/sex_diff_gradients

Sex Differences in Functional Organization

Primary LanguageJupyter Notebook

Sex differences in functional brain organization

This is the repository for the publication:

Bianca Serio, Meike D. Hettwer, Lisa Wiersch, Giacomo Bignardi, Julia Sacher, Susanne Weis, Simon B. Eickhoff, & Sofie L. Valk, (2024) Sex differences in functional cortical organization reflect differences in network topology rather than cortical morphometry. Nature Communications, 15, 7714. https://doi.org/10.1038/s41467-024-51942-1.

Preprint version available here

Scripts

1. Preparing the data

  • calculate_fc_matrices_hcp_schaefer.ipynb computes functional connectivity matrices in Schaefer 400 parcellation from the HCP BOLD timeseries (averaged across 4 resting state sessions) at the individual level
  • p1_main_function.ipynb gets the functional connectivity matrices at the individual level
  • p1_main_microstructure.ipynb gets the microstructural intensity profile matrices at the individual level
  • p1_geodesic_distance.ipynb gets the geodesic distance of the functional connectivity profiles at the individual level
  • p1_connectivity_profiles_binary_matrices.py computing binary matrices for the Chi Square test of independence contingency tables
  • p1_connectivity_profiles_strength_fc_sub_level.py computes functional connectivity strength at the subject level for top 10% fucntional connections

2. Main analyses

  • p1_main.ipynb computes and visualizes main analyses
  • p1_main.R computes linear mixed effects models for main analyses
  • p1_connectivity_profiles_sex_diff.py runs Chi Square test of independence on contingency tables, testing for sex differences in the odds of connections belonging to the seed's top 10% functional connections at the individual level
  • p1_spin_permutation_lmer_within_between_network_dispersion.py spin permutation test to construct empirical null distribution of beta values for within and between network dispersion analyses

3. Functions

  • p1_myfunctions.ipynb contains functions used for main analyses

Data

  • Sample includes young adults (N=1000) from Human Connectome Project (HCP) S1200 release
  • Source Data.ods contains the source data used to make all figures included in the publication

Support

Please address any questions about the analyses or code to Bianca Serio


Research poster presented at:

  • Annual Meeting of the Organization for Human Brain Mapping (OHBM), Montreal 2023
  • Annual meeting of the Organization for the Study of Sex Differences (OSSD), Bergen 2024

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