Sex differences in the functional topography of association networks in youth.
Proc Natl Acad Sci U S A
; 119(33): e2110416119, 2022 08 16.
Article
in En
| MEDLINE
| ID: mdl-35939696
ABSTRACT
Prior work has shown that there is substantial interindividual variation in the spatial distribution of functional networks across the cerebral cortex, or functional topography. However, it remains unknown whether there are sex differences in the topography of individualized networks in youth. Here, we leveraged an advanced machine learning method (sparsity-regularized non-negative matrix factorization) to define individualized functional networks in 693 youth (ages 8 to 23 y) who underwent functional MRI as part of the Philadelphia Neurodevelopmental Cohort. Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 82.9% accuracy (P < 0.0001). Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention, default mode, and frontoparietal networks. Mass univariate analyses using generalized additive models with penalized splines provided convergent results. Furthermore, transcriptomic data from the Allen Human Brain Atlas revealed that sex differences in multivariate patterns of functional topography were spatially correlated with the expression of genes on the X chromosome. These results highlight the role of sex as a biological variable in shaping functional topography.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Cerebral Cortex
/
Sex Characteristics
/
Neural Pathways
Type of study:
Prognostic_studies
/
Risk_factors_studies
Limits:
Adolescent
/
Adult
/
Child
/
Female
/
Humans
/
Male
Language:
En
Journal:
Proc Natl Acad Sci U S A
Year:
2022
Type:
Article