 significant differences were found between groups in terms of chronological age and VMA (see Table 1) Insert Table 1 here Apparatus Both control and autism participants were tested either at home or in the laboratory depending on the parents preference. In both situations, the participants sat in front of a 43-cm. LCD monitor controlled by a laptop computer and responded using a modified keyboard with large keys (approximately 2.54 cm. squares) that is commercially available for young children. Black felt covered all of the keys except for the two response keys on the left and right side of the keyboard. The response keys were covered with small cartoon pictures of a male and female head that could be removed to counterbalance left and right hand responses across participants. Stimulus Materials Approximately 80 videos were made of male and female adults ranging in age from 18 to 30 years. The videos were taken with a digital camcorder and downloaded into a computer. Stimuli volunteers were required to wear a common black robe to hide their clothing. Volunteers were filmed with both their natural hair styles and with their hair hidden. To hide their hair, they wore a basic black baseball cap backwards, with their hair drawn to the back. When the videos were taken, they were framed so that just the face and a minimal amount of border were included on the video. The volunteers were seated in front of a black curtain, which blended with the cap and robe. With the robe, the cap, and the background all the same color, the videos provided a dynamic display of the face only. In order to elicit a natural pose from the volunteers and to

11 Gender 11 make the video as realistic as possible, volunteers recited a common nursery rhyme (Hickory, Dickory, Dock) during filming. Twenty undergraduate students rated each of the 80 videos for typicality of gender on a 7-point scale, with 1 being very atypical of that gender and 7 being very typical of that gender (i.e. very masculine or very feminine). The 10 most typical female videos (to be referred to as typical ) (M=4.45, SD=0.42), the 10 most typical male videos (M=4.73, SD=0.22), the 10 least typical female videos (to be referred to as atypical ) (M=2.45, SD=0.39), and the10 least atypical male videos (M=3.48, SD=0.33) were selected. The least typical faces ( atypical ) were then presented to a second group of undergraduate students who were asked to determine the gender of each face to ensure that all of the faces were easily discriminable by adults. T-tests indicated that the ratings for the typical and atypical faces were significantly different from each other, for both the male [t(19)=10.03, p<.001] and the female [t(19)=11.44, p<.001] videos. Procedure In order to insure that the participants could understand the task, they were initially shown ten full body pictures of both genders in random order and asked to say whether the picture was of a man or woman ( boy and girl labels were also acceptable). If the children got all ten correct, they proceeded to the test phase. It was explained to the children that they would see a series of very short movies with a person talking, although they would not be able to hear what the person was saying because the sound was turned off. It was explained that their job in this game was to guess whether the talking person was a man or woman and to respond by pressing one of the two keys that were covered with pictures of a man and woman. They were then asked to demonstrate what they would do if the movie was of a man or woman, e.g., press the button for man or woman. Once they successfully demonstrated that they

12 Gender 12 understood they were to push the male button for a male movie and the opposite button for a female movie, the test trials began. While it was initially planned to record reaction time data, it became apparent that many of the children would respond verbally before they actually pressed the response button. Hence, the reaction time data would not be accurate and was not used for analyses. Participants were then shown a total of 40 videos with equal numbers of male and female faces, typical and atypical faces, and videos with and without hair cues in randomized order. The start of each trial was controlled by the experimenter who made sure that the child s attention was focused on the screen. Once a trial started, the child saw a video of a talking male or female face, which remained on the screen until the child responded by pushing the male or female keyboard button. Results Of primary interest was whether there were any accuracy differences (as measured by the proportion of correct answers) between the control and autism participants, and whether the children s accuracy was affected by either the typicality of the stimuli or the availability of hair as a feature. Thus a two-way ANOVA was conducted that included Group (autism vs. control) as a between-subjects variable and Condition (typical with hair vs. typical without hair vs. atypical with hair vs. atypical without hair) as a within-subjects variable. Results indicated significant main effects for both Group and Condition, but more importantly a significant interaction between these two variables, F(3,105) = 2.70, p <.05. As can be seen in Figure 1, for the typical gender faces, the control participants were better at discriminating gender than were the participants with autism. This was true both when the hair cues were present, t(35) = 2.87, p <.01, and when hair was not present as a cue, t(35) = 2.82, p <.01. In contrast, there were no

13 Gender 13 differences between the two groups in either of the conditions that used atypical gender stimuli. That is, the control and autism participants performed equivalently in the two atypical conditions. Hair cues also had an impact on the participants ability to discriminate gender. The participants with autism were better at discriminating gender when hair cues were present in both the typical, t(18) = 2.70, p <.02 and atypical t(18) = 2.32, p <.05 stimulus conditions. While the hair cues helped the control participants discriminate the atypical gender stimuli, t(17) = 4.12, p<.01, it did not affect their discriminations of typical gender faces, t(17) = 1.80, p >.05, which were approaching ceiling performance in both the hair and cap conditions Insert Figure 1 here Discussion The results of this study indicate that as early as five to seven years of age, children with autism were significantly worse than typically developing children at discriminating the gender of faces, even with realistic videos of people. While the participants with autism were not poor at discriminating the typical faces, their performance did not match that of the controls who achieved greater than 90% accuracy in their performance. In contrast, both the control participants and participants with autism were considerably worse at discriminating the atypical faces than typical faces, and there were no reliable differences between the performance of the two groups with atypical faces with or without hair cues. The performance of both groups of children was considerably worse than 100%, especially when hair cues were not available. Indeed, their performance with atypical faces was not much above the chance value of 50%. Prior research with typically developing children has demonstrated that children begin to

