Work

Invariant response to faces in ASD: Unexpected trajectory of oculo-pupillometric biomarkers from childhood to adulthood

Year: 2025

Type: article

Abstract: Human faces contain a large amount of information, attracting our attention and inducing physiological engagement. Attraction to human faces can be observed from birth and develops with age and social experience. The oculometric (visual exploration) and pupillometric (physiological reactivity) parameters quantified by eye-tracking can be relevant measures to study attractiveness and engagement with human faces. Autistic people have particularities in terms of visual exploration and physiological reactivity to faces, with a reduction in the time spent on the eyes associated with a reduced pupil dilation. To date, no study has assessed the developmental dynamics of oculo-pupillometric parameters in response to faces. This study aimed to characterize these parameters throughout typical and autistic development. 109 autistic participants (3-34 years old) were compared to 150 neurotypical participants (3-32 years old). Visual stimuli were organized along a gradient of social saliency, going from static objects to static neutral faces, dynamic neutral faces and dynamic emotional faces. Ocular exploration and physiological reactivity in response to faces appear invariant throughout life in the autistic population. Their developmental dynamics differ from those of the neurotypical population, which shows first, an increasing attentional focus on the eye region with age, and second, a pupillary hypersensitivity to social salient stimuli at an early age which then decreases linearly. Our results highlight an apparent lack of maturation of face processing in the case of autism spectrum disorder (ASD) at the population level, possibly hiding atypical and complex individual developmental trajectories. On the other hand, the neurotypical population exhibits a maturation of both oculometric and pupillometric parameters, pointing towards limited age windows in which specific parameters could be used as discriminating biomarkers of ASD.

Source: Brain Research

DOI: 10.1016/j.brainres.2025.150070