Automated reconstruction of three-dimensional neuronal morphology from laser scanning microscopy images
Automated reconstruction of three-dimensional neuronal morphology from laser scanning microscopy images
复制标题
DOI：
10.1016/s1046-2023(03)00011-2
复制
发表时间：
2003-05-01
期刊：
影响因子：
4.8
通讯作者：
Wearne, SL
中科院分区：
文献类型：
--
作者：
Rodriguez, A;Ehlenberger, D;Wearne, SL
实验和理论研究表明，无论是全球树突分支拓扑结构和细棘的几何形状是神经元功能，其可塑性和病理的关键决定因素。重要的是，模拟研究表明，局部和全局形态特性之间的相互作用是决定树突信息处理和诱导突触特异性可塑性的关键。因此，在高分辨率下重建和量化树突过程的能力是理解神经元功能的结构决定因素的必要前提。现有的3D神经元结构数字化方法使用交互式手动计算机从2D显微镜图像跟踪。该方法耗时长、主观性强、精度低。特别是，这些系统无法捕获树突静脉曲张、连续树突锥度和棘形态的精细细节。我们描述了一种技术，用于自动重建的三维神经元形态从多个堆栈的平铺共聚焦和多光子激光扫描显微镜（CLSM和MPLSM）图像。该系统能够代表全球和局部的结构变化，包括总树突分支拓扑结构，树突静脉曲张，精细的脊柱形态，具有足够的分辨率，准确的三维形态分析和现实的生物物理室建模。我们的系统提供了一个非常需要的工具，自动数字化和重建的3D神经元形态，可靠地捕捉细节的空间尺度跨越几个数量级，避免了主观错误，在手动跟踪与现有的数字化系统，并运行在一个标准的桌面工作站。(C)2003 Elsevier Science（美国）。All rights reserved.
Experimental and theoretical studies demonstrate that both global dendritic branching topology and fine spine geometry are crucial determinants of neuronal function, its plasticity and pathology. Importantly, simulation studies indicate that the interaction between local and global morphologic properties is pivotal in determining dendritic information processing and the induction of synapse-specific plasticity. The ability to reconstruct and quantify dendritic processes at high resolution is therefore an essential prerequisite to understanding the structural determinants of neuronal function. Existing methods of digitizing 3D neuronal structure use interactive manual computer tracing from 2D microscopy images. This method is time-consuming, subjective and lacks precision. In particular, fine details of dendritic varicosities, continuous dendritic taper, and spine morphology cannot be captured by these systems. We describe a technique for automated reconstruction of 3D neuronal morphology from multiple stacks of tiled confocal and multiphoton laser scanning microscopy (CLSM and MPLSM) images. The system is capable of representing both global and local structural variations, including gross dendritic branching topology, dendritic varicosities, and fine spine morphology with sufficient resolution for accurate 3D morphometric analyses and realistic biophysical compartment modeling. Our system provides a much needed tool for automated digitization and reconstruction of 3D neuronal morphology that reliably captures detail on spatial scales spanning several orders of magnitude, that avoids the subjective errors that arise during manual tracing with existing digitization systems, and that runs on a standard desktop workstation. (C) 2003 Elsevier Science (USA). All rights reserved.