Neurons have diverse molecular, morphological, connectional and functional properties. We believe that the only realistic way to manage this complexity — and thereby pave the way for understanding the structure, function and development of brain circuits — is to group neurons into types, which can then be analysed systematically and reproducibly. However, neuronal classification has been challenging both technically and conceptually. New high-throughput methods have created opportunities to address the technical challenges associated with neuronal classification by collecting comprehensive information about individual cells. Nonetheless, conceptual difficulties persist. Borrowing from the field of species taxonomy, we propose principles to be followed in the cell-type classification effort, including the incorporation of multiple, quantitative features as criteria, the use of discontinuous variation to define types and the creation of a hierarchical system to represent relationships between cells. We review the progress of classifying cell types in the retina and cerebral cortex and propose a staged approach for moving forward with a systematic cell-type classification in the nervous system.

中文翻译：

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神经元细胞类型分类：挑战，机遇和前进道路

神经元具有多种分子，形态，连接和功能特性。我们认为，管理这种复杂性的唯一现实方法（从而为理解脑回路的结构，功能和发育铺平道路）是将神经元分组为类型，然后可以对其进行系统性和可重复性的分析。但是，神经元分类在技术和概念上都具有挑战性。通过收集有关单个细胞的全面信息，新的高通量方法为解决与神经元分类相关的技术挑战创造了机会。尽管如此，概念上的困难仍然存在。借鉴物种分类学的领域，我们提出了在细胞类型分类工作中应遵循的原则，包括将多个，定量特征作为标准，使用不连续变化来定义类型，并创建一个层次系统来表示单元之间的关系。我们回顾了在视网膜和大脑皮层中对细胞类型进行分类的进展，并提出了在神经系统中进行系统性细胞类型分类的分阶段方法。