ArticleiScience2026
A novel computational approach to isolating mechanisms of cognitive development across two systems: scene categorization and visually guided navigation.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Computational models propose that cognitive development reflects greater evidence accumulation efficiency, but it remains unclear whether these gains stem from increased accumulation of correct information, reduced accumulation of incorrect information, or both-and if these processes differ across domains. Taking a computational approach, we tested these possibilities in two distinct cognitive systems: scene categorization and visually guided navigation. Ninety-five participants (ages 4-21) completed tasks in each domain. Accuracy and reaction times were fit with the linear ballistic accumulator model to estimate separate accumulation rates for correct and incorrect information. For scene categorization, only the correct accumulation rate increased with age, indicating a selective enhancement in accumulation efficiency. Conversely, for visually guided navigation, both correct and incorrect accumulation rates changed, reflecting broader efficiency gains. Together, these findings formally characterize the unique developmental mechanisms driving scene categorization and visually guided navigation while demonstrating the utility of this modeling approach across any cognitive system.
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