Acknowledgements

• I would like to express my deepest appreciation to Google Summer of Code for hosting the program and provided me with the opportunity to engage in open source community.
• I would like to express my special thanks of gratitude to my mentors Daniele Marinazzo and Hannelore Aerts who helped me to coordinate my project and provided with insight and expertise.
• I would like to thank the Human Brain Project: European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2) for the contribution to human brain research.

References

• Aerts, H., Fias, W., Caeyenberghs, K., & Marinazzo, D. (2016). Brain networks under attack: robustness properties and the impact of lesions. Brain : A Journal of Neurology, 139(12), 3063–3083. doi:10.1093/brain/aww194
• Alstott, J., Breakspear, M., Hagmann, P., Cammoun, L., & Sporns, O. (2009). Modeling the impact of lesions in the human brain. PLoS Computational Biology, 5(6), e1000408. doi:10.1371/journal.pcbi.1000408
• Bernard, C., & Jirsa, V. K. (2017). Virtual Brain for neurological disease modeling. Drug Discovery Today: Disease Models, 19, 5–10. doi:10.1016/j.ddmod.2017.05.001
• Breakspear, M. (2017). Dynamic models of large-scale brain activity. Nature Neuroscience, 20(3), 340–352. doi:10.1038/nn.4497
• Deco, G., Jirsa, V. K., Robinson, P. A., Breakspear, M., & Friston, K. (2008). The dynamic brain: From spiking neurons to neural masses and cortical fields. PLoS Computational Biology, 4(8), e1000092. doi:10.1371/journal.pcbi.1000092
• Deco, G., & Kringelbach, M. L. (2014). Great expectations: Using whole-brain computational connectomics for understanding neuropsychiatric disorders. Neuron, 84, 892–905. doi:10.1016/j.neuron.2014.08.034
• Deco, G., Ponce-Alvarez, A., Hagmann, P., Romani, G. L., Mantini, D., & Corbetta, M. (2014). How local excitation – inhibition ratio impacts the whole brain dynamics. The Journal of Neuroscience, 34(23), 7886–7898. doi:10.1523/JNEUROSCI.5068-13.2014
• Falcon, M. I., Jirsa, V. K., & Solodkin, A. (2016). A new neuroinformatics approach to personalized medicine in neurology. Current Opinion in Neurology, 1. doi:10.1097/WCO.0000000000000344
• Falcon, M. I., Riley, J. D., Jirsa, V. K., McIntosh, A. R., Shereen, A. D., Chen, E. E., & Solodkin, A. (2015). The Virtual Brain: modeling biological correlates of recovery after chronic stroke. Frontiers in Neurology, 6, 228. doi:10.3389/fneur.2015.00228
• Falcon, M. I., Riley, J. D., Jirsa, V. K., McIntosh, A. R., Chen, E. E., & Solodkin, A. (2016). Functional mechanisms of recovery after chronic stroke: Modeling with the Virtual Brain. Eneuro, 3(2), e0158. doi:10.1523/ENEURO.0158-15.2016
• Jirsa, V. K., Proix, T., Perdikis, D., Woodman, M. M., Wang, H., Gonzalez-Martinez, J., … Bartolomei, F. (2017). The Virtual Epileptic Patient: Individualized whole-brain models of epilepsy spread. NeuroImage, 145, 377–388. doi:10.1016/j.neuroimage.2016.04.049
• Jirsa, V. K., Sporns, O., Breakspear, M., Deco, G., & Mcintosh, a. R. (2010). Towards the virtual brain: Network modeling of the intact and the damaged brain. Archives Italiennes de Biologie, 148(3), 189–205. doi:10.4449/aib.v148i3.1223
• Ritter, P., Schirner, M., McIntosh, A. R., & Jirsa, V. K. (2013). The virtual brain integrates computational modeling and multimodal neuroimaging. Brain Connectivity, 3(2), 121–45. doi:10.1089/brain.2012.0120
• Sanz-Leon, P., Knock, S. a, Spiegler, A., & Jirsa, V. K. (2014). Mathematical framework for large-scale brain network modelling in The Virtual Brain. Neuroimage (Submitted).
• Sanz Leon, P., Knock, S. A., Woodman, M. M., Domide, L., Mersmann, J., McIntosh, A. R., & Jirsa, V. K. (2013). The Virtual Brain: a simulator of primate brain network dynamics. Frontiers in Neuroinformatics, 7, 10. doi:10.3389/fninf.2013.00010
• Schirner, M., McIntosh, A. R., Jirsa, V. K., Deco, G., & Ritter, P. (2018). Inferring multi-scale neural mechanisms with brain network modelling. ELife, 7, e28927. doi:10.7554/eLife.28927
• Sinha, N., Dauwels, J., Kaiser, M., Cash, S. S., Westover, M. B., Wang, Y., & Taylor, P. N. (2017). Predicting neurosurgical outcomes in focal epilepsy patients using computational modelling. Brain, 140, 319–332. doi:10.1093/aww332
• Zimmermann, J., Perry, A., Breakspear, M., Schirner, M., Sachdev, P., Wen, W., … Solodkin, A. (2018). Differentiation of Alzheimer’s disease based on local and global parameters in personalized Virtual Brain models. NeuroImage: Clinical, 19(April), 240–251. doi:10.1016/j.nicl.2018.04.017