# Reproducible Sex Differences in Personalized Functional Network Topography in Youth

## TL;DR

This study finds reproducible sex differences in brain network organization in youth, which may help explain why mental health disorders are more common in females.

## Contribution

The study identifies robust sex differences in personalized functional brain network topography during the transition to adolescence.

## Key findings

- Sex differences in PFN topography were most prominent in association networks like fronto-parietal and default mode networks.
- Machine learning models accurately classified sex based on PFN topography patterns.
- These differences are reproducible across large youth samples and may relate to female-biased mental health risks.

## Abstract

A key step towards understanding psychiatric disorders that disproportionately impact female mental health is delineating the emergence of sex-specific patterns of brain organization at the critical transition from childhood to adolescence. Prior work suggests that individual differences in the spatial organization of functional brain networks across the cortex are associated with psychopathology and differ systematically by sex.

We aimed to evaluate the impact of sex on the spatial organization of person-specific functional brain networks.

We leveraged person-specific atlases of functional brain networks defined using non-negative matrix factorization in a sample of n = 6437 youths from the Adolescent Brain Cognitive Development Study. Across independent discovery and replication samples, we used generalized additive models to uncover associations between sex and the spatial layout (“topography”) of personalized functional networks (PFNs). We also trained support vector machines to classify participants’ sex from multivariate patterns of PFN topography.

Sex differences in PFN topography were greatest in association networks including the fronto-parietal, ventral attention, and default mode networks. Machine learning models trained on participants’ PFNs were able to classify participant sex with high accuracy.

Sex differences in PFN topography are robust, replicate across large-scale samples of youth. These results suggest a potential contributor to the female-biased risk in depressive and anxiety disorders that emerge at the transition from childhood to adolescence.