A systems approach to the cellular and molecular organization of neural circuits for representation of space
A systems approach to the cellular and molecular organization of neural circuits for representation of space
批准号:
BB/L010496/1
负责人:
Matthew Nolan
金额:
$91.67万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2014
资助国家:
英国
项目状态:
已结题
起止时间:
2014 至 --
中文摘要
科学中最具挑战性的问题之一是了解大脑中神经细胞表达的分子如何使思想和行动发生。这对于理解大脑是如何工作的是至关重要的。它还将支持未来神经和精神疾病治疗方法的工业发展,以及生物灵感计算技术的工业发展。分子的合成和细胞的组装在大脑和身体的其他器官中是相似的,但大脑的不同之处在于它能够有效地执行相当复杂的计算。这些计算依赖于神经细胞之间的电信号交流。一些重要的计算是由组织成模块的神经细胞组执行的,但这些模块如何与神经细胞之间的电信号组织有关尚不清楚。这一点很重要,因为控制电信号的分子是基因表达和认知过程之间的关键分子联系。我们将专注于大脑的一个子区域,称为内嗅觉皮质。在探索过程中,该区域上端的神经细胞形成一个模块,以大约30厘米的相对较高的分辨率编码动物的位置。在这个区域的下方,不同的神经细胞模块以较低的分辨率编码位置。由于现有的方法依赖于记录活体动物神经元的电活动,因此目前检查它们的物理基础是非常具有挑战性的。我们的目标是通过使用体外实验结合定量和预测计算模型来解决这个问题。我们将首先确定单个神经细胞或其连接的电学性质是否具有模块化组织。我们将使用电极记录单个组织切片中的多个神经细胞。如果电学特性有助于模块化组织,那么我们期望来自同一网络的细胞比来自不同网络的细胞彼此更相似。接下来,我们将唤起协调的网络活动,同时同时从四个细胞进行电子记录。我们希望通过细胞活动中的特定关联来识别属于同一模块的细胞。为了识别组织电学性质和连通性的分子,我们将识别标记模块的候选基因。然后,我们将确定他们是否根据神经元的电学特性和连接性来标记特定的神经元亚群。在实验的每个阶段获得的数据将指导计算机模型的开发。通过将实验结果与模型预测进行比较,我们将能够改进和提高模型的预测能力,同时还可以确定模型可能尚未解释的功能,因此需要进一步研究。通过这种方式,我们的目标是揭示大脑运行的新的计算原理,并最终使基因表达、电信号和大脑功能之间建立直接联系。所产生的模型和实验结果将在多个领域中受益和应用。1)通过建立基因、电信号和神经细胞计算之间的基本联系,这项研究将对理解健康的大脑非常重要。它们将为进一步研究特定基因如何影响大脑功能奠定关键基础。2)我们将重点关注的大脑区域是药物发现的重要目标。我们建立的计算模型将使制药或生物技术公司能够对开发中的潜在治疗策略进行干燥的实验室测试。3)发现的原理可能会刺激未来基于生物的计算设备的设计。例如,改善机器人的导航,开发受神经启发的体系结构,以提高计算硬件的能效。
英文摘要
One of the most challenging problems in science is to understand how the molecules expressed by nerve cells in the brain enable thoughts and actions to take place. This is of fundamental importance for understanding how brains work. It will also underpin future industrial development of therapies for neurological and psychiatric disorders, and of biologically inspired computing technologies. Synthesis of molecules and assembly of cells is similar in the brain and other organs of the body, but the brain is distinguished by its ability to efficiently perform computations of considerable complexity. These computations rely upon communication of electrical signals between nerve cells. Some important computations are carried out by groups of nerve cells organized into modules, but how these modules relate to organization of electrical signaling between nerve cells is not known. This is important because molecules that control electrical signaling are a critical molecular link between gene expression and cognitive processes.We will focus on a sub-region of the brain called the entorhinal cortex. During exploration, nerve cells at the upper end of this region form a module that encodes an animal's location at a relatively high resolution of approximately 30 cm. Lower down within this region, different modules of nerve cells encode location at lower resolutions. As existing approaches rely on recording electrical activity from neurons in live animals it is currently exceptionally challenging to examine their physical basis. We aim to solve this problem by instead using in vitro experiments in combination with quantitative and predictive computational models.We will first establish if electrical properties of single nerve cells or their connections have a modular organization. We will use electrodes to record from many nerve cells in single slices of tissue. If electrical properties contribute to modular organization, then we expect cells from the same network to be more similar to one another than cells from different networks. We will next evoke coordinated network activity while making electrical recordings simultaneously from four cells at a time. We expect to identify cells that are part of the same module by specific correlations in their activity. To identify molecules that organize electrical properties and connectivity, we will identify candidate genes that mark modules. We will then determine if they label specific subgroups of neurons based on their electrical properties and connectivity.Data obtained at each stage of experimentation will guide development of computer models. By comparison of the experimental results with the model predictions we will be able to refine and improve the predictive power of the models, while also identifying functions that the model may not yet explain and that will therefore require further investigation. In this way we aim to reveal new computational principles for brain operation and to ultimately enable direct links to be established between gene expression, electrical signaling and brain function.The models and experimental results generated will be of benefit and application in several areas. 1) By establishing basic links between genes, electrical signaling and computation by nerve cells, the study will be important for understanding the healthy brain. They will form a key foundation for further investigations of how specific genes influences brain function. 2) The brain region that we will focus on is an important target for drug discovery. The computational models that we build will enable dry lab testing of potential therapeutic strategies in development by pharmaceutical or biotechnology companies. 3) The principles uncovered may stimulate future design of biologically based computational devices. For example, to improve navigation by robots, and to develop neurally inspired architectures to improve the energy efficiency of computational hardware.
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Local field potentials get funny.
局部场潜力变得有趣。
DOI:
10.1113/jp272673
发表时间:
2016-07-01
期刊:
The Journal of physiology
影响因子:
--
作者:
[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
期刊:
影响因子:
--
作者:
[Pastoll H]
通讯作者:
Pastoll H
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
DOI:
10.1101/681312
发表时间:
2019-06
期刊:
bioRxiv
影响因子:
--
作者:
[Klara Gerlei;Jessica Passlack;Ian Hawes;Brianna Vandrey;Holly Stevens;Ioannis Papastathopoulos;M. Nolan]
通讯作者:
Klara Gerlei;Jessica Passlack;Ian Hawes;Brianna Vandrey;Holly Stevens;Ioannis Papastathopoulos;M. Nolan
DOI:
10.1038/nn.4652
发表时间:
2017
期刊:
Nature neuroscience
影响因子:
25
作者:
[Schmidt-Hieber C]
通讯作者:
Schmidt-Hieber C
共 6 条
Connecting objects to places: functional investigation of projections from lateral to medial entorhinal cortex
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