Code/Resources — Brain networks & behavior lab

Matlab code for generating spatially-constrained synthetic time series using a phase-randomization procedure [Link to code]. If you use this code, please cite:Zamani Esfahlani, F., Bertolero, M.A., Bassett, D.S., Betzel, R.F. (2019). Space-independe… — Matlab code for generating spatially-constrained synthetic time series using a phase-randomization procedure [Link to code]. If you use this code, please cite:
Zamani Esfahlani, F., Bertolero, M.A., Bassett, D.S., Betzel, R.F. (2019). Space-independent community and hub structure of functional brain networks. [Link to paper]

Matlab code for generating visually appealing force-directed (and community-labeled) networks. [Link to code]

Matlab code for generating distance-dependent consistency matrices [Link to code]. If you use this code, please cite:Betzel, R. F., Griffa, A., Hagmann, P., & Mišić, B. (2018). Distance-dependent consensus thresholds for generating group-represe… — Matlab code for generating distance-dependent consistency matrices [Link to code]. If you use this code, please cite:
Betzel, R. F., Griffa, A., Hagmann, P., & Mišić, B. (2018). Distance-dependent consensus thresholds for generating group-representative structural brain networks. Network Neuroscience, 1-22. [Link to paper]
Note: the code provided here bins connections by distance and seems to avoid overfitting issues that we sometimes observed with the previous version. The original code can be found here [Link to code].

Matlab code for generative modeling of structural connectivity matrices [Link to code]. If you use this code, please cite:Betzel, R. F., Avena-Koenigsberger, A., Goñi, J., He, Y., De Reus, M. A., Griffa, A., ... & Van Den Heuvel, M. (2016). Gene… — Matlab code for generative modeling of structural connectivity matrices [Link to code]. If you use this code, please cite:
Betzel, R. F., Avena-Koenigsberger, A., Goñi, J., He, Y., De Reus, M. A., Griffa, A., ... & Van Den Heuvel, M. (2016). Generative models of the human connectome. Neuroimage, 124, 1054-1064. [Link to paper]

Matlab code for fitting weighted stochastic blockmodel. [Link to code] If you use the code, please cite:Betzel, R. F., Medaglia, J. D., & Bassett, D. S. (2018). Diversity of meso-scale architecture in human and non-human connectomes. Nature comm… — Matlab code for fitting weighted stochastic blockmodel. [Link to code] If you use the code, please cite:
Betzel, R. F., Medaglia, J. D., & Bassett, D. S. (2018). Diversity of meso-scale architecture in human and non-human connectomes. Nature communications, 9(1), 346. [Link to paper]
Betzel, R. F., Bertolero, M. A., & Bassett, D. S. (2018). Non-assortative community structure in resting and task-evoked functional brain networks. bioRxiv, 355016. [Link to paper]
Aicher, C., Jacobs, A. Z., & Clauset, A. (2014). Learning latent block structure in weighted networks. Journal of Complex Networks, 3(2), 221-248. [Link to paper, Link to toolbox]

Matlab code for generating surrogate networks that preserve degree distribution (exactly), distribution of physical connection lengths (approximately), and the weight-length relationship (approximately). [Link to code]. If you use this code, please … — Matlab code for generating surrogate networks that preserve degree distribution (exactly), distribution of physical connection lengths (approximately), and the weight-length relationship (approximately). [Link to code]. If you use this code, please cite:
Betzel, R. F., & Bassett, D. S. (2018). Specificity and robustness of long-distance connections in weighted, interareal connectomes. Proceedings of the National Academy of Sciences, 115(21), E4880-E4889. [Link to paper]

