SC-FC coupling

This is the analysis scripts of SC-FC coupling for paper Heritability and interindividual variability of regional structure-function coupling. All data is created randomly for demonstration purpose.

Requirements

1. Install Python by following instructions here: https://www.python.org/downloads/
2. Install Matlab by following instructions here: https://www.mathworks.com/help/install/install-products.html
3. pip -r install requirements.txt

Steps

1. At your terminal, run glm_demo.py to get the SC-FC coupling and GLM results saved in data directory and glm_res directory.
2. In your MATLAB, run herit_demo.m to get the heritability estimates of some random phenotypes you created.

Expected output

1. Under the data directory, you will have your self-generated SC, FC and SC-FC coupling data for the number of subjects you specify. Also there will be covariates data (age, sex, cognition, ICV and motion) if you do GLM analysis.
2. Under the glm_res directory, you will have a series of txt files named GLMvar?prec/corr_all/sigroi.txt which contains the -log(p) values for different covariates (index by number ?). allroi files contains -log(p) value for all the regions while sigroi files only contains regions that are significant with other regions masked as 0. There is another mat file named GLM_'corr/prec'_confint.mat which contains the confident interval for the GLM results. Under the herit_res directory, you will have a file named herit_cp.mat which is the heritability estimates using the LME model.

References

Gu, Z., Jamison, K. W., Sabuncu, M. R., & Kuceyeski, A. (2021). Heritability and interindividual variability of regional structure-function coupling. Nature Communications, 12(1), 1-12.

Ge, T., Holmes, A. J., Buckner, R. L., Smoller, J. W., & Sabuncu, M. R. (2017). Heritability analysis with repeat measurements and its application to resting-state functional connectivity. Proceedings of the National Academy of Sciences, 114(21), 5521-5526.