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ABSTRACT We present raw and processed multimodal empirical data as well as simulation results from a study with The Virtual Brain (TVB). Simultaneous electroencephalography (EEG) - functional magnetic resonance imaging (fMRI) resting-state data, diffusion-weighted MRI, and structural MRI were acquired for 50 healthy adult subjects (18 - 80 years of age) at the Charité University Medicine, Berlin, Germany. We constructed personalized models from this multimodal data with TVB by optimizing 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. We annotated this large comprehensive empirical and simulated data set according to the openMINDS meta data schema and structured it following Brain Imaging Data Structure (BIDS) standards for EEG and MRI as well as the BIDS Extension Proposal for computational modeling data. This dataset provides ready-to-use data for future research 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.
Meier et al. (Sat,) studied this question.