CRCNS: Functional Imaging and Computational Models of Place Field Integration in Pyramidal Cell Dendrites

神经科学中的一个基本问题是了解网络中不同的神经元集合如何组合或整合它们的各种输入，以及输入的模式和结果的输出如何与行为相关。新的、甚至是史无前例的实验方法已经并正在开发，用来从大量分布的神经元中成像或记录，但理解积分步骤可能很困难，因为输入和输出通常分布在许多毫米上，而且很难同时从两者记录，特别是在行为正常的动物中。这个项目将结合实验和计算方法来阐明与哺乳动物空间导航相关的锥体神经元中的这种突触整合。从清醒行为小鼠身上获得的成像数据将提供给其他小组，完整的结果将作为其他与神经元网络中输入整合相关的研究的模型。计算模型将在ModelDB数据库上提供，并将成为其他致力于了解该大脑区域功能的其他方面的资源。此外，这项工作将涉及实验和计算研究小组之间的密切合作，从而为博士后研究员和研究生提供跨学科的研究培训。在海马体的锥体神经元中，大型树突树构成一个复杂的分支过程网络，涉及数万个包含各种电压门控离子通道的兴奋性突触。目前尚不清楚突触输入撞击树突的模式，以及这些输入在多大程度上被树突处理以驱动行为过程中的地点野放电(即与空间位置相关的放电)。该项目的目标首先是1)建立受当前成像数据约束的树突状细胞定位细胞激发的改进计算模型，2)建立新的实验技术，以单脊椎分辨率成像树突树中锥体细胞的输入，在定位野激发过程中。这些实验和模型将一起被用来确定局部树突处理在多大程度上参与了定位细胞的激发。拟议的实验将允许构建显着改进的海马体功能模型，这些模型将提供一个框架，在其中了解树突树局部水平记录的活动，并组装整个树枝上树突处理的综合图景。

A fundamental question in neuroscience is to understand how different sets of neurons in a network combine or integrate their various inputs, and how both the pattern of inputs and the resulting outputs are related to behavior. Novel, even unprecedented, experimental methods have been and are being developed with which to image or record from large numbers of distributed neurons but understanding the integration step can be difficult since inputs and outputs are generally distributed over many millimeters, and it is very difficult to record from both simultaneously, especially so in a behaving animal. This project will combine experimental and computational methods to elucidate such synaptic integration in pyramidal neurons associated with mammalian spatial navigation in awake, behaving animals. The imaging data acquired from awake behaving mice will be made available to other groups and the full results will serve as a model for other research concerned with the integration of inputs in networks of neurons. The computational models will be made available on the ModelDB database and will be a resource to others working to understand other aspects of functionality in this brain region. Furthermore, the work will involve a close collaboration between experimental and computational research groups, thus giving postdoctoral fellows and graduate students cross-disciplinary research training.In pyramidal neurons of the hippocampus, the large dendritic tree constitutes an elaborate network of branching processes involving tens of thousands of excitatory synapses containing a variety of voltage-gated ion channels. The pattern of synaptic inputs impinging upon the dendritic arbor and the degree to which these inputs are processed by it to drive place field firing (i.e., firing correlated with spatial location) during behavior are currently unknown. The goals of the project are first to 1) develop improved computational models of dendritic place cell firing constrained by current imaging data and 2) establish new experimental techniques to image the inputs to pyramidal cells in the dendritic tree, at single spine resolution, during place field firing. Together the experiments and models will be used to 3) determine the degree to which local dendritic processing is involved in place cell firing. The proposed experiments will allow for the construction of significantly improved models of hippocampal function and the models will provide a framework within which to understand activity recorded at a local level in the dendritic tree and assemble a comprehensive picture of dendritic processing across the whole arbor.