This repository includes .mat files of Virtual Cohort data released together with the article:
Virtual connectomic datasets in Alzheimer’s Disease and aging using whole-brain network dynamics modelling
Lucas Arbabyazd, Kelly Shen, Zheng Wang, Martin Hofmann-Apitius, Petra Ritter, The Alzheimer’s Disease Neuroimaging Initiative, Anthony R. McIntosh, Demian Battaglia & Viktor Jirsa (2021) bioRxiv 2020.01.18.911248; doi: https://doi.org/10.1101/2020.01.18.911248
It includes thus (bi)virtual Functional Connectomes and (bi)virtual Structural Connectomes, generated with linear (SLM) and nonlinear (MFM) Virtual Brain models, starting from an ADNI-derived dataset and an additional Healthy Aging dataset as well.
We also include fast .m files for MATLAB to quickly generate new connectomes of similar type using a "quick-and-dirty" implementation of our data completion pipelines.
For more details, see the article.