Clinical Research Group 247, Movement Disorders Section, Department of Neurology, Charité - University Medicine (CVK), Berlin, Germany; Center for Adaptive Rationality (ARC), Max-Planck-Institute for Human Development, Berlin, Germany.
Center for Adaptive Rationality (ARC), Max-Planck-Institute for Human Development, Berlin, Germany; Neurocomputation and Neuroimaging Unit, Department of Education and Psychology, Freie Universität Berlin, 14195 Berlin, Germany.
Neuroimage. 2016 Jan 1;124(Pt A):310-322. doi: 10.1016/j.neuroimage.2015.08.048. Epub 2015 Aug 29.
The analysis of the structural architecture of the human brain in terms of connectivity between its subregions has provided profound insights into its underlying functional organization and has coined the concept of the "connectome", a structural description of the elements forming the human brain and the connections among them. Here, as a proof of concept, we introduce a novel group connectome in standard space based on a large sample of 169 subjects from the Enhanced Nathan Kline Institute-Rockland Sample (eNKI-RS). Whole brain structural connectomes of each subject were estimated with a global tracking approach, and the resulting fiber tracts were warped into standard stereotactic (MNI) space using DARTEL. Employing this group connectome, the results of published tracking studies (i.e., the JHU white matter and Oxford thalamic connectivity atlas) could be largely reproduced directly within MNI space. In a second analysis, a study that examined structural connectivity between regions of a functional network, namely the default mode network, was reproduced. Voxel-wise structural centrality was then calculated and compared to others' findings. Furthermore, including additional resting-state fMRI data from the same subjects, structural and functional connectivity matrices between approximately forty thousand nodes of the brain were calculated. This was done to estimate structure-function agreement indices of voxel-wise whole brain connectivity. Taken together, the combination of a novel whole brain fiber tracking approach and an advanced normalization method led to a group connectome that allowed (at least heuristically) performing fiber tracking directly within MNI space. Such an approach may be used for various purposes like the analysis of structural connectivity and modeling experiments that aim at studying the structure-function relationship of the human connectome. Moreover, it may even represent a first step toward a standard DTI template of the human brain in stereotactic space. The standardized group connectome might thus be a promising new resource to better understand and further analyze the anatomical architecture of the human brain on a population level.
从连接各脑区的角度分析人类大脑的结构体系为揭示其潜在的功能组织提供了深刻的见解，并由此产生了“连接组”这一概念，即对构成人类大脑的要素及其相互连接的结构描述。在这里，作为概念验证，我们基于增强内森·克莱恩研究所-罗克兰样本（eNKI-RS）中的 169 名受试者的大样本，引入了一种新的标准空间群组连接组。采用全局追踪方法对每个个体的全脑结构连接组进行了估计，并用 DARTEL 将所得的纤维束变形到标准的立体定向（MNI）空间。利用这个群组连接组，可以在 MNI 空间内直接再现发表的追踪研究结果（即 JHU 白质和牛津丘脑连接图谱）。在第二项分析中，重现了一项研究结构连接的研究，即功能网络（即默认模式网络）之间的结构连接。然后计算了体素的结构中心度，并与他人的发现进行了比较。此外，还包括来自相同受试者的额外静息态 fMRI 数据，计算了大脑大约 4 万个节点之间的结构和功能连接矩阵。这是为了估计体素全脑连接的结构-功能一致性指数。总之，结合一种新的全脑纤维追踪方法和一种先进的归一化方法，得到了一个群组连接组，该群组连接组允许（至少是启发式地）在 MNI 空间内直接进行纤维追踪。这种方法可用于各种目的，如结构连接分析和旨在研究人类连接组结构-功能关系的建模实验。此外，它甚至可能是在立体定向空间中建立人类大脑标准 DTI 模板的第一步。因此，标准化的群组连接组可能是一种有前途的新资源，可以在人群水平上更好地理解和进一步分析人类大脑的解剖结构。
