Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan; Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan.
Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan; Department of Neurology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan; Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan.
Neuroimage. 2020 Nov 15;222:117241. doi: 10.1016/j.neuroimage.2020.117241. Epub 2020 Aug 14.
Neuroimaging studies have shown that the brain is functionally organized into several large-scale brain networks. Within these networks are regions that are widely connected to several other regions within and/or outside the network. Regions that connect to several other networks, known as connector hubs, are believed to be crucial for information transfer and between-network communication within the brain. To identify regions with high between-network connectivity at the voxel level, we introduced a novel metric called functional connectivity overlap ratio (FCOR), which quantifies the spatial extent of a region's connection to a given network. Using resting state functional magnetic resonance imaging data, FCOR maps were generated for several well-known large-scale resting state networks (RSNs) and used to examine the relevant associations among different RSNs, identify connector hub regions in the cerebral cortex, and elucidate the hierarchical functional organization of the brain. Constructed FCOR maps revealed a strong association among the core neurocognitive networks (default mode, salience, and executive control) as well as among primary processing networks (sensorimotor, auditory, and visual). Prominent connector hubs were identified in the bilateral middle frontal gyrus, posterior cingulate, lateral parietal, middle temporal, dorsal anterior cingulate, and anterior insula, among others, regions mostly associated with the core neurocognitive networks. Finally, clustering the whole brain using FCOR features yielded a topological organization that arranges brain regions into a hierarchy of information processing systems with the primary processing systems at one end and the heteromodal systems comprising connector hubs at the other end.
神经影像学研究表明，大脑在功能上组织成几个大规模的脑网络。在这些网络中，有一些区域与网络内和/或网络外的几个其他区域广泛连接。连接到几个其他网络的区域，称为连接器枢纽，被认为是大脑内信息传递和网络间通信的关键。为了在体素水平上识别具有高网络间连通性的区域，我们引入了一种新的度量标准，称为功能连接重叠比（FCOR），它量化了一个区域与给定网络连接的空间范围。使用静息态功能磁共振成像数据，为几个著名的大规模静息态网络（RSN）生成了 FCOR 图，并用于研究不同 RSN 之间的相关关联，识别大脑皮质中的连接器枢纽区域，并阐明大脑的分层功能组织。构建的 FCOR 图揭示了核心神经认知网络（默认模式、突显和执行控制）之间以及主要处理网络（感觉运动、听觉和视觉）之间存在很强的关联。在双侧额中回、后扣带、外侧顶叶、颞中回、背侧前扣带和前岛叶等区域中发现了显著的连接器枢纽，这些区域主要与核心神经认知网络相关。最后，使用 FCOR 特征对整个大脑进行聚类，产生了一种拓扑组织，将大脑区域排列成一个信息处理系统的层次结构，一端是主要处理系统，另一端是由连接器枢纽组成的异模态系统。
