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.

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.

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

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-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.

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.

 
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 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 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 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 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 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]