Networks of neural dynamics: Knowledge-discovery for experimental neuroscience

神经动力学网络:实验神经科学的知识发现

基本信息

  • 批准号:
    MR/J008648/1
  • 负责人:
  • 金额:
    $ 167.34万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Fellowship
  • 财政年份:
    2012
  • 资助国家:
    英国
  • 起止时间:
    2012 至 无数据
  • 项目状态:
    已结题

项目摘要

What is happening in your brain when you think and act? Cells are firing tiny electrical pulses, little spikes of activity, all across the brain. Some groups of cells emit these spikes at the same time, all of them responding to sudden noise, or to the swinging of your arm. In other groups, the spikes occur in a fixed sequence across the cells, remembering the path you just took from the front door to the bus-stop. Fundamentally, the brain works by co-ordinating activity between its cells. So when cells stop being precisely co-ordinated, the brain stops working properly. In an epileptic fit, the cells across the cortex all become synchronised and waves of activity drown out the fine control of the muscles. In dementia, the loss of synchronisation between cells prevents reliable recall of past events. The goal of my research is to enable us to find and analyse the co-ordinated activity of brain cells. Neuroscientists are now able to record the spikes from hundreds of separate cells, for hours at a time, from all across the brain. Yet the resulting data mountain is growing without the ability to analyse those recordings. We have many methods for comparing the activity of two cells, but few for comparing the activity of hundreds. We have even fewer methods for finding when in each recording the co-ordination happens, or for finding which cells are taking part, or for finding if the co-ordination is made up of simultaneous spikes, a sequence of spikes, or something more complex. Without these methods, these recordings cannot reveal what co-ordinated activity of individual cells tells us about how the brain functions and dysfunctions. I will develop analysis methods that are able to take the recordings and automatically solve all these problems: finding when the cells are active together, which groups they belong to, and what form that co-ordinated activity takes. I will apply these methods to three areas of neuroscience research that seek to study the brain in health and disease by recording many cells at the same time. First, with Dr Constance Hammond's lab in Marseille, we will analyse their recordings of the developing rat striatum, a large forebrain system that is central to both the control and learning of actions. We will use my methods to understand how the co-ordinated activity in the healthy striatum develops over pregnancy and infancy, and then understand how genetic and environmental factors disrupt this correct development, leading to disorders of the striatum that appear in youth, like Tourette's syndrome. Second, with Dr Sid Wiener's lab in Paris, we will analyse their recordings from the forebrains of rats learning to solve spatial navigation tasks in mazes. We will use my methods to understand how co-ordinated activity across the forebrain develops during learning. Particularly we will analyse how the sudden onset of widespread co-ordination that precedes correct decisions on the task depends on dopamine, and how replays of co-ordinated activity during sleep lead to improved performance. From the first we can gain a better understanding of how abnormal dopamine in the forebrain, as in schizophrenics, disrupts working memory and decision-making; from the second we can gain a better understanding of how poor quality sleep can affect learning. Third, with Dr Rasmus Petersen's lab in Manchester, we will analyse their recordings from cells in the centre of the rat's brain that fire in response to movements of their whiskers. Dr Petersen's lab study these cells to understand the basic "neural code", the information that is carried by each spike. They have already found that some cells emit spikes in response to single features of movement, such as the whisker's position or velocity, whereas other cells emit spikes only to a complex mix of these features. We will use my methods to understand how these single cell codes combine when co-ordinated, forming the "population code" for sensory information.
当你思考和行动时,你的大脑里发生了什么?细胞发射微小的电脉冲,活动的小尖峰,遍布整个大脑。有些细胞群会同时发出这些尖峰信号,它们都对突然的噪音或你的手臂摆动做出反应;而在另一些细胞群中,这些尖峰信号以固定的顺序出现在细胞群中,记住你刚从前门走到公共汽车站的路径。从根本上说,大脑通过协调细胞之间的活动来工作。因此,当细胞停止精确协调时,大脑就会停止正常工作。在癫痫发作时,大脑皮层的细胞都变得同步,活动波淹没了肌肉的精细控制。在痴呆症中,细胞之间失去同步性会阻止对过去事件的可靠回忆。我的研究目标是使我们能够发现和分析脑细胞的协调活动。神经科学家现在能够记录来自数百个不同细胞的尖峰信号,每次持续数小时,来自整个大脑。然而,由此产生的数据山正在增长,而没有能力分析这些记录。我们有很多方法来比较两个细胞的活性,但很少有方法来比较数百个细胞的活性。我们有更少的方法来发现在每个记录中协调何时发生,或者发现哪些细胞参与其中,或者发现协调是否由同时发生的尖峰信号,尖峰信号序列或更复杂的东西组成。如果没有这些方法,这些记录就无法揭示单个细胞的协调活动告诉我们大脑如何运作和功能障碍。 我将开发能够记录并自动解决所有这些问题的分析方法:发现细胞何时一起活动,它们属于哪组,以及协调活动的形式。我将把这些方法应用于神经科学研究的三个领域,这些领域试图通过同时记录许多细胞来研究健康和疾病中的大脑。首先,在马赛的康斯坦斯哈蒙德博士的实验室,我们将分析他们对发育中的大鼠纹状体的记录,纹状体是一个巨大的前脑系统,对行为的控制和学习都很重要。我们将使用我的方法来了解健康纹状体的协调活动如何在怀孕和婴儿期发展,然后了解遗传和环境因素如何破坏这种正确的发展,导致年轻时出现的纹状体疾病,如图雷特综合征。第二,在巴黎西德·维纳博士的实验室,我们将分析他们从老鼠前脑中记录的在迷宫中学习解决空间导航任务的记录。我们将使用我的方法来了解在学习过程中前脑的协调活动是如何发展的。特别是,我们将分析在正确决定任务之前突然出现的广泛协调如何取决于多巴胺,以及睡眠期间协调活动的重播如何导致性能改善。从第一个角度,我们可以更好地理解前脑中异常的多巴胺是如何扰乱工作记忆和决策的,就像精神分裂症患者一样;从第二个角度,我们可以更好地理解低质量的睡眠是如何影响学习的。第三,在曼彻斯特的Rasmus Petersen博士的实验室,我们将分析老鼠大脑中心细胞的记录,这些细胞对胡须的运动做出反应。彼得森博士的实验室研究这些细胞,以了解基本的“神经代码”,即每个尖峰所携带的信息。他们已经发现,一些细胞会对单一的运动特征(如触须的位置或速度)做出反应,而另一些细胞只会对这些特征的复杂组合做出反应。我们将用我的方法来理解这些单细胞代码如何在协调时结合联合收割机,形成感官信息的“群体代码”。

