Botia, I. | bioRxiv Science

bioRxiv2026

Serotonergic circuit architecture underlies sex dimorphism in anxiogenic states

The serotonergic system underpins anxiety-like behavior vital for the adaptive response to a new environment. However, our understanding of the neural circuitry underlying the diversity of anxiety-like behaviors across individuals is limited. Whilst previous studies have characterized diverse features related to the neurochemical substrate of serotonergic neurotransmission and behavioral presentation between males and females, no investigations have fully addressed the sexual dimorphism in the structural and functional connectivity of serotonergic circuits. Here, using functional FosTRAP connectivity analysis, we found sex-dependent functional differences in the serotonergic neurons of the dorsal raphe nucleus (DRN), such as enriched connectivity to the amygdala in females, compared to male mice. We also discovered previously unidentified morpho-functional sex-specific differences in DRN serotonergic circuitry that reflects the disparity in behavior presentation. To understand the molecular basis of serotonergic circuit architecture differences between sexes, we leveraged on single-cell RNA sequencing dataset from DRN serotonergic cells taking sex as a biological variable and spotted some gene candidates involved in neural circuit wiring. Altering the expression of the receptor tyrosine kinase Erbb4 in serotonergic circuits, altered the axonal connectivity to downstream targets and shifted sex-specific behavior which. Overall, this study provides an essential foundation to delineate the molecular basis and connectivity pattern mechanisms underlying the serotonergic system-dependent sex-specific behaviors. Since alterations in serotonin function play a vital role in adaptive behavior, as well as various pathologies including chronic anxiety and depression, this study may advance our understanding of sex-biases in presentation and treatment response of neuropsychiatric disorders.

neuroscience↗

bioRxiv2025

No sex differences in predictive processing

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.

neuroscience↗