1000BRAINS study, connectivity data (v1.1)

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.

人类大脑存在显著的个体间差异，尤其在衰老过程中，这种差异受遗传与环境因素的共同影响。为了刻画普通人群中广泛受试者的这种差异，需要包含脑成像及多种表型数据的大型队列数据。

1000BRAINS研究基于德国杜伊斯堡-埃森大学开展的人群队列研究——Heinz Nixdorf Recall Study，旨在探究老年人脑结构、功能、连接性及认知能力的个体间差异，并分析其与遗传因素、生活方式、城市环境或健康状况等影响因素的关联。

本数据集包含基于HBP人脑图谱（HBP Human Brain Atlas）区域的全脑连接矩阵，反映了1000BRAINS人群样本中脑结构连接（即纤维束，fiber tracts）的个体间差异。

结构连接数据来源于3T磁共振扫描仪获取的扩散加权磁共振成像（diffusion-weighted magnetic resonance imaging, MRI）数据（b值=2700 s/mm²），并通过标准化流程进行纤维束重建——该流程采用MRtrix 3.0中实现的局部约束球面反卷积模型（local constrained spherical deconvolution model）对扩散信号进行建模。

对于每个受试者，我们以流线计数（streamline counts）估算HBP图谱中每个区域与其他所有脑区的连接强度，最终生成每个脑区对应的连接矩阵——该矩阵包含各脑区间连接强度的均值及个体值。