Kurylas Angela E, Rohlfing Torsten, Krofczik Sabine, Jenett Arnim, Homberg Uwe
Fachbereich Biologie, Tierphysiologie, Philipps Universität Marburg, 35032, Marburg, Germany.
Cell Tissue Res. 2008 Jul;333(1):125-45. doi: 10.1007/s00441-008-0620-x. Epub 2008 May 27.
In order to understand the connectivity of neuronal networks, their constituent neurons should ideally be studied in a common framework. Since morphological data from physiologically characterized and stained neurons usually arise from different individual brains, this can only be performed in a virtual standardized brain that compensates for interindividual variability. The desert locust, Schistocerca gregaria, is an insect species used widely for the analysis of olfactory and visual signal processing, endocrine functions, and neural networks controlling motor output. To provide a common multi-user platform for neural circuit analysis in the brain of this species, we have generated a standardized three-dimensional brain of this locust. Serial confocal images from whole-mount locust brains were used to reconstruct 34 neuropil areas in ten brains. For standardization, we compared two different methods: an iterative shape-averaging (ISA) procedure by using affine transformations followed by iterative nonrigid registrations, and the Virtual Insect Brain (VIB) protocol by using global and local rigid transformations followed by local nonrigid transformations. Both methods generated a standard brain, but for different applications. Whereas the VIB technique was designed to visualize anatomical variability between the input brains, the purpose of the ISA method was the opposite, i.e., to remove this variability. A novel individually labeled neuron, connecting the lobula to the midbrain and deutocerebrum, has been registered into the ISA atlas and demonstrates its usefulness and accuracy for future analysis of neural networks. The locust standard brain is accessible at http://www.3d-insectbrain.com .
为了理解神经元网络的连通性，理想情况下应该在一个通用框架中研究其组成神经元。由于来自生理特征明确且经过染色的神经元的形态学数据通常来自不同的个体大脑，所以这只能在一个虚拟的标准化大脑中进行，该大脑可补偿个体间的变异性。沙漠蝗虫，即群居飞蝗，是一种广泛用于分析嗅觉和视觉信号处理、内分泌功能以及控制运动输出的神经网络的昆虫物种。为了为该物种大脑中的神经回路分析提供一个通用的多用户平台，我们生成了这种蝗虫的标准化三维大脑。利用蝗虫全脑的系列共聚焦图像重建了十个大脑中的34个神经纤维网区域。为了进行标准化，我们比较了两种不同的方法：一种是通过仿射变换然后进行迭代非刚性配准的迭代形状平均（ISA）程序，另一种是通过全局和局部刚性变换然后进行局部非刚性变换的虚拟昆虫大脑（VIB）协议。两种方法都生成了一个标准大脑，但适用于不同的应用。VIB技术旨在可视化输入大脑之间的解剖变异性，而ISA方法的目的则相反，即消除这种变异性。一个新的单独标记的神经元，连接小叶与中脑和后脑，已被注册到ISA图谱中，并证明了其对未来神经网络分析的有用性和准确性。蝗虫标准大脑可在http://www.3d-insectbrain.com上获取。
