Synapse Elimination during Development: Pruning Rates, Models, and Diseases

描述(申请人提供)：许多神经回路是通过两个阶段的发育过程形成的，其中包括最初旺盛的突触形成阶段，随后是较长时间的依赖活动的突触消除阶段。虽然修剪在许多生物体和大脑区域都有很好的记录，但很少有人注意到突触在发育过程中被消除的速度。不同的修剪率对所产生的神经回路的质量和可塑性有很大的影响，事实上，许多神经疾病都与关键发育时期皮质中突触水平的异常有关。我们假设大脑皮层的修剪率已经被优化，以实现潜在神经回路的连通性和健壮性。为了验证我们的假设，我们提出了一个联合实验-计算研究计划，以探索突触水平在发育过程中如何变化，以及这些变化如何在网络和表型水平上表现出来。首先，我们将使用一种专门的电子显微镜(EM)准备，选择性地对突触进行染色，以量化小鼠桶状皮质发育过程中突触消除的准确速度。我们将开发一条全自动化和高通量的图像处理管道，使我们能够在每个时间点计算数万个突触，并获得关于修剪率和突触密度峰值时间的可靠统计数据。其次，我们将开发突触修剪的计算模型，以评估修剪速度如何影响神经回路中的信息处理。我们的计算实验将探索稀疏电路是如何出现的，这些电路能够进行高效和健壮的编码，同时仍然具有足够的灵活性，可以进行可塑性和适应性，同时满足新陈代谢成本。我们的模型还将帮助我们回答有关全球神经电路的问题，包括中枢是否可能存在以及功能模块是如何形成的。第三，我们将研究在发育异常情况下突触重新连接和重组的案例。我们将使用脆性X综合征和Rett综合征的小鼠模型重复我们的EM过程，以比较突触与对照的水平，我们将扩展我们的计算模型，以了解这些条件下电路水平的差异。拟议的项目将产生新的计算和实验解决方案，用于分析网络发展，并将导致对局部修剪机制如何影响全局电路特性的生物学见解。

DESCRIPTION (provided by applicant): Many neural circuits are formed using a two-stage developmental process that includes an initial period of exuberant synapse formation, followed by a longer period of activity-dependent synapse elimination. While pruning has been well-documented in many organisms and brain regions, little attention has been paid to the rate at which synapses are eliminated during development. Different pruning rates have a strong effect on the quality and plasticity of the resulting neural circuits, and indeed, many neurological diseases have been linked to abnormal synapse levels in the cortex during critical developmental periods. We hypothesize that pruning rates in the cortex have been optimized to achieve both connectivity and robustness of underlying neural circuits. To test our hypothesis, we propose a joint experimental-computational research plan to explore how synapse levels change during development and how these changes manifest at the network and phenotypic levels. First, we will quantify the precise rate of synapse elimination during development of the mouse barrel cortex using a specialized electron microscopy (EM) preparation that selectively stains for synapses. We will develop a fully-automated and high-throughput image processing pipeline that will allow us to count tens of thousands of synapses per time point and gain robust statistics of pruning rates and the time of peak synapse density. Second, we will develop computational models of synaptic pruning to evaluate how pruning rates affect information processing in neural circuits. Our computational experiments will explore how sparse circuits emerge that are capable of efficient and robust encoding, while still being flexible enough for plasticity and adaptation and while meeting metabolic costs. Our models will also help us answer questions about global neural circuitry, including whether hubs are likely to exist and how functional modules are formed. Third, we will examine cases of synapse rewiring and reorganization following abnormal developmental conditions. We will repeat our EM procedure using mouse models of Fragile X syndrome and Rett syndrome to compare synapse levels with respect to control, and we will extend our computational models to understand circuit-level differences in these conditions. The proposed project will generate new computational and experimental solutions for analyzing network development and will lead to biological insights into how local pruning mechanisms affect global circuit properties.