Cell Biological Limitations Constrain Dendritic Branching Morphology and Neuronal Function

描述（由申请人提供）：我将解决的一般问题是神经元如何整合其输入并计算其输出。整合和计算的核心是神经元的形态，特别是它们高度分支的树突状乔木的形态，这些树突状乔木接收来自其他神经元的突触输入或来自外部世界的感觉输入。轴突和树突过程之间的连接定义了神经系统的结构，这被视为理解神经功能的先决条件;连接组学，神经元连接的全球研究，已成为神经科学的主要目标。 在这个先驱者的提议中，我想对神经元形态学采取一种正交的方法。我的假设是，神经元的细胞生物学--物质的运输和周转--对树突的建立和维持都有很强的限制。此外，我建议，这些约束是如此强大，他们实际上损害了神经元的功能：我假设，例如，在直径的变化，树突状进程跨越分支路口是由运输约束，他们实际上降低了信号传播。如果这是真的，那么形态学是细胞生物学和神经元功能之间的妥协，确定权衡的性质可能会提供对连接性的关键见解。我将揭示的形态学规则将为确定连接图提供强有力的先验，并可能有助于解决连接组学中的一个主要问题：为了理解功能，连接图需要有多好？ 为了验证这一假设，需要一个可以精确测量形态的系统（并且在大多数情况下， 一般意义上的，包括蛋白质定位），其中它可以以受控的方式被操纵，并且其中 形态可以与功能相关联。果蝇幼虫的IV类树枝状机械感受器 符合这些要求，并将成为研究的最初重点。实验目标是：（1）利用光和电子 用显微镜来发现一整套分支规则，即直径、角度、分支长度和蛋白质是如何形成的。 细胞器分布随分支点而变化。和：（ii）使用钙和电压记录，连同行为， 来描述神经元的功能。测量将在野生型果蝇和突变体中进行，其中 已经使用精确的遗传操作修改了形态。理论目标是确定 观察到的解剖和功能特征优化了运输和发育限制， 另一方面是信号处理的限制。理论将与实验密切配合进行 在同一个实验室进行。 这些相互冲突的成本和收益之间的权衡的性质将提供巨大的洞察力， 神经元结构本研究通过精确的实验测量和理论建模相结合， 将不可估量地增加我们对神经系统中形式和功能之间关系的理解。我们希望 这些原则将被发现广泛适用于神经系统，并且这些原则将具有实用价值， 确定神经网络的结构。

DESCRIPTION (provided by applicant): The general problem that I will address is how neurons integrate their inputs and compute their outputs. Central to integration and computation is the morphology of neurons, and in particular that of their highly branched dendritic arbors, which receive synaptic input from other neurons or sensory input from the outside world. The connections between axonal and dendritic processes define the nervous system's structure, which is viewed as a prerequisite for understanding neural function; connectomics, the global study of neuronal connectivity, has emerged as a major goal of neuroscience. In this Pioneer proposal, I want to take an orthogonal approach to neuronal morphology. My hypothesis is that the cell biology of the neuron-the transport and turnover of materials-places very strong constraints on both building and maintaining dendrites. Furthermore, I propose that these constraints are so strong that they actually compromise the functioning of neurons: I hypothesize, for example, that the changes in diameters of dendritic processes across branch junctions are dictated by transport constraints and that they actually degrade signal propagation. If this is true, then morphology is a compromise between cell biology and neuronal function, and determining the nature of the tradeoff is likely to provide key insight into connectivity. The morphological rules that I will uncover will provide powerful a prioris for determining connectivit maps, and may help to solve a major problem in connectomics: how well does the connectivity map need to be in order to understand the function? To test this hypothesis, one needs a system in which morphology can be measured precisely (and in the most general sense, which includes protein localization), where it can be manipulated in a controlled way, and where morphology can be correlated with function. The Class IV dendritic arborization mechanoreceptor of Drosophila larvae meets these requirements, and will be the initial focus of study. The experimental goals are: (i) to use light and electron microscopy to discover the full set of branching rules—that is, how diameters, angles, branch lengths, and protein & organelle distributions change over branch points. And: (ii) to use calcium and voltage recordings, together with behavior, to characterize the function of the neuron. The measurements will be done in wild-type flies and in mutants, in which the morphology has been modified using precise genetic manipulations. The theoretical goal is to determine the extent to which the observed anatomical and functional characteristics optimize transport and developmental constraints on the one hand, and signal processing constraints on the other hand. The theory will be done in close coordination with experiments performed in the same laboratory. The nature of the tradeoff between these conflicting costs and benefits will provide tremendous insight into neuronal architecture. This research, via the combination of precise experimental measurement and theoretical modeling, will add inestimably to our understanding of the relationship between form and function in the nervous system. We hope that principles will be found that apply broadly across nervous systems and that the principles will have practical value in the determination of the structure of neural networks.