14 Gender 14 discriminate facial gender within the first year of life (Leinbach & Fagot, 1993; Yamaguchi, 2000). Consequently, it probably has been assumed that they are at ceiling, and the ability to discriminate gender does not show improvement in childhood. However, no published study to date has varied the typicality of the faces and, hence, looked at the ability of children to discriminate facial gender with more difficult exemplars. The current results indicated that while typically developing 5- to 7-year-old children easily discriminated the typical exemplars of gender, their performance was relatively poor with the atypical exemplars, suggesting that expertise in gender discrimination is not reached until later in development. These results also illustrate how critical it is to establish how well typically developing children are performing on a task in order to determine whether children with autism are demonstrating a relative deficit. In this task, since both groups of children performed poorly at discriminating the atypical faces, group differences between the control participants and participants with autism did not emerge. It is also apparent, that at least for typically developing children, there is improvement in the ability to discriminate atypical gender faces with development since normal adults used in a pilot study were able to categorize these faces. When children reach the near perfect accuracy of adults for atypical faces is not known. It is also unknown whether, with experience or development, the children with autism also improve in their ability to discriminate the atypical faces, especially when there are no hair cues and the discrimination must be made using only internal facial features. Thus, in the next experiment, we tested the ability of older 8- to 12-year-old children with and without autism to discriminate typical and atypical faces with and without hair cues.

15 Gender 15 Experiment 2 Method Participants Participants included 29 high-functioning children with autism and 21 healthy control children between 8 and 12 years of age. Control participants were matched with the autism group on age, Full Scale IQ, Verbal IQ, and Performance IQ. Table 2 summarizes the participants demographic characteristics. No significant differences existed between the autism and control groups on any of the demographic variables Insert Table 2 here Participants were recruited through advertisements in autism support group newsletters, posters at autism conferences, and distribution of recruitment fliers to autism parent groups. Participants with autism were administered a diagnostic evaluation consisting of the Autism Diagnostic Observation Schedule-General (ADOS-G; Lord et al., 1989) and the Autism Diagnostic Interview-Revised (ADI-R; Lord, Rutter, & LeCouteur, 1994) with confirmation of diagnosis by expert clinical opinion. Both instruments were scored using the DSM-IV (APA, 2000) scoring algorithm for autism. Children with Asperger s disorder or PDD-NOS were excluded. Participants with autism were also required to be in good medical health, free of seizures, have a negative history of traumatic brain injury, and have Full Scale and Verbal IQ scores > 80 as determined by the Wechsler Abbreviated Scale of Intelligence (WASI; Wechsler, 1999).

16 Gender 16 Control participants were volunteers recruited from the community. Parents of potential control participants completed questionnaires of demographic and family information to determine eligibility. Control participants were required to be in good physical health, free of past or current neurological and psychiatric disorders, have a negative family history of first degree relatives with major psychiatric disorders, and have a negative family history in first and second degree relatives of autism spectrum disorder. Control participants were also excluded if they had a history of poor school attendance or evidence of a disparity between general level of ability and academic achievement suggesting a learning disability. The Wide Range Achievement Test-IV (WRAT-4) was administered to exclude the presence of a learning disability Insert Table 2 here Apparatus In contrast to Experiment 1, all participants in this experiment were tested in the laboratory in a quiet room. The apparatus was identical to Experiment 1 except that the response keys were labeled boy and girl. Stimulus Materials The stimulus materials were identical to Experiment 1 Procedure The procedure was very similar to Experiment 1. Participants were told they would see videos of either men or women and that they were to press the boy button if the video was of a man and press the girl button if the video was of a woman. They received the identical 40

17 Gender 17 videos used in Experiment 1 consisting of both typical and atypical gender faces either with hair cues or wearing a cap to hide the hair cues. Participants were encouraged to respond as quickly and as accurately as possible. Thus, both accuracy and reaction times were recorded in Experiment 2. Results Accuracy Results A two-way ANOVA was conducted on the proportion of correct scores that included Group (autism vs. control) as a between-subjects variable and Condition (typical with hair vs. typical without hair vs. atypical with hair vs. atypical without hair) as a within variable. The results, which are shown in Figure 2a, indicated there was a significant main effect for Group, F(1,48) = , p <.001; control children were better than the children with autism at discriminating gender across all of the conditions (all comparisons shown in figure 2a are twotail t tests). The interaction between Group and Condition was not significant, indicating that across all four stimulus conditions, the control children were better at discriminating gender than the children with autism. Indeed, the control children s proportion of correct scores was above 90% in all four conditions, thus approaching ceiling. In contrast, while the children with autism showed improvement relative to the 5- to 7-year-old children in Experiment 1, they were still having difficulty discriminating gender across all of the conditions. Finally, for the control participants, having hair as an external cue did not affect their accuracy at discriminating gender with either the typical or atypical faces. Similarly, for the children with autism, when the faces were typical, the presence of hair as a cue had no impact on their accuracy to discriminate gender. However, the children with autism were significantly better [t(28) = 2.63 p <.02] at

