Institute of Neuroscience, Newcastle University, United Kingdom.
Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, United Kingdom.
Sci Rep. 2017 Jan 5;7:39859. doi: 10.1038/srep39859.
Previous structural brain connectivity studies have mainly focussed on the macroscopic scale of around 1,000 or fewer brain areas (network nodes). However, it has recently been demonstrated that high resolution structural connectomes of around 50,000 nodes can be generated reproducibly. In this study, we infer high resolution brain connectivity matrices using diffusion imaging data from the Human Connectome Project. With such high resolution we are able to analyse networks within brain areas in a single subject. We show that the global network has a scale invariant topological organisation, which means there is a hierarchical organisation of the modular architecture. Specifically, modules within brain areas are spatially localised. We find that long range connections terminate between specific modules, whilst short range connections via highly curved association fibers terminate within modules. We suggest that spatial locations of white matter modules overlap with cytoarchitecturally distinct grey matter areas and may serve as the structural basis for function specialisation within brain areas. Future studies might elucidate how brain diseases change this modular architecture within brain areas.
先前的大脑结构连接研究主要集中在大约 1000 个或更少的脑区(网络节点)的宏观尺度上。然而,最近已经证明,大约 50000 个节点的高分辨率结构连接组图可以被重复生成。在这项研究中,我们使用来自人类连接组计划的扩散成像数据来推断高分辨率的大脑连接矩阵。有了如此高的分辨率,我们能够在单个对象中分析脑区内部的网络。我们表明,全局网络具有标度不变的拓扑组织,这意味着模块结构具有层次组织。具体来说,脑区内部的模块在空间上是局部化的。我们发现,长程连接终止于特定的模块之间,而通过高度弯曲的联合纤维的短程连接则终止于模块内。我们认为,白质模块的空间位置与细胞构筑上不同的灰质区域重叠,并可能作为脑区内部功能特化的结构基础。未来的研究可能阐明脑疾病如何改变脑区内部的这种模块结构。