Regulation of Dendritic Compartmentalization Features

树突区室化特征的调控

• 批准号: RGPIN-2015-05830
• 负责人: Béïque, JeanClaude
• 金额: $ 2.77万
• 依托单位: University of Ottawa
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=613775
• 关键词: Regulation; Dendritic; Compartmentalization; Features

The brain is made of billions of microscopic cells called neurons, which are interconnected in dense, complex networks. Neurons have large branches called dendrites that resemble the branches on a tree, which are studded with specialized connections called synapses, where neurons communicate with one another. Neurons sum-up synaptic inputs in real-time and, when enough synapses are activated, fire ‘spikes’ to transmit signals to their partners downstream. Since every single neuron may carry more than ten thousand synapses, the number of computations that a neuron potentially performs is staggering. Remarkable insights into these operations have been made in recent decades, together outlining fundamental mechanisms for information processing at single neurons. One key finding is that individual branches of a neuron’s dendritic tree can powerfully boost synaptic inputs and drive neuronal spiking, which enable neurons to be more efficient at information processing. In this way, neurons are thought to be divided into multiple functional ‘subunits’ or ‘compartments’, represented by individual branches of the dendritic tree. In recent years, our laboratory has applied cutting-edge laser scanning microscopy and electrophysiology to study in live neurons the maturation of synapses along these dendritic subunits during brain development. We have discovered a novel mode of calcium signaling that takes place at developing dendritic compartments, shedding light on how neural circuits are formed. In this research proposal, we aim to extend these findings to better understand how information processing is controlled at individual dendritic compartments. In our first Objective, we will characterize how developing dendrites respond to different patterns of synaptic input. These experiments are a natural extension of the work we have accomplished to date, and will provide a firm foundation for understanding how synaptic activity is processed during neural circuit formation. In the second and third Objectives, we will directly investigate how specific neuromodulators in the brain, specifically endocannabinoids and serotonin, affect the function of individual dendrites. Endocannabinoids are natural chemicals in the body that resemble the active drug in cannabis, and serotonin is classically involved in the regulation of mood, appetite and sexual behavior. Although these neurochemicals are well-known to alter neuron function, current understanding of these processes is rudimentary, and significantly lags behind modern models of neural computation. The experiments we propose will expand on recent discoveries about dendritic subunit function, and are therefore suited to push forward our understanding of neuromodulation in the brain. This research program will make use of sophisticated technologies and analyses to uncover the complex cellular mechanisms that underlie brain function.

大脑是由数十亿个被称为神经元的微小细胞组成的，这些细胞以密集而复杂的网络相互连接。神经元有被称为树突的大分支，类似于树上的树枝，树突上布满了被称为突触的特殊连接，神经元在突触上相互交流。神经元实时汇总突触输入，当足够多的突触被激活时，就会发出“尖峰”信号，将信号传递给下游的同伴。由于每个神经元可能携带超过一万个突触，因此一个神经元潜在执行的计算量是惊人的。近几十年来，人们对这些操作有了深刻的认识，共同概述了单个神经元信息处理的基本机制。一个关键的发现是，神经元树突树的单个分支可以有力地促进突触输入并驱动神经元尖峰，从而使神经元在信息处理方面更有效。通过这种方式，神经元被认为被分成多个功能的“亚单位”或“室”，由树突树的单个分支代表。近年来，我们的实验室应用尖端的激光扫描显微镜和电生理学来研究活神经元在大脑发育过程中沿这些树突亚基突触的成熟。我们发现了一种新的钙信号传导模式，它发生在树突隔室的发育过程中，从而揭示了神经回路是如何形成的。在这项研究计划中，我们的目标是扩展这些发现，以更好地理解信息处理是如何在单个树突隔室中控制的。在我们的第一个目标中，我们将描述发育中的树突如何对不同模式的突触输入作出反应。这些实验是我们迄今为止完成的工作的自然延伸，并将为理解神经回路形成过程中突触活动的处理方式提供坚实的基础。在第二个和第三个目标中，我们将直接研究大脑中的特定神经调节剂，特别是内源性大麻素和血清素，如何影响单个树突的功能。内源性大麻素是人体内的天然化学物质，类似于大麻中的活性药物，血清素通常参与调节情绪、食欲和性行为。尽管众所周知，这些神经化学物质可以改变神经元功能，但目前对这些过程的理解还很初级，而且明显落后于现代神经计算模型。我们提出的实验将扩展最近关于树突亚基功能的发现，因此适合推动我们对大脑神经调节的理解。这个研究项目将利用复杂的技术和分析来揭示大脑功能背后的复杂细胞机制。