Quantifying sex differences in brain network topology by aggregating nodal centrality rankings
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866913537741291520 |
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| author | Chen, Wenyu Zhan, Ling Luo, Yunsong Qiu, Jiang Jia, Tao |
| author_facet | Chen, Wenyu Zhan, Ling Luo, Yunsong Qiu, Jiang Jia, Tao |
| contents | Although numerous studies report significant sex differences in functional connectivity, these differences do not sufficient to reveal specific functional disparities among brain regions or the topological differences in brain networks. Meanwhile, individual differences could potentially bias the understanding of these sex differences. To address these challenges, we propose a consensus rank-based method to quantify sex differences in four node centrality ranking within the functional brain network. This method aggregates individuals' nodal centrality rankings into a consensus or "average" ranking, minimizing the impact of outliers and enhancing the robustness of the findings. By analyzing resting-state functional MRI data from 1,948 healthy young adults (aged 18-27 years, 1,163 females), we find significant sex differences in the topology of functional brain network, primarily attributed to biological sex rather than individual differences. Particularly, sex accounts for approximately 10% of the differences in nodal centrality consensus rankings. Using a rank difference index (RDI), we identify eight critical brain regions with the greatest rank differences, including the insula, supramarginal gyrus, and dorsolateral superior frontal gyrus. females show higher rankings in regions with stronger intra-system connections, whereas males dominate in areas with stronger inter-system connections. Our findings enhance our understanding of sex-specific characteristics in functional brain networks. Moreover, our approach may offer novel insights into targeted population studies, including those involving healthy individuals and patients with brain injuries. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2410_05923 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Quantifying sex differences in brain network topology by aggregating nodal centrality rankings Chen, Wenyu Zhan, Ling Luo, Yunsong Qiu, Jiang Jia, Tao Quantitative Methods Although numerous studies report significant sex differences in functional connectivity, these differences do not sufficient to reveal specific functional disparities among brain regions or the topological differences in brain networks. Meanwhile, individual differences could potentially bias the understanding of these sex differences. To address these challenges, we propose a consensus rank-based method to quantify sex differences in four node centrality ranking within the functional brain network. This method aggregates individuals' nodal centrality rankings into a consensus or "average" ranking, minimizing the impact of outliers and enhancing the robustness of the findings. By analyzing resting-state functional MRI data from 1,948 healthy young adults (aged 18-27 years, 1,163 females), we find significant sex differences in the topology of functional brain network, primarily attributed to biological sex rather than individual differences. Particularly, sex accounts for approximately 10% of the differences in nodal centrality consensus rankings. Using a rank difference index (RDI), we identify eight critical brain regions with the greatest rank differences, including the insula, supramarginal gyrus, and dorsolateral superior frontal gyrus. females show higher rankings in regions with stronger intra-system connections, whereas males dominate in areas with stronger inter-system connections. Our findings enhance our understanding of sex-specific characteristics in functional brain networks. Moreover, our approach may offer novel insights into targeted population studies, including those involving healthy individuals and patients with brain injuries. |
| title | Quantifying sex differences in brain network topology by aggregating nodal centrality rankings |
| topic | Quantitative Methods |
| url | https://arxiv.org/abs/2410.05923 |