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一组中枢神经元和非局部连接特征支持秀丽隐杆线虫的大脑全局动力学。

A set of hub neurons and non-local connectivity features support global brain dynamics in C. elegans.

机构信息

Department of Neuroscience and Developmental Biology, Vienna BioCenter (VBC), University of Vienna, Djerassiplatz 1, 1030 Vienna, Austria; Vienna BioCenter (VBC) PhD Program, Doctoral School of the University of Vienna and Medical University of Vienna, 1030 Vienna, Austria.

Department of Neurology, Weill Institute for Neurosciences, Kavli Institute for Fundamental Neuroscience and Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, CA, USA.

出版信息

Curr Biol. 2022 Aug 22;32(16):3443-3459.e8. doi: 10.1016/j.cub.2022.06.039. Epub 2022 Jul 8.

Abstract

The wiring architecture of neuronal networks is assumed to be a strong determinant of their dynamical computations. An ongoing effort in neuroscience is therefore to generate comprehensive synapse-resolution connectomes alongside brain-wide activity maps. However, the structure-function relationship, i.e., how the anatomical connectome and neuronal dynamics relate to each other on a global scale, remains unsolved. Systematically, comparing graph features in the C. elegans connectome with correlations in nervous system-wide neuronal dynamics, we found that few local connectivity motifs and mostly other non-local features such as triplet motifs and input similarities can predict functional relationships between neurons. Surprisingly, quantities such as connection strength and amount of common inputs do not improve these predictions, suggesting that the network's topology is sufficient. We demonstrate that hub neurons in the connectome are key to these relevant graph features. Consistently, inhibition of multiple hub neurons specifically disrupts brain-wide correlations. Thus, we propose that a set of hub neurons and non-local connectivity features provide an anatomical substrate for global brain dynamics.

摘要

神经元网络的布线结构被认为是其动力学计算的一个重要决定因素。因此,神经科学领域正在努力生成全面的突触分辨率连接组图谱,以及全脑活动图谱。然而,结构-功能关系,即解剖连接组和神经元动力学如何在全局范围内相互关联,仍未得到解决。我们系统地比较了秀丽隐杆线虫连接组中的图特征与神经系统全范围神经元动力学之间的相关性,发现很少有局部连接模式,而大多数其他非局部特征,如三聚体模式和输入相似性,可以预测神经元之间的功能关系。令人惊讶的是,连接强度和共同输入的数量并不能改善这些预测,这表明网络的拓扑结构是足够的。我们证明了连接组中的中枢神经元是这些相关图特征的关键。一致地,抑制多个中枢神经元特异性地破坏了全脑相关性。因此,我们提出一组中枢神经元和非局部连接特征为全局大脑动力学提供了一个解剖学基础。

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