issue. 

## 5. Appendix 

The main text describes the results of generative models applied to a dataset of 40 participants scanned at CHUV. In this appendix we demonstrate the ro- bustness of those results by reproducing the principal findings using alternative datasets. The additional datasets are described, briefly, below and in more de- tail later in this appendix. Figures S1-S9 shows model energies for each of the additional datasets, reproducing Figure 2 from the main text. 

1. Two replication datasets (HCP and NKI) of N = 214 and N = 126 participants, respectively. 

2. The same CHUV dataset with different levels of network density (5% and 15%) and defined using an alternative weighting. 

3. CHUV dataset including both left/right cerebral hemispheres. 

4. Composite (i.e. group averaged) CHUV, HCP, and NKI connectomes. 

5. Composite CHUV dataset using fiber length in place of Euclidean distance. 

6. Composite CHUV dataset using an exponential function to model geo- metric constraints in place of the power-law function. 

7. Composite CHUV dataset using a finer cortical parcellation ( n = 223 nodes.) 

Each additional dataset is accompanied by a figure showing the energy dis- tribution for the 100 best-fitting synthetic networks for each model type. At the end of this appendix we have also included a glossary of graph theoretic terms that appear throughout the main text. 

