Computational tools for simulation of stochastic ion channel activity in neurons

用于模拟神经元随机离子通道活动的计算工具

• 批准号: BB/E014526/1
• 负责人: Matthew Nolan
• 金额: $ 10.55万
• 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: 2006
• 资助国家: 英国
• 起止时间: 2006 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FE014526%2F1
• 关键词: Computational; tools; simulation; stochastic; ion

A fundamental goal of modern biology is to understand how the physical and behavioural characteristics of living organisms arise from components, such as cells and molecules, which are often too small to be seen with the naked eye. Considerable progress has been made towards determining how the physical properties of living organisms are specified by their genetic code, which is contained in individual molecules of DNA. By contrast, we understand much less about the physical principles that govern human or animal behaviour. For example, although it is clear that communication between nerve cells is a key component of brain function, the appropriate level of physical detail at which nerve cells must be understood to fully account for human or animal behaviour is far from clear. Most nerve cells have ornate branching structures, called axons and dendrites, which play fundamental roles in processing of information in the brain. In a single nerve cell these structures may contain well over a million ion channels, small molecules that determine how the cell processes information. While in the past neuroscientists have generally only considered how the average activity of this large umber of ion channels influences the function of nerve cells, recent evidence suggests that fluctuations in the activity of individual ion channels may be a critical determinant of nervous system function. Yet, we have few clear insights into how this basic property of ion channel function affects information processing in the brain. One promising approach to this problem is to develop computer models to simulate ion channel activity. However, at present accurately simulating the activity of each ion channel in complex neuronal structures is a formidable task, and it has therefore been difficult to explore how fluctuations in the activity of individual ion channels influences brain function. The goal of the proposed study is to develop new tools to efficiently simulate models of neurons or neuronal circuits that explicitly simulate the activity and location of individual ion channels. These tools will take advantage of recently developed computational algorithms, together with advances in computer science and methods for parallel computing, to reduce the time required for simulation of these models by greater than 100 fold. To facilitate compatibility with other widely used software, the tools will build on current community standards for specification of neuronal models and will be made freely available for download by other researchers or interested parties. Development of these new computational tools will enable new and fundamental questions to be addressed. For example, what particular aspects of neural information processing are most sensitive to fluctuations in the activity of individual ion channels? Do these fluctuations impair neural function, for example by introducing noise, or do they increase the computational power of neural circuits, for example though stochastic resonance effects? If they impair neural function then what mechanisms have evolved to counteract this effect? Conversely, if they confer benefits, then how are these advantages optimized in biological systems? The proposed project will prime new areas of research in the principal investigators laboratory that will aim to address these questions. More generally it will provide a new set of tools, of general use to the wider research community, that may lead to a better understanding of the relationship between the properties of single ion channel molecules, computations carried out by neural circuits and the behaviour of living organisms.

现代生物学的一个基本目标是了解活生物体的物理和行为特征是如何从诸如细胞和分子之类的成分中产生的，这些成分通常太小而无法用肉眼看到。在确定生物体的物理特性是如何由它们的遗传密码决定的方面已经取得了相当大的进展，遗传密码包含在单个DNA分子中。相比之下，我们对支配人类或动物行为的物理原理的了解要少得多。例如，虽然神经细胞之间的交流是大脑功能的关键组成部分，这一点很清楚，但要充分解释人类或动物的行为，必须了解神经细胞的适当物理细节水平，这一点还远不清楚。大多数神经细胞都有华丽的分支结构，被称为轴突和树突，它们在大脑的信息处理中起着重要作用。在单个神经细胞中，这些结构可能包含超过一百万个离子通道，这些小分子决定了细胞如何处理信息。过去，神经科学家通常只考虑大量离子通道的平均活动如何影响神经细胞的功能，但最近的证据表明，单个离子通道活动的波动可能是神经系统功能的关键决定因素。然而，对于离子通道功能的这一基本特性如何影响大脑中的信息处理，我们知之甚少。解决这个问题的一个有希望的方法是开发计算机模型来模拟离子通道的活性。然而，目前准确模拟复杂神经元结构中每个离子通道的活动是一项艰巨的任务，因此很难探索单个离子通道活动的波动如何影响大脑功能。这项研究的目标是开发新的工具来有效地模拟神经元或神经元回路的模型，明确地模拟单个离子通道的活动和位置。这些工具将利用最近开发的计算算法，以及计算机科学和并行计算方法的进步，将模拟这些模型所需的时间减少100倍以上。为了促进与其他广泛使用的软件的兼容性，这些工具将建立在当前的神经元模型规范社区标准之上，并将免费提供给其他研究人员或感兴趣的团体下载。这些新的计算工具的发展将使新的和基本的问题得到解决。例如，神经信息处理的哪些特定方面对单个离子通道活动的波动最敏感？这些波动是否会损害神经功能，例如通过引入噪声，或者它们是否会增加神经回路的计算能力，例如通过随机共振效应？如果它们损害神经功能，那么进化出了什么机制来抵消这种影响？相反，如果它们能带来好处，那么这些好处如何在生物系统中得到优化？拟议的项目将在主要研究人员实验室中开辟新的研究领域，旨在解决这些问题。更一般地说，它将提供一套新的工具，对更广泛的研究团体普遍使用，这可能会导致更好地理解单个离子通道分子的性质，神经回路进行的计算和生物体行为之间的关系。