Computational mechanisms of perception in autism revealed using games inspired by rodent operant tasks

Abstract

Altered perception is a hallmark of autism spectrum disorder (ASD), yet its underlying mechanisms remain unclear, in part because individuals with greater impairments are often excluded from psychophysics research. Here, we introduce GEODE (gathering evidence to optimize decisions), an online video game designed to measure visual perception across the full autism spectrum. GEODE incorporates feedback-based shaping from animal training to teach task mechanics, customized graphics and storyline elements to sustain engagement, and touchscreen compatibility for broader accessibility, enabling participation from adolescents including those with profound autism. Across a large, heterogeneous cohort, autistic participants successfully played GEODE but showed slower learning and reduced accuracy compared with typically developing siblings. These deficits were best explained by increased noise in the integration of sensory evidence, which scaled nonlinearly with stimulus complexity and tracked standardized survey measures of adaptive functioning more closely than diagnostic category alone. Injecting equivalent noise into artificial neural networks produced agents that recapitulated ASD-like patterns of learning and decision-making. These findings implicate noisy evidence integration as a computational mechanism for altered visual perception across the autism spectrum and establish a scalable, accessible platform for probing altered perception and learning in neurodevelopmental and neuropsychiatric disorders.