Automated Neuron Reconstruction from Multiphoton Images

描述（由申请人提供）：与年龄相关的认知障碍，影响全世界绝大多数老年人，伴随着树突树突几何形状的细微变化，以及树突棘密度和分布的减少。要准确理解这些结构变化是如何产生所观察到的认知缺陷的，需要精确的神经元形态的3D表示，以及可以将结构变化与改变的神经元放电模式联系起来的生物物理模型。最近的实验工作表明，这些整体（树突拓扑）和局部（脊柱几何）变化的综合效应严重影响神经元的动态行为和突触特异性可塑性的程度。然而，到目前为止，还没有能够在全球和局部尺度上解析和模拟神经元形态和动力学的工具。这个应用程序直接解决了这两个需求。现有的获取神经元形态用于定量分析或室建模的方法在分辨率上是有限的，或者是非常耗时的。该项目的中心目标是开发一个自动化的软件系统，用于数字化，3D重建和基于生物物理的详细神经元形态模拟，该系统可以可靠地捕获跨越几个数量级的空间尺度上的细节，并避免在手动跟踪过程中出现的主观错误。该系统将用于获得结构变化在与年龄相关的工作记忆和认知衰退中的作用的机制理解。两个具体目标将解决这个广泛的目标：1)为我们的原型体积集成系统开发一个自动化的用户界面，并扩展原型来处理包含整个第三层锥体神经元的多光子图像堆栈；2)开发用于共聚焦和多光子图像数据自动参数提取的软件工具，适用于标准隔室建模软件包的仿真。通过确定突触传递、神经整合和动作电位正向和反向传播的简单形态学指标，本研究开发的工具将深入了解正常认知功能基础上记忆诱导和维持的基本机制。这样的见解将导致加强的策略，以延缓和改善学习，记忆和认知能力的损害，伴随着正常的衰老和年龄相关的病理。

DESCRIPTION (provided by applicant): Age-related cognitive impairment, which affects the vast majority of elderly people worldwide, is accompanied by subtle changes in the geometry of dendritic arborizations, and reduced densities and distributions of dendritic spines. Understanding exactly how these structural changes might produce the observed cognitive deficits requires accurate 3D representations of neuronal morphology, and biophysical modeling that can relate structural changes to altered neuronal firing patterns. Recent experimental work indicates that the combined effects of these global (dendritic topology) and local (spine geometry) variations critically affect neuronal dynamic behavior and the extent of synapse-specific plasticity. To date however, no tools capable of resolving and simulating neuronal morphology and dynamics on both global and local scales have been available. This application directly addresses both of these needs. Existing methods of acquiring neuronal morphology for quantitative analysis or compartment modeling are limited in resolution, or are prohibitively time-consuming. The central goal of this project is to develop an automated software system for digitization, 3D reconstruction and biophysically-based simulation of detailed neuronal morphology, that reliably captures detail on spatial scales spanning several orders of magnitude and that avoids the subjective errors that arise during manual tracing. This system will be used to obtain a mechanistic understanding of the role of structural changes in age-related decrements in working memory and cognition. Two specific aims will address this broad objective: 1) To develop an automated user interface for our prototype volume integration system and to extend the prototype to handle multiphoton image stacks that contain entire layer III pyramidal neurons; 2) To develop software tools for automatic parameter extraction from confocal and multiphoton imaged data, suitable for simulation with standard compartment modeling packages. By determining simple morphologic indices for altered efficacy of synaptic transmission, neural integration and action potential forward and backpropagation, the tools developed in this study will provide insight into fundamental mechanisms of memory induction and maintenance that underlie normal cognitive function. Such insight will lead to enhanced strategies for delaying and ameliorating the impairment of learning, memory and cognitive performance that accompanies normal aging and age-related pathologies.