18 Gender 18 discriminating the gender of atypical faces when there were hair cues in comparison to when this external cue was not present Insert Figure 2a here Reaction Time Results A two-way ANOVA was conducted on the reaction times (msec) that included Group (autism vs. control) as a between-subjects variable and Condition (typical with hair vs. typical without hair vs. atypical with hair vs. atypical without hair) as a within-subjects variable. As seen in Figure 2b, the children with autism are considerably slower than the control participants across the four conditions [F(1,55)= 338.1, p<.001]. There was also a reliable Group by Condition interaction [F(3,165)= 3.98, p<.01]. For both groups, the reaction times were fastest to the typical faces that had hair cues. Reaction times slowed when hair cues were removed or the faces were atypical. Since the reaction times of the control participants were always faster than participants with autism, in order to best understand this group by condition interaction, it was decided to convert all of the reaction times to a percent change from the typical hair condition. That is, how much slower are the participants in the typical cap, atypical cap, and atypical hair conditions relative to the typical hair condition? These percentage change scores are also shown in Figure 2b as the numbers above each plot point. Looking first at the typical cap condition, it can be seen that the control participants discriminated these stimuli as quickly as the typical faces that had hair cues. In contrast, the children with autism were 38% slower at discriminating typical faces that did not have hair cues in comparison to the typical faces that did have hair cues. This difference between groups is statistically reliable [t(48) = 3.06, p<.01]

19 Gender 19 indicating that, unlike the control children, the children with autism relied on hair cues to help discriminate the gender of the typical faces. In comparison, both groups were slower to discriminate the gender of the atypical exemplars, and the increase in reaction times was not different between the two groups of participants Insert Figure 2b here Discussion Considering the results of the typically developing children first, their ability to discriminate facial gender was above 90% in all conditions. Thus, by 8 to 12 years of age, typically developing children have nearly reached the adult levels in discriminating gender. Whereas the ability to discriminate gender may begin during infancy, it takes at least 8 to 12 years to acquire adult-like expertise at discriminating facial gender. As will be considered in the general discussion, this lengthy course of development may reflect a combination of needed experience with less typical faces but most likely the development of more efficient configural processing abilities. With respect to the children with autism, both their accuracy and their reaction times indicated that they were not able to discriminate facial gender as well as typically developing children. While they did show improvement over the performance of the younger children with autism in Experiment 1, their performance for both typical and atypical faces was worse than the matched control children. This was particularly true for the two atypical conditions where the children with autism had error rates of 15% to 20%. Finally, unlike the controls, reaction times of the autistic children indicated that they were dependent on seeing hair cues even when the

20 Gender 20 faces were typical exemplars. Research with normal adults indicates that gender is discriminated very quickly (O'Toole, Peterson, & Deffenbacher, 1996). As people naturally interact, they must process information about gender, age, identity, and expression very rapidly and automatically. Delays in processing any single aspect of facial information could slow the efficiency of processing other aspects of the face. At the least, difficulty processing the most elementary aspects of the face, such as gender, bodes ill for more complex processing such as identity. While speculative, known difficulties in the ability of individuals with autism to recognize faces might in part be due to the extra time it takes them to process facial aspects such as gender, age or expression. Alternatively, though this difficulty may reflect the common dependence on faulty configural processing. These possibilities will be discussed further in the general discussion. Finally, given that the ability of older children with autism did improve in contrast to the younger children in first experiment, it is possible that with continued development, the gender discrimination abilities of individuals with autism might approach the abilities of typically developing children. Alternatively, since the control children have already reached performance levels similar to adults (with respect to accuracy), it is possible that the children with autism have also reached their maximal abilities and might not show continued improvement with development. Thus, the next study looked at the ability of adolescents and adults with autism to discriminate gender in comparison to control participants. Experiment 3 Method

21 Gender 21 Participants Participants were 24 high-functioning adolescents with autism and 15 healthy adolescent control individuals between the ages of 13 and 16 years. Adult participants were 29 highfunctioning individuals with autism and 28 healthy control adults between the ages of 17 to 53 years. As in the previous study, normal control participants in each age group (adolescent or adult) were matched with the autism group (same mean with equal variances) on age, Full Scale IQ, Verbal IQ, and Performance IQ scores. Table 3 summarizes the participants demographic characteristics. No significant differences existed between the autism and control groups on any of the demographic variables Insert Table 3 here Apparatus, Stimulus Materials, and Procedure The apparatus, stimuli, and procedures were identical to Experiment 2 Results The accuracy results for both the adolescents and adults are presented in Figures 3a and 3b. The Group by Condition ANOVAs, one for adolescents and one for adults, indicated that for both age groups, there were significant two-way interactions [Adolescents: F(3,111) = 5.86, p <.001; Adults: F(3,165) = 3.89, p <.01]. As indicated in the Figures 3a, both groups of participants discriminated the typical gender faces with almost perfect accuracy. In contrast, the adolescent and adult participants with autism were still significantly worse than the control participants at discriminating the atypical faces. This was true whether the atypical faces had

