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脑微血管具有共同的拓扑结构,局部几何形状存在差异,与代谢负荷相匹配。

Brain microvasculature has a common topology with local differences in geometry that match metabolic load.

机构信息

Department of Physics, University of California, San Diego, La Jolla, CA 92093, USA.

Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA 20147, USA.

出版信息

Neuron. 2021 Apr 7;109(7):1168-1187.e13. doi: 10.1016/j.neuron.2021.02.006. Epub 2021 Mar 2.

Abstract

The microvasculature underlies the supply networks that support neuronal activity within heterogeneous brain regions. What are common versus heterogeneous aspects of the connectivity, density, and orientation of capillary networks? To address this, we imaged, reconstructed, and analyzed the microvasculature connectome in whole adult mice brains with sub-micrometer resolution. Graph analysis revealed common network topology across the brain that leads to a shared structural robustness against the rarefaction of vessels. Geometrical analysis, based on anatomically accurate reconstructions, uncovered a scaling law that links length density, i.e., the length of vessel per volume, with tissue-to-vessel distances. We then derive a formula that connects regional differences in metabolism to differences in length density and, further, predicts a common value of maximum tissue oxygen tension across the brain. Last, the orientation of capillaries is weakly anisotropic with the exception of a few strongly anisotropic regions; this variation can impact the interpretation of fMRI data.

摘要

微血管是支持异质脑区神经元活动的供应网络的基础。毛细血管网络的连通性、密度和方向有哪些共同和不同的方面?为了解决这个问题,我们以亚微米分辨率对整个成年小鼠大脑的微血管连接组进行了成像、重建和分析。图分析显示,整个大脑具有共同的网络拓扑结构,从而导致血管稀疏时具有共同的结构鲁棒性。基于解剖学精确重建的几何分析揭示了一种标度律,将长度密度(即单位体积内的血管长度)与组织到血管的距离联系起来。然后,我们推导出一个公式,将区域代谢差异与长度密度差异联系起来,并进一步预测整个大脑中最大组织氧张力的共同值。最后,毛细血管的方向具有各向同性,除了少数几个具有各向异性的区域;这种变化会影响 fMRI 数据的解释。

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