Novel analytical and datasharing tools for rich neuronal activity datasets obtained with a 4096 electrodes array

用于通过 4096 电极阵列获得的丰富神经元活动数据集的新颖分析和数据共享工具

• 批准号: BB/H023569/1
• 负责人: Evelyne Sernagor
• 金额: $ 12.68万
• 依托单位: Newcastle University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FH023569%2F1
• 关键词: Novel; analytical; datasharing; tools; rich

The functional intricacy of the central nervous system (CNS) arises from the complex anatomical and dynamic interactions between different types of neurones involved in specific networks. Hence, the encoding of information in neural circuits occurs as a result of interactions between individual neurones as well as through the interplay within both microcircuits (made of few neurones) and large scale networks involving thousands to millions of cells. One of the great challenges of neuroscience nowadays is to understand how these neural networks are formed and how they operate. Such challenge can be resolved only through simultaneous recording from thousands of neurones that become active during specific neuronal tasks. One of the experimental approaches to fulfil this goal is to use multielectrode arrays (MEAs) that consist of several channels (electrodes) that can each record (and/or stimulate) from few adjacent neurones within a particular area of the CNS. MEAs can be used in vitro to record from dissociated neuronal cultures or from brain slices or isolated retinas. These MEAs consist of assemblies of electrodes embedded in planar substrates. Typical commercial MEAs consist of 60-128 electrodes with a spacing of 100-200 um. Considering that a generic neurone in the mammalian CNS has a diameter of about 10 um, it is obvious that such MEAs cannot convey information on the activity of all neurones involved in a specific network, but rather just from a sample of these cells. To overcome this activity under-sampling, in this project, we will use the Active Pixel Sensor (APS) MEA, a novel type of MEA platform developed in a NEST-EU Project by our collaborator Luca Berdondini (Italian Institute of Technology, Genova). This MEA consists of 4,096 electrodes with near cellular resolution (21x21 um, 42 um centre-to-centre separation, covering an active area of 2.5 mm x 2.5 mm), where recording is possible from all channels at the same time. We will use the APS MEA to record spontaneous waves of activity that are present in the neonatal vertebrate retina. These waves occur during a short period of development during perinatal weeks and they are known to play an important role in guiding the precise wiring of neural connections in the visual system, both at the retinal and extra-retinal levels. The APS-MEA, thanks to its unmet size and resolution, will enable us to reach new insights into the precise dynamics of these waves as never achieved before. Recordings from such large scale networks at near cellular resolution generate extremely rich datasets with the drawback that these datasets are very large and difficult to handle, thus necessitating the development of new powerful analytical tools enabling to decode in a fast, efficient and user-friendly way how cellular elements interact in the network. The development of such computational tools is the central goal of this project, while the experimental work on the retina defines a challenging and unique scientific context. The tools we plan to develop will yield parameters that will help us reach better understanding of network function, from the temporal firing patterns of individual neurones to how activity precisely propagates within the network. We will also develop novel tools for easier visualisation of the dynamical behaviour of the activity within the network. These tools will be developed in a language that could be easily utilized by other investigators using the same recording system or other platforms of their choice. Finally, to ensure that these tools are accessible to the wide neurophysiology community, they will be deployed on CARMEN (Code Analysis, Repository and Modelling for e-Neuroscience), a new internet-based neurophysiology sharing resource designed for facilitating worldwide communication between collaborating neurophysiologists.