22 Gender 22 hair cues [Adolescents: t (37) = 2.96, p <.01; Adults: t(55) = 3.42, p <.001] or whether the hair was hidden with the caps [Adolescents: t(37) = 3.24, p <.001; Adults: t(55) = 6.34, p <.001] Insert Figures 3a and 3b here Reaction time results are presented in Figures 4a and 4b. Considering the adolescent results first, the two-way ANOVA of Group by Condition resulted in a significant main effect for groups [F(1, 37) = , p <.001], indicating that the control participants were faster across all four stimulus conditions. There was also Group by Condition interaction [F(3,111) = 3.24, p <.05]. Again, to help interpret this interaction, the reaction time scores were converted into percent scores indicating how much slower participants were in the typical cap, atypical hair, and atypical cap conditions relative to the typical hair condition. As seen in Figure 4a, the reaction times of the autistic adolescents were considerably slower in all three conditions than the control participants, indicating that despite improvement in accuracy, the adolescents with autism take more time to discriminate gender when either hair cues are not available or when the faces are atypical. Thus, even in the typical cap condition where the autistic participants were just as accurate as the control participants, it took them significantly longer to make this discrimination. Considering the adult reaction data shown in Figure 4b, the two-way ANOVA of Group and Condition also demonstrated and significant main effect for Group [F(1,55) = , p <.001]. Similar to the adolescents, the adults with autism were significantly slower than control participants at discriminating gender across all stimulus conditions. There was also a significant Group by Condition interaction for the adults reaction time data [F(3,165) = 7.31, p <.01]. As seen in Figure 4b, while the accuracy data for the adolescents and adults with autism were

23 Gender 23 virtually identical, adults with autism did show improvement in their processing efficiency. The adults with autism demonstrated relatively little increase in their reaction times to either the typical cap or atypical hair stimuli, and the reaction time increases in these two conditions were similar between participants with autism and control participants. However, the adults with autism were still considerably less efficient than control participants at processing the atypical gender faces that did not have hair cues. Discussion First considering the accuracy results, there was improvement in the ability of both the adolescents and adults with autism to discriminate gender in comparison to the ability of the children with autism. However, both the adolescents and adults with autism had difficulty discriminating the atypical faces. Indeed their accuracy scores were lower than the control 8- to 12-year-old children. Thus, while the individuals with autism improved from childhood through adulthood, their abilities to discriminate facial gender never reached the true level of expertise of the control participants when more challenging atypical exemplars of men and women were presented. Again, it should be noted that while less representative of gender than the typical faces, the atypical faces were not genderless faces that were difficult for the control participants to discriminate. In contrast to the accuracy data, the reaction time data did show improvement from adolescence to adulthood. Processing and reaction time differences between the control and autism participants were found only for the atypical faces without hair cues. General Discussion This was the first study to trace the development of the ability to discriminate gender from early childhood to adulthood in both typically developing individuals and individuals with

24 Gender 24 autism. In contrast to previous research, it manipulated the degree of typicality of the faces and used naturalistic digital videos. First considering the results of the typically developing participants, we know from prior research that even infants are able to discriminate gender (Leinbach & Fagot, 1993; Yamaguchi, 2000). Unfortunately, there has been very little research on gender discrimination by typical children, perhaps because it has been tacitly assumed that the ability to discriminate gender develops early and does not change developmentally. In contrast, the present study demonstrates that while even 5- to 7-year-old typical children were very good at discriminating typical exemplars, they had difficulty discriminating the atypical exemplars, especially when hair cues were not available. Indeed, these younger children were only 70% accurate in the atypical cap condition with random guessing being fifty percent. Interestingly, even the younger typical children capitalized on hair cues when they were present; a cue that is obviously culturally learned, since hair styles of men versus women is a cultural artifact. More importantly, the typically developing children did not reach accuracy levels comparable to adults until 8 to 12 years of age. Thus, while the ability to discriminate facial gender appears to begin in infancy, it takes 8 to 12 years to reach a level of true expertise as defined by the abilities of adults. Concerning the results of the children with autism, the 5- to 7-year-old children had difficulty discriminating even the typical exemplars relative to control participants and it took them until adolescence to reach the ability of typically developing individuals. However, even in adulthood, the participants with autism were not as good as the controls in discriminating the atypical exemplars. While they were clearly above chance with these exemplars, their accuracy remained lower then typically developing 8- to 12-year-old children and they exhibited continued difficulty with respect to both their absolute reaction times and the amount of time it

25 Gender 25 took them to discriminate the atypical faces in comparison to the typical faces. Thus, at issue are several critical questions. What is developing that allows typically developing children to discriminate gender as well as adults by 8 to 12 years of age? Why are the atypical exemplars of gender so much harder to discriminate? And similarly, why do the participants with autism continue to have delayed development of the capacity to identify gender and persisting difficulty discriminating atypical exemplars even as adult? Research on the development of face recognition suggests several processes may be improving with development. First, a number of studies indicate that typically developing children slowly shift from a predominant reliance on more featural processing of faces to having adult expertise in configural processing of faces (Schwarzer, 2000; Mondloch, et al., 2002; Mondloch, et al., 2004). Configural processing is typically seen as the ability to perceive the spatial distances or relationships among aspects of the faces (e.g., eye separation) as opposed to attending to single non-spatial features such as the nose. Unfortunately, this distinction between configural and featural aspects of the face may not be as straightforward as is usually depicted. Spatial distances can also vary in how easily they can be discriminated. Categorizing a male and female face where the man has very wide or thick eyebrows and the woman has very narrow eyebrows may be relatively easy. In contrast, this categorization would be much more difficult if the man had relatively narrow eyebrows. In line with many models of face perception, it is being suggested that eyebrow widths (and other features that distinguish gender such as forehead size, eye size, and nose length) are normally distributed around two prototypic means for men versus women. Faces that contain widths close to either gender s mean are easier to discriminate than faces with values at the boundary. Thus, with development, not only must individuals rely more on configural information, they must also get better at making subtle configural discriminations.

