Emergence of Functional Network Dynamics from Single Cell Properties

项目摘要/摘要 大脑中神经元网络的集体动力驱动其主要的整体功能--控制 有机体的行为。破坏这种协调活动的神经系统的病理会导致 运动输出和粗暴行为的失调模式。然而，尚不清楚这些模式是如何 协调活动源于单个神经元及其连接的特性。在未来的五年里 我们寻求开发一个严谨的理论和生物现实的模型来协调出现 在一个完整的神经元网络中的动力学，类似于目前对如何 相互作用的分子物种的动力学在单细胞细菌中产生目标导向的运动行为。我们 关注线虫相对简单的神经系统；它恰好有302个神经元，是一种天然的 是这类基础神经动力学研究的选择。为了解决这个问题，我们实验室的研究 利用实验和计算方法的融合，包括先进的显微镜、基因组学 工程学、基于机器学习的图像处理、量化行为和动力系统 分析。我们已经开发了新的方法来定量探测和表征信号 单个神经元的加工特性以及记录和量化整个线虫的活动 在遗传扰动下使用体积钙成像的单细胞分辨率的神经系统。我们 现在正在探索细胞信号的微观特性与 集体网络动力的宏观作用。构图的机械模型和 维持结构化的、受控的大脑动力学将为理解如何 严重的神经疾病状态是由细胞和分子功能障碍引起的。

Project Summary/Abstract The collective dynamics of the network of neurons in the brain drive its primary holistic function — control of organismal behavior. Pathologies of the nervous system that disrupt this coordinated activity result in dysfunctional patterns of motor output and gross behavior. However, it is unknown how patterns of coordinated activity arise from the properties of single neurons and their connections. In the next five years we seek to develop a rigorous theory and biologically realistic model of the emergence of coordinated dynamics in a complete network of neurons, similar to the current level of understanding of how the dynamics of interacting molecular species produce goal-directed motile behavior in single-cell bacteria. We focus on the relatively simple nervous system of C. elegans; with precisely 302 neurons, it is a natural choice for such fundamental neurodynamical studies. To attack this problem, the research in our lab utilizes a fusion of experimental and computational approaches including advanced microscopy, genomic engineering, machine learning based image processing, quantitative behavior, and dynamical systems analysis. We have developed novel approaches to quantitatively probe and characterize the signal processing properties of single neurons as well as record and quantify the activity of the entire C. elegans nervous system at single-cell resolution using volumetric calcium imaging under genetic perturbation. We are now exploring the relationship between the microscopic properties of cellular signaling and the macroscopic function of collective network dynamics. A mechanistic model of the composition and maintenance of structured, controlled brain dynamics would provide a framework for understanding how gross neurological disease states arise from cellular and molecular dysfunction.