No gender differences in predictive processing

Abstract

Statistical learning, defined as the implicit extraction of environmental regularities, is considered a fundamental cognitive mechanism that supports predictive processing across individuals, domains, and species. However, whether it is modulated by gender remains unclear. This study investigated potential gender-related differences in statistical learning using an age-matched sample of 129 women and 129 men (N = 258) who completed a well-established visuomotor probabilistic learning task. Statistical learning was revealed in both reaction time and accuracy measures, with participants responding faster and more accurately to high-probability than to low-probability trials. Critically, neither the magnitude nor the trajectory of statistical learning differed between women and men. Furthermore, no baseline differences in visuomotor performance interacted with learning metrics. Overall, these findings suggest that implicit statistical learning is a robust cognitive mechanism that is highly resilient to gender-related variation. Highlights Implicit statistical learning was robust in both women and men, with no evidence for gender differences in the magnitude or trajectory of learning. Although a minor baseline difference in general response speed was observed, this effect did not interact with or influence statistical learning. Statistical learning was robust across menstrual cycle phases and hormonal contraceptive use groups. The findings suggest that the "predictive brain" relies on fundamental, evolutionarily conserved mechanisms that are largely resilient to gender-based variation.