Brainnetome Center, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
Institute of Neuroscience and Medicine (INM-2), Forschungszentrum Jülich, Jülich 52428, Germany.
J Neurosci. 2024 Mar 27;44(13):e0856232024. doi: 10.1523/JNEUROSCI.0856-23.2024.
Large-scale functional networks are spatially distributed in the human brain. Despite recent progress in differentiating their functional roles, how the brain navigates the spatial coordination among them and the biological relevance of this coordination is still not fully understood. Capitalizing on canonical individualized networks derived from functional MRI data, we proposed a new concept, that is, co-representation of functional brain networks, to delineate the spatial coordination among them. To further quantify the co-representation pattern, we defined two indexes, that is, the co-representation specificity (CoRS) and intensity (CoRI), for separately measuring the extent of specific and average expression of functional networks at each brain location by using the data from both sexes. We found that the identified pattern of co-representation was anchored by cortical regions with three types of cytoarchitectural classes along a sensory-fugal axis, including, at the first end, primary (idiotypic) regions showing high CoRS, at the second end, heteromodal regions showing low CoRS and high CoRI, at the third end, paralimbic regions showing low CoRI. Importantly, we demonstrated the critical role of myeloarchitecture in sculpting the spatial distribution of co-representation by assessing the association with the myelin-related neuroanatomical and transcriptomic profiles. Furthermore, the significance of manifesting the co-representation was revealed in its prediction of individual behavioral ability. Our findings indicated that the spatial coordination among functional networks was built upon an anatomically configured blueprint to facilitate neural information processing, while advancing our understanding of the topographical organization of the brain by emphasizing the assembly of functional networks.
大规模的功能网络在人类大脑中呈空间分布。尽管最近在区分它们的功能作用方面取得了进展，但大脑如何在它们之间进行空间协调，以及这种协调的生物学相关性仍然没有完全被理解。利用从功能磁共振成像数据中得出的规范的个体化网络，我们提出了一个新概念，即功能脑网络的共表示，以描绘它们之间的空间协调。为了进一步量化共表示模式，我们定义了两个指标，即共表示特异性（CoRS）和强度（CoRI），用于分别测量在每个大脑位置功能网络的特定和平均表达的程度，使用来自两性的数据。我们发现，共表示的识别模式由皮质区域锚定，这些区域沿着感觉-发散轴具有三种细胞构筑类型，包括在第一个末端，具有高 CoRS 的主要（同型）区域，在第二个末端，具有低 CoRS 和高 CoRI 的多模态区域，在第三个末端，具有低 CoRI 的边缘区域。重要的是，我们通过评估与髓鞘相关的神经解剖学和转录组学特征的关联，证明了髓鞘结构在塑造共表示的空间分布中的关键作用。此外，共表示的表现揭示了其对个体行为能力预测的重要性。我们的发现表明，功能网络之间的空间协调是基于解剖配置蓝图建立的，以促进神经信息处理，同时通过强调功能网络的组装，推进对大脑拓扑组织的理解。
