Brain network simulations derived from fMRI and structural MRI from 50 healthy participants, age range 18-80 years (1.0)

We present simulation results from a study with The Virtual Brain (TVB). Structural, functional and simulated data have been prepared in accordance with [Brain Imaging Data Structure (BIDS)](https://bids.neuroimaging.io/) standards and annotated according to the [openMINDS](https://openminds-documentation.readthedocs.io/en/latest/) metadata framework. This simultaneous electroencephalography (EEG) - functional magnetic resonance imaging (fMRI) resting-state data, diffusion-weighted MRI (dwMRI), and structural MRI were acquired for 50 healthy adult subjects (18 - 80 years of age, mean 41.12±18.20; 30 females, 20 males) at the Berlin Center for Advanced Imaging, Charité University Medicine, Berlin, Germany. We constructed personalized models from this multimodal data of 50 healthy individuals with TVB. We calculated the optimal parameters on an individual basis that predict multiple empirical features in fMRI and EEG, e.g. dynamic functional connectivity and bimodality in the alpha band power, and analyzed inter-individual differences with respect to optimized parameters and structural as well as functional connectivity in a previous study ([Triebkorn et al. 2024](https://doi.org/10.1101/2020.03.26.009795)). We present this large comprehensive empirical and simulated data set in an annotated and structured format following the BIDS Extension Proposal for computational modeling data. We describe how we processed and converted the diverse data sources to make it reusable. In its current form, this dataset can be reused for further research and provides ready-to-use data at various levels of processing including the thereof inferred brain simulation results for a large data set of healthy subjects with a wide age range.