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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,用于探索多个尖峰列车中的时空模式

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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). (C) 2010 Elsevier B.V. All rights reserved.
机译:在过去几年中,多个尖峰列车的同时记录已被神经科学家广泛使用。因此,开发新工具,用于分析多个尖峰列车,以获得新的洞察神经系统功能。本文介绍了视野分析领域的技术如何透露神经活动的特定模式。已经开发出一个名为eraster的交互式栅格图。该软件采用了一系列统计程序,用于具有多个尖峰列车的可视化和灵活的操作。例如,有几个程序可用于重新排序的尖峰列车,其可用于揭开活动传播,尖峰同步和多个尖峰列车活动的许多其他重要特征。另外,伊拉斯特包括神经活动的速率表示,速率和尖峰的组合表示,尖峰列车去除和时间间隔去除。此外,它提供了多种协调的视图,时间和尖峰火车缩放窗口,鱼眼镜头失真和传播设施。伊拉斯特是一个用户友好,交互式的灵活的工具,支持广泛的视觉表示。此工具已成功用于分析合成和实验录制的数据集。在本文中,描述了Iraster的主要特征,并且使用包括来自小鼠视网膜中神经节细胞层的实验多电极阵列记录的各种类型数据来证明其性能和有效性。伊拉斯特是普利茅斯大学可视化实验室的持续研究项目的一部分,称为Visa(秒间协会的可视化)。签证项目的整体目标是提供神经科学家,具有自由探索和分析其数据的能力。该软件可从Visualization Lab网站自由提供(见www.plymouth.ac.uk/infovis)。 (c)2010年elsevier b.v.保留所有权利。

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