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Sex Differences in Functional Topography of Association Networks
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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 nonnegative matrix factorization) to define individualized functional networks in 693 youth (ages 8-23 years) who underwent functional magnetic resonance imaging as part of the Philadelphia Neurodevelopmental Cohort. Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 83% accuracy (
p
<0.0001). Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention and default mode networks. Mass-univariate analyses using generalized additive models with penalized splines provided convergent results. Comparative analysis using transcriptomic data from the Allen Human Brain Atlas revealed that sex differences in multivariate patterns of functional topography correlated with the expression of genes on the X-chromosome. These results identify normative developmental sex differences in the functional topography of association networks and highlight the role of sex as a biological variable in shaping brain development in youth.
SIGNIFICANCE STATEMENT
We identify normative developmental sex differences in the functional topography of personalized association networks including the ventral attention network and default mode network. Furthermore, chromosomal enrichment analyses revealed that sex differences in multivariate patterns of functional topography were spatially coupled to the expression of X-linked genes as well as astrocytic and excitatory neuronal cell-type signatures. These results highlight the role of sex as a biological variable in shaping functional brain development in youth.
openRxiv
Sheila Shanmugan
Jakob Seidlitz
Zaixu Cui
Azeez Adebimpe
Danielle S. Bassett
Maxwell A. Bertolero
Christos Davatzikos
Damien A. Fair
Raquel E. Gur
Ruben C. Gur
Bart Larsen
Hongming Li
Adam Pines
Armin Raznahan
David R. Roalf
Russell T. Shinohara
Jacob Vogel
Daniel H. Wolf
Yong Fan
Aaron Alexander-Bloch
Theodore D. Satterthwaite
Title: Sex Differences in Functional Topography of Association Networks
Description:
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 nonnegative matrix factorization) to define individualized functional networks in 693 youth (ages 8-23 years) who underwent functional magnetic resonance imaging as part of the Philadelphia Neurodevelopmental Cohort.
Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 83% accuracy (
p
<0.
0001).
Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention and default mode networks.
Mass-univariate analyses using generalized additive models with penalized splines provided convergent results.
Comparative analysis using transcriptomic data from the Allen Human Brain Atlas revealed that sex differences in multivariate patterns of functional topography correlated with the expression of genes on the X-chromosome.
These results identify normative developmental sex differences in the functional topography of association networks and highlight the role of sex as a biological variable in shaping brain development in youth.
SIGNIFICANCE STATEMENT
We identify normative developmental sex differences in the functional topography of personalized association networks including the ventral attention network and default mode network.
Furthermore, chromosomal enrichment analyses revealed that sex differences in multivariate patterns of functional topography were spatially coupled to the expression of X-linked genes as well as astrocytic and excitatory neuronal cell-type signatures.
These results highlight the role of sex as a biological variable in shaping functional brain development in youth.
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