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iRaster: A novel information visualization tool to explore spatiotemporal patterns in multiple spike trains

机译:iRaster:一种新颖的信息可视化工具,用于探索多个峰值序列中的时空模式

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Over the last few years, simultaneous recordings of multiple spike trains have become widely used by neuroscientists. Therefore, it is important to develop new tools for analysing multiple spike trains in order to gain new insight into the function of neural systems. This paper describes how techniques from the field of visual analytics can be used to reveal specific patterns of neural activity. An interactive raster plot called iRaster has been developed. This software incorporates a selection of statistical procedures for visualization and flexible manipulations with multiple spike trains. For example, there are several procedures for the re-ordering of spike trains which can be used to unmask activity propagation, spiking synchronization, and many other important features of multiple spike train activity. Additionally, iRaster includes a rate representation of neural activity, a combined representation of rate and spikes, spike train removal and time interval removal. Furthermore, it provides multiple coordinated views, time and spike train zooming windows, a fisheye lens distortion, and dissemination facilities. iRaster is a user friendly, interactive, flexible tool which supports a broad range of visual representations. This tool has been successfully used to analyse both synthetic and experimentally recorded datasets. In this paper, the main features of iRaster are described and its performance and effectiveness are demonstrated using various types of data including experimental multi-electrode array recordings from the ganglion cell layer in mouse retina. iRaster is part of an ongoing research project called VISA (Visualization of Inter-Spike Associations) at the Visualization Lab in the University of Plymouth. The overall aim of the VISA project is to provide neuroscientists with the ability to freely explore and analyse their data. The software is freely available from the Visualization Lab website (see www.plymouth.ac.uk/infovis).
机译:在最近几年中,神经科学家广泛使用了同时记录多个峰值序列的记录。因此,重要的是开发新的工具来分析多个峰值序列,以获得对神经系统功能的新见解。本文介绍了如何使用视觉分析领域的技术来揭示神经活动的特定模式。已经开发了一个交互式的栅格图,称为iRaster。该软件结合了多种统计程序,以实现可视化和带有多个峰值序列的灵活操作。例如,存在几种用于对尖峰脉冲序列进行重新排序的过程,这些过程可用于掩盖活动传播,尖峰同步以及多个尖峰脉冲序列活动的许多其他重要特征。此外,iRaster包括神经活动的速率表示,速率和峰值的组合表示,峰值序列去除和时间间隔去除。此外,它提供了多个协调的视图,时间和峰值火车缩放窗口,鱼眼镜头变形和传播设施。 iRaster是一种用户友好,交互式,灵活的工具,支持广泛的视觉表示。该工具已成功用于分析合成和实验记录的数据集。本文介绍了iRaster的主要特征,并使用各种类型的数据(包括来自小鼠视网膜神经节细胞层的实验性多电极阵列记录)证明了iRaster的性能和有效性。 iRaster是普利茅斯大学可视化实验室正在进行的名为VISA(钉间关联可视化)研究项目的一部分。 VISA项目的总体目标是为神经科学家提供自由探索和分析其数据的能力。该软件可从Visualization Lab网站免费获得(请参阅www.plymouth.ac.uk/infovis)。

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