Matlab code for sampling multi-layer, multi-resolution, multi-subject communities using modularity maximization [Link to code]. If you use this code, please cite:Betzel, R. F., Bertolero, M. A., Gordon, E. M., Gratton, C., Dosenbach, N. U., & Ba… — Matlab code for sampling multi-layer, multi-resolution, multi-subject communities using modularity maximization [Link to code]. If you use this code, please cite:
Betzel, R. F., Bertolero, M. A., Gordon, E. M., Gratton, C., Dosenbach, N. U., & Bassett, D. S. (2018). The community structure of functional brain networks exhibits scale-specific patterns of variability across individuals and time. bioRxiv, 413278. [Link to paper]
Note: This code requires the GenLouvain toolbox. Please download [here] and cite both:
Jutla, I. S., Jeub, L. G., & Mucha, P. J. (2011). A generalized Louvain method for community detection implemented in MATLAB. URL http://netwiki. amath. unc. edu/GenLouvain.
Mucha, P. J., Richardson, T., Macon, K., Porter, M. A., & Onnela, J. P. (2010). Community structure in time-dependent, multiscale, and multiplex networks. science, 328(5980), 876-878. [Link to paper]

Matlab code for generating ego-centric co-authorship networks. [Link to code].

Matlab code for generating and clustering edge time series [Link to code]. If you use this code, please cite:Faskowitz, J., Esfahlani, F. Z., Jo, Y., Sporns, O., & Betzel, R. F. (2020). Edge-centric functional network representations of human ce… — Matlab code for generating and clustering edge time series [Link to code]. If you use this code, please cite:
Faskowitz, J., Esfahlani, F. Z., Jo, Y., Sporns, O., & Betzel, R. F. (2020). Edge-centric functional network representations of human cerebral cortex reveal overlapping system-level architecture. Nature Neuroscience. 23, 1644–1654. [Link to preprint]
Jo, Youngheun, et al. "The diversity and multiplexity of edge communities within and between brain systems." bioRxiv (2020). [Link to paper]
Zamani Esfahlani, F., Jo, Y., Faskowitz, J., Byrge, L., Kennedy, D., Sporns, O., Betzel, R.F. (2020). High-amplitude co-fluctuations in cortical activity drive functional connectivity. PNAS, 117(45), 28393–28401. [Link to paper]

Matlab code for generating and analyzing bipartitions of edge time series [Link to code] [Edge time series video]. If you use this code, please cite:Sporns, O., Faskowitz, J., Teixeira, A.S., Cutts, S. Betzel, R.F. (2020). Dynamic Expression of Brai… — Matlab code for generating and analyzing bipartitions of edge time series [Link to code] [Edge time series video]. If you use this code, please cite:
Sporns, O., Faskowitz, J., Teixeira, A.S., Cutts, S. Betzel, R.F. (2020). Dynamic Expression of Brain Functional Systems Disclosed by Fine-Scale Analysis of Edge Time Series. (to appear Network Neuroscience). [Link to paper]
Zamani Esfahlani, F., Jo, Y., Faskowitz, J., Byrge, L., Kennedy, D., Sporns, O., Betzel, R.F. (2020). High-amplitude co-fluctuations in cortical activity drive functional connectivity. PNAS, 117(45), 28393–28401. [Link to paper]

Matlab code for performing optimal control using spatially diffuse inputs [Link to code]. If you use this code, please cite:
Betzel, R. F., Puxeddu, M. G., Seguin, C., Bazinet, V., Luppi, A., Podschun, A., ... & Parkes, L. (2024). Controlling the human connectome with spatially diffuse input signals. bioRxiv, 2024-02.

Matlab code for analyzing high-amplitude frames in edge time series [Link to code]. If you use this code, please cite:Zamani Esfahlani, F., Jo, Y., Faskowitz, J., Byrge, L., Kennedy, D., Sporns, O., Betzel, R.F. (2020). High-amplitude co-fluctuation… — Matlab code for analyzing high-amplitude frames in edge time series [Link to code]. If you use this code, please cite:
Zamani Esfahlani, F., Jo, Y., Faskowitz, J., Byrge, L., Kennedy, D., Sporns, O., Betzel, R.F. (2020). High-amplitude co-fluctuations in cortical activity drive functional connectivity. PNAS, 117(45), 28393–28401. [Link to paper]

Lab logo design by Cai Pyle