Motivation Given that neuronal morphology can widely vary among cell classes, brain regions, and animal species, accurate quantitative descriptions allowing classification of large sets of neurons is essential for their structural and functional characterization. However, robust and unbiased computational methods currently used to characterize groups of neurons are scarce.

中文翻译：

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用于神经元聚类和分类的拓扑 Sholl 描述符

动机鉴于神经元形态在细胞类别、大脑区域和动物物种之间可能存在很大差异，因此允许对大量神经元进行分类的准确定量描述对于它们的结构和功能表征至关重要。然而，目前用于表征神经元组的稳健且无偏的计算方法很少。