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舷窗和风暴云:时空 M/EEG 统计可视化工具。

Porthole and Stormcloud: Tools for Visualisation of Spatiotemporal M/EEG Statistics.

机构信息

Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia.

Queensland Brain Institute, University of Queensland, Brisbane, Australia.

出版信息

Neuroinformatics. 2020 Jun;18(3):351-363. doi: 10.1007/s12021-019-09447-6.

Abstract

Electro- and magneto-encephalography are functional neuroimaging modalities characterised by their ability to quantify dynamic spatiotemporal activity within the brain. However, the visualisation techniques used to illustrate these effects are currently limited to single- or multi-channel time series plots, topographic scalp maps and orthographic cross-sections of the spatiotemporal data structure. Whilst these methods each have their own strength and weaknesses, they are only able to show a subset of the data and are suboptimal at articulating one or both of the space-time components.Here, we propose Porthole and Stormcloud, a set of data visualisation tools which can automatically generate context appropriate graphics for both print and screen with the following graphical capabilities: Animated two-dimensional scalp maps with dynamic timeline annotation and optional user interaction; Three-dimensional construction of discrete clusters within sparse spatiotemporal volumes, rendered with 'cloud-like' appearance and augmented by cross-sectional scalp maps indicating local maxima. These publicly available tools were designed specifically for visualisation of M/EEG spatiotemporal statistical parametric maps, however, we also demonstrate alternate use cases of posterior probability maps and weight maps produced by machine learning classifiers. In principle, the methods employed here are transferrable to visualisation of any spatiotemporal image.

摘要

脑电和磁脑图是功能神经影像学模式,其特点是能够量化大脑内动态时空活动。然而,用于说明这些效应的可视化技术目前仅限于单通道或多通道时间序列图、头皮地形图和时空数据结构的正交剖面图。虽然这些方法各有其优点和缺点,但它们只能显示数据的一部分,并且在表达时空分量之一或两者方面不是最佳的。在这里,我们提出了 Porthole 和 Stormcloud,这是一组数据可视化工具,可以自动为打印和屏幕生成上下文适当的图形,具有以下图形功能:带有动态时间线注释和可选用户交互的动画二维头皮图;稀疏时空体积内离散簇的三维构建,呈现“云状”外观,并通过指示局部最大值的头皮图进行增强。这些公开可用的工具是专门为可视化 M/EEG 时空统计参数图而设计的,但是,我们还演示了机器学习分类器生成的后验概率图和权重图的替代用例。原则上,这里采用的方法可转移到任何时空图像的可视化。

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