Cognitive/ Affective Mechanisms Underlying the Anger Superiority Effect in Children with Autism Spectrum Disorders

Background:  An atypical face and emotion processing in ASD have received wide attention in the research of cognitive characteristics in ASD.  It is, however, still not clear whether/ how their processing is different from typical people.  In the current study, we focused on the "anger superiority effect (ASE)", which refers a phenomenon where an angry face is detected more quickly than a happy or neutral face in a crowd of distracter (i.e., Face-in-crowd task).  This is believed to stem from the attention-getting properties in such threatening stimuli.  Previous studies reported that individuals with ASD also showed the ASE but the effect was weaker at a larger crowd size in ASD. (Ashwin et al., 2006; Krysko & Rutherford, 2009).  Moreover, children with ASD showed a developmental change in ASE, but such developmental change was not observed in typically developing (TD) children (Isomura et al., submitted).  These findings suggested that the rapid processing to angry faces in ASD would be acquired through their development.  One remaining question is whether the rapid processing to angry faces in ASD is brought by the same mechanisms as the one typical people use, or it stems from a different strategy.  

Objectives:  In this study, we examined the cognitive/ affective mechanisms underlying the ASE in children with and without ASD.  We focused on configural/ local bias in their face processing.

Methods:  22 children with ASD and 25 TD aged 8 to 12 years old participated in this study.  To examine whether they rely more on configural or on local biased processing during a face-in-crowd task, we employed a recognition task in combination with a face-in-crowd task.  We used schematic facial stimuli including angry, happy, and neutral faces.  Their responses were recorded through a touch sensitive monitor.  In the baseline trials, participants were required to touch a discrepant face (angry or happy) among neutral faces as quickly as possible (face-in-crowd task).  In the test trials, the face-in-crowd task was immediately followed by a recognition task where the participants were additionally required to recognize the target face that they had detected in the preceded face-in-crowd task.  In the recognition task, either whole faces or only local-features of faces (i.e., eyebrows or mouth) were presented randomly. 

Results:  The quicker detection of angry faces over happy faces was observed along with previous studies.  More interestingly, while TD children showed slower reaction time in recognizing local-features compared to whole faces, ASD children did not show such a difference. This suggests that recognizing local-features was as easy as recognizing whole faces in ASD. 

Conclusions: These results suggested that children with ASD focused more on local-features during face-in-crowd task than TD children, who relied on configural feature in face processing.  Therefore, the mechanisms behind the emotion processing seem different between groups even though they show ASE similarly.  Together with previous studies, our results suggest that ASD children, who rely on local-features in processing faces, compensate the poorer face perception, develop emotion process, and successfully detect angry faces quickly as they grow up.