26 Gender 26 While prior research with individuals with autism suggest they do not rely on configural information as much as typical individuals (see, Dawson, et al., 2005; Schultz, 2005), they may also have limitations in their ability to make subtle configural discriminations. Similarly, most cognitive models (e.g., Valentine, 1992) of how adults process facial information assume that individuals compare the faces they are viewing to either stored exemplars or a multidimensional prototype that contains the mean of all of the dimensions that vary in faces. It is likely that gender is discriminated by comparing the multiple aspects of the face to separate prototypes for male and females faces (e.g, O, Toole et al., 1998). For typical exemplars, this comparison is relatively easy. In contrast, when trying to decide the gender of a boundary or asexual face, a careful decision must be made as to whether the face is closer to the male or female prototype. We know that even infants are able to abstract prototypes of faces (Quinn, 1987; Strauss, 1979) and that they can use prototypic information to help recognize faces (de Haan, Johnson, Maurer, & Perrett, 2001) and in their perception of attractiveness (Langlois & Roggmann, 1990). With development, the formation of prototypes may improve (for example, they may become more multidimensional), and thus the distribution of male versus female faces may become more distinct. Unfortunately, there is no current research on this topic. However, there is research that suggests that individuals with autism have difficulty abstracting prototypes (Best, Strauss, Newell, & Minshew, 2005; Klinger & Dawson, 2001; Plaisted, 2000). Thus, the difficulty seen in the ability of individuals with autism to discriminate atypical gender faces may also be related to limitations in forming prototypic representations and comparing exemplars to these prototypes. Finally, in comparison to typical faces, discriminating atypical faces may require a more flexible decision process. One of the faces that even the adults with autism consistently

27 Gender 27 answered incorrectly is the female depicted in Figure 5. As can be seen, this individual has relatively masculine eyebrows and eyes. While the eye region is generally important in gender category decisions, when categorizing this face, the other dimensions outside of the eye region might need to be given more weight or importance. Thus, with development, it is possible that children develop more flexible decision making processes. Again, while speculative, it is possible that individuals with autism are less flexible in these decision processes. In summary, it is being suggested that improvements in the face processing abilities of typically developing children may involve more than just a shift in emphasis from featural to configural processes but also an increase in flexibility in weighting properties depending on the circumstances. Similarly, deficits seen in individuals with autism may also be more complex and involve limits in their ability to make subtle quantitative discriminations, compare exemplars to prototypes, and use flexible decision processes. Indeed improvement in all of these processes may be similar to the abilities that develop as individuals acquire the expertise necessary to discriminate any subordinate category exemplar (e.g., Gauthier & Nelson, 2001; Tanaka & Curran, 1991). Finally, why do individuals with autism never develop the expertise at discriminating gender that is seen with normal development? Dawson et al. (2005), Schultz (2005) and others have argued that a lack of early social motivation and attention to faces leads to decreased expertise in configural/holistic processing and by extension the types of subordinate category processing abilities just described. That is, because of a lack of experience with faces, individuals with autism never develop true expertise at perceiving and recognizing faces. However, recent studies by Behrmann, et al. (2005) and Gastgeb et al. (in press) have demonstrated very similar deficits in the way individuals with autism process non-social stimuli.

28 Gender 28 For example, the study by Gastgeb et al. (in press) traced the development of categorization ability in children, adolescents and adults for both typical and less typical exemplars of categories such as chairs, couches, and cats. Interestingly, the results for these categories were very similar to the results of the present study. It was found that while children with autism were just as efficient at categorizing typical category exemplars (as measured by reaction time), they had difficulty with less typical and atypical exemplars. With development there was improvement, but, even as adults, the individuals with autism had difficultly categorizing the atypical exemplars in these categories. Thus, it appears that individuals with autism have a deficit in the skills needed to discriminate subtle subordinate level category information and that this deficit applies to social and non-social stimuli. These deficits may be more apparent for social stimuli because socially based stimuli are generally more complex and have greater reliance on more subtle discriminatory processes than non-social stimuli. More research is needed to explore these relatively complicated issues but the existing data are sufficient to demonstrate that the same pattern of impairments exist with objects as with faces. In conclusion, the current study provides evidence that suggests that there may be significant processing differences in the ability of individuals with autism to discriminate facial gender information. While the current study tested only high functioning individuals, these difficulties may be more profound in lower functioning individuals. From early in life, infants have a number of processes that help them to decrease the amount of complexity in the world, including the ability to detect statistical correlations in both language and visual stimuli (Saffran, Aslin, & Newport, 1996), to form prototypes (Bomba & Siqueland, 1983; Quinn, 1987; Strauss, 1979; Younger & Gotlieb, 1988), and to categorize on the basis of correlated attributes (Younger, 1986). While speculative, one possibility is that individuals with autism may have

29 Gender 29 general problems in data reduction from infancy and that the differences in perceptual processing that were evidenced in the current study are only one piece of a larger cognitive deficit. Previously cited studies showing that individuals with autism have difficulty forming prototypes and categories support this view. Again, while speculative, this possibility presents an interesting avenue for future research. The current study also highlights the importance of developmental studies in understanding the cognitive deficits that are present in individuals with autism. This study was the first to examine the role that cognitive processing differences may have on gender discrimination from early childhood to adulthood. As a result, this study provides a developmental picture of improvement in gender discrimination and development of subordinate perceptual processes with limitations for individuals with autism.

