No sex differences in predictive processing

Statistical learning, defined as the implicit extraction of environmental regularities, is recognized as a universal and evolutionarily conserved mechanism, and constitutes a fundamental aspect of predictive processing. Still, whether it is modulated by sex or hormonal influences remains an open question. The present study investigated whether statistical learning varies as a function of sex or women’s hormonal status. We re-analyzed data from 473 young adults who completed an online visuomotor Alternating Serial Reaction Time (ASRT) task, comparing (i) age-matched men and women, (ii) women using or not using hormonal contraceptives, and (iii) cycling women across self-reported menstrual phases. Robust statistical learning emerged across all groups. Neither sex, hormonal contraceptive use, nor menstrual phase significantly modulated the magnitude or trajectory of statistical learning. Bayesian analyses consistently favored models excluding group effects. In addition, we observed small but noteworthy baseline differences in visuomotor performance, including faster initial responses in men and a slight premenstrual decline in accuracy. These findings suggest that while implicit statistical learning itself is largely resilient to sex-related and hormonal influences, sex and menstrual cycle may still shape aspects of visuomotor behavior, pointing to distinct levels of sensitivity within predictive cognition.