1000BRAINS study, connectivity data

The human brain shows considerable interindividual variability, particularly during the course of aging, which is influenced by genetic and environmental factors. To characterize this variability across a wide range of subjects in the general population, large cohort data including brain imaging as well as a variety of phenotypic data are required. The 1000BRAINS study, which is based on the population-based Heinz Nixdorf Recall Study of the University of Duisburg-Essen (Germany), aims at studying this variability of brain structure, function and connectivity as well as cognition particularly in the older population in relation to influences such as genetic factors, lifestyle, urban environment or health conditions. The current data set on whole brain connectivity matrices of the HBP Human Brain Atlas regions reflects the variability of structural connections (i.e. fiber tracts) in this 1000BRAINS population sample. Structural connectivity data have been derived from diffusion-weighted magnetic resonance imaging (MRI) data (b=2700 s/mm2) obtained on a 3T MR scanner and processed with a standardized pipeline for fiber tract reconstructions based on the local constrained spherical deconvolution model for modelling the diffusion signal as implemented in MRtrix 3.0. Connectivity from each HBP Atlas region to all other brain regions was estimated as streamline counts for each participant, resulting in a connectivity matrix per brain region describing the connection strength to each other brain region as mean and per subject individual values. A new data version of “1000BRAINS study, connectivity data” can be found here: Caspers, S., & Schreiber, J. (2020) [Data set, v1.1] [DOI: 10.25493/6640-3XH](https://doi.org/10.25493%2F6640-3XH)