Liu Lijuan, Yun Zhixi, Manubens-Gil Linus, Chen Hanbo, Xiong Feng, Dong Hongwei, Zeng Hongkui, Hawrylycz Michael, Ascoli Giorgio A, Peng Hanchuan
SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu, China.
Tencent AI Lab, Bellevue, WA, USA.
Res Sq. 2023 Jun 14:rs.3.rs-2960606. doi: 10.21203/rs.3.rs-2960606/v1.
Classifications of single neurons at brain-wide scale is a powerful way to characterize the structural and functional organization of a brain. We acquired and standardized a large morphology database of 20,158 mouse neurons, and generated a whole-brain scale potential connectivity map of single neurons based on their dendritic and axonal arbors. With such an anatomy-morphology-connectivity mapping, we defined neuron connectivity types and subtypes (both called "c-types" for simplicity) for neurons in 31 brain regions. We found that neuronal subtypes defined by connectivity in the same regions may share statistically higher correlation in their dendritic and axonal features than neurons having contrary connectivity patterns. Subtypes defined by connectivity show distinct separation with each other, which cannot be recapitulated by morphology features, population projections, transcriptomic, and electrophysiological data produced to date. Within this paradigm, we were able to characterize the diversity in secondary motor cortical neurons, and subtype connectivity patterns in thalamocortical pathways. Our finding underscores the importance of connectivity in characterizing the modularity of brain anatomy, as well as the cell types and their subtypes. These results highlight that c-types supplement conventionally recognized transcriptional cell types (t-types), electrophysiological cell types (e-types), and morphological cell types (m-types) as an important determinant of cell classes and their identities.
在全脑尺度上对单个神经元进行分类是表征大脑结构和功能组织的一种有效方法。我们获取并标准化了一个包含20158个小鼠神经元的大型形态学数据库，并基于它们的树突和轴突分支生成了单个神经元的全脑尺度潜在连接图谱。通过这种解剖 - 形态学 - 连接性映射，我们为31个脑区的神经元定义了神经元连接类型和亚型（为简单起见，均称为“c型”）。我们发现，由相同区域内的连接性定义的神经元亚型在其树突和轴突特征上可能比具有相反连接模式的神经元在统计学上具有更高的相关性。由连接性定义的亚型彼此之间表现出明显的分离，这是迄今为止所产生的形态学特征、群体投射、转录组学和电生理数据所无法概括的。在这个范式中，我们能够表征次级运动皮层神经元的多样性以及丘脑皮质通路中的亚型连接模式。我们的发现强调了连接性在表征脑解剖结构模块化以及细胞类型及其亚型方面的重要性。这些结果突出表明，c型作为细胞类别及其身份的重要决定因素，补充了传统上认可的转录细胞类型（t型）、电生理细胞类型（e型）和形态学细胞类型（m型）。