中枢神经系统（CNS）的功能复杂性源于参与特定网络的不同类型神经元之间复杂的解剖学和动力学相互作用。因此，神经回路中的信息编码是单个神经元之间相互作用的结果，也是通过微回路（由少数神经元组成）和涉及数千至数百万细胞的大规模网络之间的相互作用而发生的。当今神经科学面临的最大挑战之一是了解这些神经网络是如何形成的，以及它们是如何运作的。这种挑战只能通过同时记录在特定神经元任务中变得活跃的数千个神经元来解决。实现这一目标的实验方法之一是使用多电极阵列（MEA），它由几个通道（电极）组成，每个通道可以记录（和/或刺激）CNS特定区域内的几个相邻神经元。MEA可以在体外用于从分离的神经元培养物或从脑切片或分离的视网膜记录。这些MEA由嵌入平面基板中的电极组件组成。典型的商业MEA由60-128个电极组成，电极间距为100-200 μ m。考虑到哺乳动物CNS中的一般神经元具有约10 μ m的直径，很明显，这种MEA不能传递关于特定网络中涉及的所有神经元的活性的信息，而是仅来自这些细胞的样品。为了克服这种活动采样不足，在本项目中，我们将使用有源像素传感器（APS）MEA，这是我们的合作者Luca Berdondini（意大利理工学院，热那亚）在NEST-EU项目中开发的一种新型MEA平台。该MEA由4，096个电极组成，具有接近细胞的分辨率（21 x21 um，42 um中心到中心间隔，覆盖2.5 mm x 2.5 mm的有效面积），其中可以同时从所有通道进行记录。我们将使用APS MEA记录新生脊椎动物视网膜中存在的自发活动波。这些波发生在围产期的短期发展期间，并且已知它们在指导视觉系统中的神经连接的精确布线方面发挥重要作用，无论是在视网膜还是视网膜外水平。APS-MEA由于其未满足的尺寸和分辨率，将使我们能够对这些波的精确动态进行前所未有的新见解。来自这种大规模网络的以接近细胞分辨率的记录产生极其丰富的数据集，缺点是这些数据集非常大并且难以处理，因此需要开发新的强大的分析工具，从而能够以快速、有效和用户友好的方式解码细胞元素如何在网络中相互作用。开发这样的计算工具是该项目的中心目标，而视网膜的实验工作定义了一个具有挑战性和独特的科学背景。我们计划开发的工具将产生有助于我们更好地理解网络功能的参数，从单个神经元的时间放电模式到活动如何在网络中精确传播。我们还将开发新的工具，以更容易地可视化网络内活动的动态行为。这些工具将以其他调查人员使用同一记录系统或他们选择的其他平台容易使用的语言开发。最后，为了确保这些工具可以被广泛的神经生理学社区使用，它们将被部署在CARMEN（电子神经科学的代码分析，存储库和建模）上，这是一个新的基于互联网的神经生理学共享资源，旨在促进全球合作神经生理学家之间的交流。

项目成果

Non-parametric physiological classification of retinal ganglion cells in the mouse retina

小鼠视网膜视网膜神经节细胞的非参数生理学分类

• DOI: 10.1101/407635
• 发表时间: 2018
• 作者: Jouty J

Spike Detection for Large Neural Populations Using High Density Multielectrode Arrays.

• DOI: 10.3389/fninf.2015.00028
• 发表时间: 2015
• 期刊: Frontiers in neuroinformatics
• 影响因子: 3.5
• 作者: Muthmann JO;Amin H;Sernagor E;Maccione A;Panas D;Berdondini L;Bhalla US;Hennig MH
• 通讯作者: Hennig MH

Pan-retinal characterisation of Light Responses from Ganglion Cells in the Developing Mouse Retina.

• DOI: 10.1038/srep42330
• 发表时间: 2017-02-10
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Hilgen G;Pirmoradian S;Pamplona D;Kornprobst P;Cessac B;Hennig MH;Sernagor E
• 通讯作者: Sernagor E

Following the ontogeny of retinal waves: pan-retinal recordings of population dynamics in the neonatal mouse.

• DOI: 10.1113/jphysiol.2013.262840
• 发表时间: 2014-04-01
• 期刊: The Journal of physiology
• 作者: Maccione A;Hennig MH;Gandolfo M;Muthmann O;van Coppenhagen J;Eglen SJ;Berdondini L;Sernagor E
• 通讯作者: Sernagor E

A head mounted device stimulator for optogenetic retinal prosthesis.

• DOI: 10.1088/1741-2552/aadd55
• 发表时间: 2018-12
• 期刊: Journal of neural engineering
• 影响因子: 4
• 作者: Soltan A;Barrett JM;Maaskant P;Armstrong N;Al-Atabany W;Chaudet L;Neil M;Sernagor E;Degenaar P
• 通讯作者: Degenaar P