Neurons perform computations by integrating inputs from thousands of synapses-mostly in the dendritic tree-to drive action potential firing in the axon. One fruitful approach to studying this process is to record from neurons using patch-clamp electrodes, fill the recorded neurons with a substance that allows subsequent staining, reconstruct the three-dimensional architectures of the dendrites, and use the resulting functional and structural data to develop computer models of dendritic integration. Accurately producing quantitative reconstructions of dendrites is typically a tedious process taking many hours of manual inspection and measurement. Here we present ShuTu, a new software package that facilitates accurate and efficient reconstruction of dendrites imaged using bright-field microscopy. The program operates in two steps: (1) automated identification of dendritic processes, and (2) manual correction of errors in the automated reconstruction. This approach allows neurons with complex dendritic morphologies to be reconstructed rapidly and efficiently, thus facilitating the use of computer models to study dendritic structure-function relationships and the computations performed by single neurons.

中文翻译：

---

ShuTu：用于高效、准确重建树突形态的开源软件。

神经元通过整合来自数千个突触（主要在树突树中）的输入来执行计算，以驱动轴突中的动作电位放电。研究这一过程的一种富有成效的方法是使用膜片钳电极记录神经元，用允许随后染色的物质填充记录的神经元，重建树突的三维结构，并使用所得的功能和结构数据来开发树突整合的计算机模型。准确地生成树突的定量重建通常是一个繁琐的过程，需要花费大量时间进行手动检查和测量。在这里，我们推出了 ShuTu，这是一种新软件包，有助于准确有效地重建使用明场显微镜成像的树突。该程序分两步运行：（1）自动识别树突过程，（2）手动纠正自动重建中的错误。这种方法允许快速有效地重建具有复杂树突形态的神经元，从而促进使用计算机模型来研究树突结构-功能关系以及单个神经元执行的计算。