项目成果

期刊论文数量(10)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
A spiral attractor network drives rhythmic locomotion
  • DOI:
    10.7554/elife.27342
  • 发表时间:
    2017-08-07
  • 期刊:
  • 影响因子:
    7.7
  • 作者:
    Brunolt, Angela M.;Frost, William N.;Humphries, Mark D.
  • 通讯作者:
    Humphries, Mark D.
Modular deconstruction reveals the dynamical and physical building blocks of a locomotion motor program.
模块化解构揭示了运动电机程序的动态和物理构建块。
  • DOI:
    10.1016/j.neuron.2015.03.005
  • 发表时间:
    2015-04-08
  • 期刊:
  • 影响因子:
    16.2
  • 作者:
    Bruno AM;Frost WN;Humphries MD
  • 通讯作者:
    Humphries MD
Early hypersynchrony in juvenile PINK1(-)/(-) motor cortex is rescued by antidromic stimulation.
  • DOI:
    10.3389/fnsys.2014.00095
  • 发表时间:
    2014
  • 期刊:
  • 影响因子:
    3
  • 作者:
    Carron R;Filipchuk A;Nardou R;Singh A;Michel FJ;Humphries MD;Hammond C
  • 通讯作者:
    Hammond C
A probabilistic, distributed, recursive mechanism for decision-making in the brain.
  • DOI:
    10.1371/journal.pcbi.1006033
  • 发表时间:
    2018-04
  • 期刊:
  • 影响因子:
    4.3
  • 作者:
    Caballero JA;Humphries MD;Gurney KN
  • 通讯作者:
    Gurney KN
Passive dendrites enable single neurons to compute linearly non-separable functions.
  • DOI:
    10.1371/journal.pcbi.1002867
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    4.3
  • 作者:
    Cazé RD;Humphries M;Gutkin B
  • 通讯作者:
    Gutkin B
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Mark Humphries其他文献

Real time systems laboratory development: Experiments focusing on a dual core processor
实时系统实验室开发:专注于双核处理器的实验
  • DOI:
    10.18260/1-2--451
  • 发表时间:
    2006
  • 期刊:
  • 影响因子:
    0
  • 作者:
    M. Shirvaikar;Mark Humphries;L. Estevez
  • 通讯作者:
    L. Estevez

Mark Humphries的其他文献

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{{ truncateString('Mark Humphries', 18)}}的其他基金

The computational basis of foraging
觅食的计算基础
  • 批准号:
    BB/X013111/1
  • 财政年份:
    2023
  • 资助金额:
    $ 167.34万
  • 项目类别:
    Research Grant
Uncovering the neural basis of movement transitions
揭示运动转换的神经基础
  • 批准号:
    MR/S025944/1
  • 财政年份:
    2020
  • 资助金额:
    $ 167.34万
  • 项目类别:
    Research Grant
Networks of neural dynamics: Knowledge-discovery for experimental neuroscience
神经动力学网络:实验神经科学的知识发现
  • 批准号:
    MR/J008648/2
  • 财政年份:
    2018
  • 资助金额:
    $ 167.34万
  • 项目类别:
    Fellowship
Resolving the size and nature of neocortical population codes
解决新皮质群体代码的大小和性质
  • 批准号:
    MR/P005659/2
  • 财政年份:
    2018
  • 资助金额:
    $ 167.34万
  • 项目类别:
    Research Grant
Resolving the size and nature of neocortical population codes
解决新皮质群体代码的大小和性质
  • 批准号:
    MR/P005659/1
  • 财政年份:
    2017
  • 资助金额:
    $ 167.34万
  • 项目类别:
    Research Grant

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