30 Gender 30 References American Psychiatric Association. (2000). Diagnostic and Statistical Manual of Mental Disorders, 4 th ed., Text Revision (DSM-IV-TR). Washington, DC: American Psychiatric Association. Barrera, M. E., & Maurer D. (1981). Discrimination of strangers by the three-month-old. Child Development, 5, Behrmann, M., Avidan, G., Leonard, G. L., Kimchi, R., Luna, B., Humphreys, K., et al. (2006). Configural processing in autism and its relationship to face processing. Neuropsychologia, 44, Best, C. A., Strauss, M. S., Newell, L. C., & Minshew, N. J. (2005, May). Face knowledge in individuals with autism: Abstracting specific information from faces. Poster session presented at the annual International Meeting for Research in Autism, Boston, MA. Bomba, P. C., & Siqueland, E. R. (1983). The nature and structure of infant form categories. Journal of Experimental Child Psychology, 35, Boucher, J., & Lewis V. (1992). Unfamiliar face recognition in relatively able autistic children. Journal of Child Psychology and Psychiatry and Allied Disciplines, 33, Brown, E., & Perrett, D. I. (1993). What gives a face its gender? Perception, 22, Bruce, V., Campbell, R. N., Dohetry-Sneddon, G., Iport, A., Langton, S., McAuley, S., et al. (2000). Testing face processing skills in children. British Journal of Developmental Psychology, 18, Bulthoff, I., & Newell, F. N. (2004). Categorical perception of sex occurs in familiar but not unfamiliar faces. Visual Cognition, 11, Bushnell, I. W. R. (2001). Mother's face recognition in newborn infants: Learning and memory. Infant and Child Development, 10, Carey, S., Diamond, R., & Woods, B. (1980). Development of face recognition: A maturational component? Developmental Psychology, 16, Cohen, L. B., & Cashon, C. H. (2001). Do 7-month-old infants process independent features or facial configurations? Infant & Child Development, 10, Chronicle, E. P., Chan, M., Hawkings, C., Mason, K., Smethurs, K., Stallybrass, K., et al. (1995). You can tell by the nose - Judging sex from an isolated facial feature. Perception, 24, Dawson, G., Carver, L., Meltzoff, A. N., Panagiotides, H., McPartland, J., & Webb, S. J. (2002). Neural correlates of face and object recognition in young children with autism spectrum disorder, developmental delay, and typical development. Child Development, 73, Dawson, G., Webb, S. J., & McPartland, J. (2005). Understanding the nature of face processing impairment in autism: Insights from behavioral and electrophysiological studies. Developmental Neuropsychology, 27, de Haan, M., Johnson, M. H., Maurer, D., &Perrett, D. I. (2001). Recognition of individual faces and average face prototypes by 1-and 3-month-old infants. Cognitive Development, 16, Deruelle, C., Rondan, C.,Gepner, B., Tardif, C. (2004). Spatial frequency and face processing in children with autism and Asperger's Syndrome. Journal of Autism and Developmental Disorders, 34,

31 Gender 31 Dunn, L. M., & Dunn, L. M. (1981). Peabody Picture Vocabulary Test-Revised. American Guidance Service, MN. Easterbrook, M. A., Kisilevsky, B. S., Muri, D.W., & Laplante, D. P. (1999). Newborns discriminate schematic faces from scrambled faces. Canadian Journal of Experimental Psychology, 53, Fombonne, E. (2003). Epidemiological surveys of autism and other pervasive disorders: An update. Journal of Autism and Developmental Disorders, 33, Gastgeb, H., Strauss, M. S., & Minshew, M. J. (in press). Do individuals with autism process categories differently? The effect of typicality and development. Child Development. Gauthier, I., & Nelson, C. A. (2001). The development of face expertise. Current Opinion in Neurobiology, 11, Grelotti, D., Gauthier, I., & Shultz, R. (2002). Social interest and the development of cortical face specialization. Developmental Psychobiology, 40, Hobson, R. P. (1986). The autistic child's appraisal of expressions of emotion. Journal of Child Psychology and Psychiatry and Allied Disciplines, 27, Hobson, R. P. (1987). The autistic child's recognition of age- and sex-related characteristics of people. Journal of Autism and Developmental Disorders, 17, Hobson, R. P., Ouston, J., & Lee, A. (1988). What's in a face? The case of autism. British Journal of Psychology, 79, Johnson, M. H. (1999). Ontogenetic constraints on neural and behavioral plasticity: Evidence from imprinting and face processing. Canadian Journal of Experimental Psychology, 53, Joseph, R. M., & Tanaka, J. (2002). Holistic and part-based recognition in children with autism. Journal of Child Psychology and Psychiatry, 43, Klin, A., Sparrow, S. S., de Bildt, A., Cicchetti, D.V., Cohen, D. J., & Volkmark, F.R. (1999). A normed study of face recognition in autism and related disorders. Journal of Autism and Developmental Disorders, 29, Klinger, L. G., & Dawson, G. (2001). Prototype formation in autism. Development and Psychology, 13, Langdell, T. (1978). Recognition of faces: An approach to the study of autism. Journal of Child Psychology and Psychiatry and Allied Disciplines, 19, Langlois, J. H., & Roggmann, L.A. (1990). Attractive faces are only average. Psychological Science, 1, Leinbach, M. D., & Fagot, B. I. (1993). Categorical habituation to male and female faces: Gender schematic processing in infancy. Infant Behavior and Development, 16, Lewkowicz, D. J. (1996). Infants' response to the audible and visible properties of the human face: Role of lexical syntactic content, temporal synchrony, gender, and manner of speech. Developmental Psychology, 32, Lord, C., Rutter, M., Goode, S., Heemsbergen, J,. Jordan, H., Mawhodd, L., et al. (1989). Autism diagnostic observation schedule: A standardized observation of communicative and social behavior. Journal of Autism and Developmental Disorders, 19, Lord, C., Rutter, M., & Le Couteur, A. (1994). Autism diagnostic interview-revised: A revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. Journal of Autism and Developmental Disorders, 24,

