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No gender differences in predictive processing
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DOI：10.1038/s41598-026-63997-9.png)
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Abstract
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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.
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