A systems approach to long-term in vivo homeostatic control of neural activity

神经活动长期体内稳态控制的系统方法

• 批准号: BB/I022147/1
• 负责人: Matthew Nolan
• 金额: $ 82.04万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FI022147%2F1
• 关键词: systems; approach; long; term; vivo

Throughout life the brain is faced with the challenge of maintaining its stability, while also being sufficiently flexible to respond to environmental changes and to make modifications required for storage of memories. The process of maintaining brain functions near some set point in the face of these challenges is called homeostasis. Homeostasis regulates the electrical activity of neurons and is likely to be exceptionally important for life-long health and for healthy aging. It is required to maintain a neuron's activity within an optimal range. If neurons have too much or too little activity, neurons will be damaged or information will be lost. Deficits in homeostasis are believed to play critical roles in a spectrum of brain disorders that are targets for pharmaceutical and biotechnology industries. Yet, we know very little about the basic cellular or molecular mechanisms that stabilize neural activity in the adult brain. We propose a new approach to establish fundamental cellular and molecular mechanisms that mediate homeostasis in the adult brain. Our approach uses molecular tools that we have recently developed to specifically manipulate activity of identified populations of neurons in the brains of adult mice. With these tools we can either increase or reduce neuronal activity and then directly measure homeostatic responses that return key neuronal functions to previous set points. We will focus on a brain area called the dentate gyrus (DG), which is important for spatial memory and is implicated in age-related memory loss. This is a good model as it has well defined anatomical and physiological properties. Our preliminary data demonstrate that neurons in the dentate gyrus homeostatically adapt to manipulations that cause their activity to be increased or reduced. We now propose to use this new approach to to identify molecules that are important for homeostasis in the adult brain and to understand the underlying mechanisms. We will use our new molecular tools to induce homeostatic responses in neurons in the DG of adult mice. We will then use electrophysiological recordings to measure the functional changes that have occurred to return neural activity to its previous set point. These experiments will determine if neurons compensate homeostatically for changes in their activity levels by altering their communication with each other or by changing the way they process incoming information. We will develop computational models to reconcile data from different experiments and to make testable predictions for further experiments. Using gene expression profiling technology we will identify which genes have become more or less active during the homeostatic response. We will then examine how these genes contribute to the cellular changes that are associated with homeostasis. By linking gene expression, cellular changes and computational models of neuronal activity, we aim to predict the impact of homeostasis on the function of circuits in the brain and ultimately on cognitive processes and behaviour. The models and experimental results generated by this study will be of benefit and application in several areas. 1) By establishing basic links between genes, communication between neurons and neural homeostasis, the study will provide important insight into how neurons function in the healthy brain. It will form a basis for further investigations of how specific genes influence brain function. 2) The results of the study will give a foundation for investigation of the roles of homeostasis during aging and in disease. Identification of cellular changes underpinning homeostasis will provide potential targets for drug discovery and our approach to altering excitability in adult neurons will provide a useful model for drug testing and validation. 3) The computational models that we build will enable dry lab testing of potential therapeutic strategies in development by pharmaceutical or biotechnology companies.

在整个生命过程中，大脑都面临着保持稳定性的挑战，同时还要足够灵活地响应环境变化并进行记忆存储所需的修改。面对这些挑战，将大脑功能维持在某个设定点附近的过程称为体内平衡。体内平衡调节神经元的电活动，对于终生健康和健康衰老可能极其重要。需要将神经元的活动维持在最佳范围内。如果神经元的活动过多或过少，神经元就会受损或信息丢失。据信，体内平衡缺陷在一系列脑部疾病中发挥着关键作用，而这些脑部疾病是制药和生物技术行业的目标。然而，我们对稳定成人大脑神经活动的基本细胞或分子机制知之甚少。我们提出了一种新方法来建立介导成人大脑稳态的基本细胞和分子机制。我们的方法使用我们最近开发的分子工具来专门操纵成年小鼠大脑中已识别的神经元群的活动。通过这些工具，我们可以增加或减少神经元活动，然后直接测量使关键神经元功能恢复到先前设定点的稳态反应。我们将重点关注称为齿状回 (DG) 的大脑区域，该区域对于空间记忆很重要，并且与年龄相关的记忆丧失有关。这是一个很好的模型，因为它具有明确的解剖学和生理学特性。我们的初步数据表明，齿状回中的神经元稳态适应导致其活动增加或减少的操作。我们现在建议使用这种新方法来识别对成人大脑稳态很重要的分子并了解其潜在机制。我们将使用我们的新分子工具来诱导成年小鼠 DG 神经元的稳态反应。然后，我们将使用电生理记录来测量使神经活动返回到之前的设定点所发生的功能变化。这些实验将确定神经元是否通过改变它们之间的通信或改变它们处理传入信息的方式来平衡其活动水平的变化。我们将开发计算模型来协调不同实验的数据，并为进一步的实验做出可测试的预测。使用基因表达谱技术，我们将识别哪些基因在稳态反应期间变得更加活跃或不活跃。然后我们将研究这些基因如何促进与体内平衡相关的细胞变化。通过将基因表达、细胞变化和神经元活动的计算模型联系起来，我们的目标是预测稳态对大脑回路功能以及最终对认知过程和行为的影响。这项研究产生的模型和实验结果将在多个领域发挥作用和应用。 1）通过建立基因之间、神经元之间的通讯和神经稳态之间的基本联系，该研究将为神经元如何在健康大脑中发挥作用提供重要的见解。它将为进一步研究特定基因如何影响大脑功能奠定基础。 2）研究结果将为研究衰老和疾病过程中体内平衡的作用奠定基础。识别支持稳态的细胞变化将为药物发现提供潜在的靶点，而我们改变成体神经元兴奋性的方法将为药物测试和验证提供有用的模型。 3）我们构建的计算模型将使制药或生物技术公司开发的潜在治疗策略能够进行干实验室测试。

项目成果

Continuous attractor network models of grid cell firing based on excitatory-inhibitory interactions.

• DOI: 10.1113/jp270630
• 发表时间: 2016-11-15
• 期刊: The Journal of physiology
• 作者: Shipston-Sharman O;Solanka L;Nolan MF
• 通讯作者: Nolan MF

Molecularly Defined Circuitry Reveals Input-Output Segregation in Deep Layers of the Medial Entorhinal Cortex.

• DOI: 10.1016/j.neuron.2015.10.041
• 发表时间: 2015-12-02
• 期刊: Neuron
• 影响因子: 16.2
• 作者: Sürmeli G;Marcu DC;McClure C;Garden DLF;Pastoll H;Nolan MF
• 通讯作者: Nolan MF

Inter- and intra-animal variation of integrative properties of stellate cells in the medial entorhinal cortex

内侧内嗅皮层星状细胞整合特性的动物间和动物内变异

• DOI: 10.1101/678565
• 发表时间: 2019
• 作者: Pastoll H

Laminar and dorsoventral molecular organization of the medial entorhinal cortex revealed by large-scale anatomical analysis of gene expression.

• DOI: 10.1371/journal.pcbi.1004032
• 发表时间: 2015-01
• 期刊: PLoS computational biology
• 影响因子: 4.3
• 作者: Ramsden HL;Sürmeli G;McDonagh SG;Nolan MF
• 通讯作者: Nolan MF