32 Gender 32 Minshew, N. J., Goldstein, G., Muenz, L. R., & Payton, J. B. (1992). Neuropsychological functioning in non-mentally retarded autisitic individuals. Journal of Clinical and Experimental Neuropsychology, 14, Mondloch, C. J., Dobson, K. S., Parsons, J., & Maurer, D. (2004). Why 8-year-olds cannot tell the difference between Steve Martin and Paul Newman: Factors contributing to the slow development of sensitivity to the spacing of facial features. Journal of Experimental Child Psychology, 89, Mondloch, C. J., Le Grand, R., & Maurer, D. (2002). Configural face processing develops more slowly than featural face processing. Perception, 31, Mondloch, C. J., Lewis, T. L., Budreau, D. R., Maurer, D., Dannemiller, J. L., Stephens, B.R., et al. (1999). Face perception during early infancy. Psychological Science, 10, Newell, L. C., Strauss, M. S., & Best, C. A. (2003, April). Gender categorization during infancy: The effect of typicality. Poster session presented at the biennial meeting of the Society for Research in Child Development, Tampa, FL. Newell, L. C., Strauss, M. S., Best, C. A., & Gastgeb, H. (2004, May). Gender categorization abilities of preschoolers: The effects of typicality and hair. Poster session presented at the biennial meeting of International Conference on Infant Studies, Chicago, IL. Nijiokiktjien, C., Verschoor, A., de Sonneville, L., Huyse, C., Op het Veld, V., & Toorenaar, N. (2001). Disordered recognition of facial identity and emotions in three Asperger type autistics. European Child and Adolescent Psychiatry, 10, O' Toole, A. J., Defenbacher, K. A., Valentine K., McKee, K., Huff, D., & Abdi, H. (1998). The perception of face gender: The role of stimulus structure in recognition and classification. Memory and Cognition, 26, O'Toole, A. J., Peterson, J., & Deffenbacher, K. A. (1996). An 'other-race effect' for categorizing faces by sex. Perception, 25, Plaisted, K. C. (2000). Aspects of autism that theory of mind cannot explain. In S. Baron-Cohen, H. Tager-Flusberg, & D. J. Cohen (Eds.), Understanding Other Minds: Perspective from Developmental Cognitive Neuroscience. New York: Oxford University Press. Quinn, P. C. (1987). The categorical representation of visual pattern information by young infants. Cognition, 27, Rossion, B. (2002). Is sex categorization from faces really parallel to face recognition? Visual Cognition, 9, Rossion, B., Gauthier, I., Goffaux, V., Tarr, M. J., & Crommelinck, M. (2002). Expertise training with novel objects leads to left-lateralized facelike electrophysiological responses. Psychological Science, 3, Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science, 274, Schultz, R. (2005). Developmental deficits in social perception in autism: The role of the amygdala and fusiform face area. International Journal of Developmental Neuroscience, 23, Schwartzer, G., Huber, S., & Dummler, T. (2005). Gaze behavior in analytical and holistic face processing. Memory and Cognition, 33, Schwarzer, G. (2000). Development of face processing: The effect of face inversion. Child Development, 71, Schyns, P. G., Bonnar, L., & Gosselin, F. (2002). Show me the features! Understanding recognition from the use of visual information. Psychological Science, 13,

