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Updated: Jan 6, 2026

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome
Published on: July 31, 2016
Facial Emotion Recognition in Neurodevelopmental Disorders: A Comparative Study in Children and Adolescents With and
Giulia Crisci1, Rachele Lievore2, Irene C Mammarella3
1Department of Developmental and Social Psychology, University of Padova, Padova, Italy. giulia.crisci@unipd.it.
Purpose:
Facial emotion recognition (FER) enables individuals to interpret emotions, predict intentions, and respond appropriately in social interactions. Difficulties with FER are often associated with neurodevelopmental conditions such as Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD), while less is known about its impact on individuals with Specific Learning Disorders (SLD). Few studies have compared FER across these groups.
Methods:
To address this gap, we evaluated FER in 540 children and adolescents aged 8 to 16 years old autistic (N = 80), ADHD (N = 80), and SLD (N = 80), compared to a control group (CG; N = 300), matched for age, sex and intelligence quotient. We used a FER task that varied in task type - matching (comparing whether two facial expressions convey the same or different emotions) vs. labeling (identifying the specific emotion depicted by a facial expression), emotions' intensity (high vs. low), and type of emotion (anger, disgust, fear, happiness, sadness, surprise).
Results:
Mixed-effects models revealed significant difficulties in the ASD and ADHD groups, particularly in the matching task. In contrast, the labeling task revealed broader challenges across all clinical groups compared to CG, with distinct emotion-specific patterns: children with ADHD had difficulty recognizing nearly all emotional expressions; the ASD group exhibited strengths in labeling anger but had difficulty with surprise and disgust; and the SLD group showed low scores with disgust. In both types of tasks, high-intensity emotions were more easily recognized than low-intensity ones across all groups.
Conclusion:
These findings underscore the importance of considering task demands, intensity levels, emotion types, and individual developmental profiles when assessing emotional functioning in clinical populations.
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