The assembly of population coding networks

群体编码网络的组装

• 批准号: 10668566
• 负责人: BING YE
• 金额: $ 39.45万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2028-02-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10668566
• 关键词: Abdomen; Animals; Anterior; Brain; Candidate Disease Gene; Cells; Code; Cues; Development; Drosophila genus; Ensure; Exhibits; Genes; Genetic; Heterogeneity; Homeobox Genes; Image; Individual; Invertebrates; Knowledge; Larva; Location; Mental disorders; Mission; Modeling; Molecular; Motor; Nervous System; Neurons; Nociception; Nociceptors; Pathway interactions; Pattern; Perception; Physiological; Population; Property; Proteins; Public Health; Reporting; Research; Role; Specific qualifier value; Stimulus; Synapses; System; Techniques; Testing; United States National Institutes of Health; Vertebrates; Visual; experimental study; improved; innovation; insight; interdisciplinary approach; nervous system disorder; neural network; neuronal cell body; neuronal excitability; novel; novel strategies; overexpression; patch clamp; postmitotic; recruit; response; sensory stimulus; study population; tool; transcriptomics; vector

PROJECT SUMMARY Population coding is a fundamental strategy that the nervous system employs to represent sensory stimulus and generate perception. In neural networks that perform population coding (termed “population coding networks (PCNs)”), input-elicited responses are quantitatively heterogeneous across neurons and the response of a single neuron does not sufficiently define the stimulus; instead, the computed response of the entire population of neurons underlies the perception of the stimulus. Despite the importance of PCNs, very little is known about how they are assembled during development. The objective of the proposed research is to identify the mechanisms that establish a PCN during development. In many PCNs, the constituent neurons are not distinguishable from each other, except by their heterogeneous physiological properties. While the apparent homogeneity of these PCNs ensures that constituent neurons contribute to the same brain function, it also poses a challenge for studying the molecular and cellular mechanisms that underlie the assembly of PCNs. A recent study reported a neural network that encodes the intensity of noxious inputs through population coding in Drosophila larvae, which offers an excellent system for studying PCN assembly. Preliminary results suggest that Hox genes are involved in establishing this PCN. The central hypothesis is that a post-mitotic Hox code specifies the synaptic inputs to different neurons along the A-P axis, establishing a population-coding network that encodes stimulus intensity. This hypothesis will be tested by identifying the cellular (Aim 1) and molecular (Aim 2) mechanisms that establish the heterogeneity of the neurons in this PCN. The proposed research is innovative because it proposes novel cellular and molecular mechanisms that generate quantitative heterogeneity in a neural network. Moreover, it will use a newly developed technique that is ideally suited for studying neuronal population activity in the PCN. Novel genetic tools have also been developed for accessing subpopulation of neurons in the PCN. This research is significant because it will provide cellular, molecular, and conceptual insights into the establishment of other PCNs in Drosophila and other species. Beyond the PCNs, it will inform how physiological heterogeneity arises in a seemingly identical group of neurons. Furthermore, the successful completion of the proposed study will also demonstrate a Hox-based matching system that establish neuronal connections confined to specific rostrocaudal segments.

项目概要 群体编码是神经系统用来表示感觉刺激的基本策略 在执行群体编码（称为“群体编码”）的神经网络中。 网络（PCN）”），输入引发的反应在神经元和神经元之间存在数量上的异质性 单个神经元的响应不足以定义刺激；相反，计算出的响应 尽管 PCN 很重要，但整个神经元群都是刺激感知的基础。 人们对它们在开发过程中如何组装知之甚少。 是确定在开发过程中建立 PCN 的机制，在许多 PCN 中，其组成部分。 除了不同的生理特性之外，神经元彼此之间没有区别。 虽然这些 PCN 的明显同质性确保了组成神经元对相同的贡献 脑功能，它也对研究其背后的分子和细胞机制提出了挑战 最近的一项研究报道了一种编码有害强度的神经网络。 通过果蝇幼虫群体编码输入，这为研究 PCN 提供了一个优秀的系统 初步结果表明 Hox 基因参与了该 PCN 的建立。 假设是有丝分裂后 Hox 代码指定沿 A-P 的不同神经元的突触输入 轴，建立一个编码刺激强度的群体编码网络。 通过识别建立异质性的细胞（目标 1）和分子（目标 2）机制进行测试 所提出的研究具有创新性，因为它提出了新的细胞和 此外，它将使用在神经网络中产生定量异质性的分子机制。 新开发的技术非常适合研究 PCN 中的神经元群活动。 这项研究还开发了用于获取 PCN 神经元亚群的遗传工具。 意义重大，因为它将提供细胞、分子和概念上的见解来建立 果蝇和其他物种中的其他 PCN 除了 PCN 之外，它还将告知其生理情况。 此外，看似相同的神经元组也存在异质性。 拟议的研究还将展示基于 Hox 的匹配系统，该系统建立神经网络 连接仅限于特定的轴尾段。