33 Gender 33 Strauss, M. S. (1979). Abstraction of prototypical information by adults and 10-month-old infants. Journal of Experimental Psychology: Human Learning and Memory, 5, Tanaka, J. & Curran, T. (2001). A neural basis for expert object recognition. Psychological Science, 12, Teunisse, J. P., & Degelder, B. (1994). Do autistics have a generalized face processing deficit? International Journal of Neuroscience, 77, Valentine, T., & Endo, M. (1992). Towards an exemplar model of face processing: The effects of race and distinctiveness. The Quarterly Journal of Experimental Psychology, 44, Valentine, T. (2001). Face-space models of face recognition. In M. J. Wenger, & J. T. Townsend (Eds.), Computational, geometric, and process perspectives on facial cognition: Contexts and challenges. Scientific psychology series. (pp ). Mahwah, NJ: Erlbaum. Wechsler, D. (1999). Wechsler Abbreviated Intelligence Scale. San Antonio: The Psychological Corporation. Weeks, S. J., & Hobson, R. (1987). The salience of facial expression for autistic children. Journal of Child Psychology and Psychiatry and Allied Disciplines, 28, Yamaguchi, M. K. (2000). Discriminating the sex of faces by 6-and 8-mo.-old infants. Perceptual and Motor Skills, 91, Yamaguchi, M. K., Hirukawa, T., & Kanazawa, S. (1995). Judgment of gender through facial parts. Perception, 24, Younger, B. (1986). The segregation of items into categories by ten-month-old infants. Child Development, 56, Younger, B, & Gotlieb, S. (1988). Development of categorization skills: hanges in the nature or structure of infant form categories. Developmental Psychology, 24,

34 Gender 34 Table 1 Demographic Characteristics of Autism and Control Groups for Experiment 1 Autism Group (N=19) Control Group (N=18) M SD Range M SD Range Age (9.45) (9.65) VMA (15.86) (11.99) Gender (M:F) 14:5 11:7 Ethnicity 19 Caucasian 18 Caucasian Note: Age is indicated in months. VMA = Verbal Mental Age. Ethnicity was obtained by self report.

35 Gender 35 Table 2 Demographic Characteristics of Autism and Control Groups for Experiment 2 Autism Group (N = 29) Control Group (N = 21) M SD M SD Age VIQ PIQ FSIQ Gender (M:F) 26:3 19:2 Ethnicity 26 Caucasian 19 Caucasian 1 African American 2 Unknown/Other 2 Unknown/Other Note: Age is indicated in years. SD = standard deviation; VIQ = Verbal IQ, PIQ = Performance IQ, FSIQ = Full Scale IQ. Ethnicity was obtained by self report.

36 Gender 36 Table 3 Demographic Characteristics of Autism and Control Groups for Experiment 3 Adolescents Autism Group (N = 24) Control Group (N = 15) M SD M SD Age VIQ PIQ FSIQ Gender (M:F) 20:4 13:2 Ethnicity 24 Caucasian 13 Caucasian 2 Unknown/Other Adults Autism Group (N = 29) Control Group (N = 28) M SD M SD Age VIQ PIQ FSIQ Gender (M:F) 26:3 26:2 Ethnicity 26 Caucasian 26 Caucasian 3 Unknown/Other 2 African American

37 Gender 37 Figure Captions Figure 1. Proportion of correct responses for control vs. autistic 5- to 7-year-old participants in each stimulus condition. Figure 2a. Proportion of correct responses for control vs. autistic 8- to 12-year-old participants in each stimulus condition. Figure 2b. Reaction time (msec) and percent change for control vs. autistic 8- to 12-year-old participants in each stimulus condition. Figure 3a. Proportion of correct responses for control vs. autistic adolescent participants in each stimulus condition. Figure 3b. Proportion of correct responses for control vs. autistic adult participants in each stimulus condition. Figure 4a. Reaction time (msec) and percent change for control vs. autistic adolescent participants in each stimulus condition. Figure 4b. Reaction time (msec) and percent change for control vs. autistic adult participants in each stimulus condition. Figure 5. Example of atypical female face with which participants with autism had difficulty.

38 Gender 38 Figure 1 5- to 7- Year Olds Proportion Correct 1 Proportion Correct ** ** Control Autistic * p <.01 Typical Hair Typical Cap Atypical Hair Atypical Cap Condition

39 Gender 39 Figure 2a 8- to 12-Year-Olds' Proportion Correct Proportion Correct ** ** ** ** Control Autism * p < Typical Hair Typical Cap Atypical Hair Atypical Cap Condition Figure 2b 8- to 12-Year-Olds' Reaction Time by Condition & Percentage of Change in Reaction Time to Typical Hair 2000 Reaction Time (msec) % * 4% 25% 17% 35% 38% Control Autism * p < Typical Hair Typical Cap Atypical Hair Atypical Cap Condition

40 Gender 40 Figure 3a Adolocents Proportion Correct Proportion Correct ** ** ** ** ** Control Autistic * p <.01 Typical Hair Typical Cap Atypical Hair Atypical Cap Condition Figure 3b Adults Proportion Correct Proportion Correct ** ** ** ** Control Autistic * p <.01 Typical Hair Typical Cap Atypical Hair Atypical Cap Condition

41 Gender 41 Figure 4a Adolescents' Reaction Time by Condition & Percentage of Change in Reaction Time to Typical Hair % 1950 Reaction Time (msec) * 26% 10% 28% * 12% * 40% Control Autism * p < Typical Hair Typical Cap Atypical Hair Atypical Cap Condition Figure 4b Adults' Reaction Time by Condition & Percentage of Change in Reaction Time to Typical Hair Reaction Time (msec) % 12% 14% 7% 48% Typical Hair Typical Cap Atypical Hair Atypical Cap Condition * 30% * p <.05 Control Autism

42 Figure 5 Gender 42