Cell Biological Limitations Constrain Dendritic Branching Morphology and Neuronal Function

描述(申请人提供)：我将解决的一般问题是神经元如何整合它们的输入和计算它们的输出。整合和计算的中心是神经元的形态，特别是它们高度分枝的树枝的形态，它们接受来自其他神经元的突触输入或来自外部世界的感觉输入。轴突和树突之间的联系决定了神经系统的结构，这被视为理解神经功能的先决条件；连接学，即对神经元连接的全球研究，已经成为神经科学的主要目标。在这个先驱者的提案中，我想采用一种正交的方法来研究神经元形态。我的假设是，神经元的细胞生物学--材料的运输和周转--对构建和维护树突施加了非常强烈的限制。此外，我认为这些限制是如此强烈，以至于它们实际上损害了神经元的功能：我假设，例如，跨分支连接的树突直径的变化是由运输限制决定的，它们实际上降低了信号传播。如果这是真的，那么形态是细胞生物学和神经元功能之间的折衷，确定权衡的性质可能会提供对连接的关键洞察。我将揭示的形态规则将为确定连接图提供一个强大的先验，并可能有助于解决连接学中的一个主要问题：为了理解功能，连接图需要有多好？ 为了检验这一假设，人们需要一个能够精确测量形态的系统(并且最多 一般意义上，包括蛋白质定位)，在哪里可以以受控的方式操作，以及在哪里 形态可以与功能相关联。果蝇幼虫第IV类树突分枝机械感受器 符合这些要求，并将是最初的研究重点。实验目标是：(I)利用光和电子 显微镜来发现一整套的分支规则--即直径、角度、分支长度和蛋白质 细胞器的分布随分支点的变化而变化。和：(Ii)使用钙和电压记录，以及行为， 来描述神经元的功能。这些测量将在野生型苍蝇和突变体中进行，在这些突变体中， 形态已经通过精确的遗传操作得到了改变。理论上的目标是确定 其中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，又受到信号处理的制约。这一理论将与实验密切配合。 在同一个实验室里完成的。 这些相互冲突的成本和收益之间权衡的本质将为我们提供对 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， 将无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 将发现这些原则广泛适用于神经系统，并且这些原则将在 神经网络结构的确定。

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.