Background

Fundamental to understanding neuronal network function is defining neuron morphology, location, properties, and synaptic connectivity in the nervous system. A significant challenge is to reconstruct individual neuron morphology and connections at a whole CNS scale and bring together functional and anatomical data to understand the whole network.

New Method

We used a PC controlled micropositioner to hold a fixed whole mount of Xenopus tadpole CNS and replace the stage on a standard microscope. This allowed direct recording in 3D coordinates of features and axon projections of one or two neurons dye-filled during whole-cell recording to study synaptic connections. Neuron reconstructions were normalised relative to the ventral longitudinal axis of the nervous system. Coordinate data were stored as simple text files.

Results

Reconstructions were at 1 μm resolution, capturing axon lengths in mm. The output files were converted to SWC format and visualised in 3D reconstruction software NeuRomantic. Coordinate data are tractable, allowing correction for histological artefacts. Through normalisation across multiple specimens we could infer features of network connectivity of mapped neurons of different types.

Comparison with Existing Methods

Unlike other methods using fluorescent markers and utilising large-scale imaging, our method allows direct acquisition of 3D data on neurons whose properties and synaptic connections have been studied using whole-cell recording.

Conclusions

This method can be used to reconstruct neuron 3D morphology and follow axon projections in the CNS. After normalisation to a common CNS framework, inferences on network connectivity at a whole nervous system scale contribute to network modelling to understand CNS function.

中文翻译：

---

一种简单的方法定义小 CNS 体积中填充神经元的 3D 形态和轴突投影：了解功能网络电路的步骤

背景

理解神经元网络功能的基础是定义神经系统中的神经元形态、位置、特性和突触连接。一个重大挑战是在整个 CNS 尺度上重建单个神经元形态和连接，并将功能和解剖数据结合起来以了解整个网络。

新方法

我们使用 PC 控制的微定位器来固定整个非洲爪蟾蝌蚪 CNS，并替换标准显微镜上的载物台。这允许在全细胞记录期间直接记录一两个神经元的特征和轴突投影的 3D 坐标，以研究突触连接。神经元重建相对于神经系统的腹侧纵轴进行归一化。坐标数据存储为简单的文本文件。

结果

重建分辨率为 1 μm，以 mm 为单位捕获轴突长度。输出文件被转换为 SWC 格式并在 3D 重建软件 NeuRomantic 中进行可视化。坐标数据易于处理，允许对组织学伪影进行校正。通过对多个样本的归一化，我们可以推断出不同类型映射神经元的网络连接特征。

与现有方法的比较

与使用荧光标记和利用大规模成像的其他方法不同，我们的方法允许直接获取神经元的 3D 数据，其特性和突触连接已使用全细胞记录进行了研究。

结论

该方法可用于重建神经元 3D 形态并跟踪 CNS 中的轴突投影。在标准化为通用 CNS 框架后，对整个神经系统规模的网络连通性的推断有助于网络建模以了解 CNS 功能。