脑功能连通性的视觉分析

M. D. Ridder, Karsten Klein, Jinman Kim
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引用次数: 9

摘要

我们提出了CereVA,一个基于网络的界面,用于大脑活动数据的可视化分析。CereVA结合了2D和3D可视化,允许用户交互式地探索和比较大脑活动数据集。基于web的界面结合了网络数据的几个链接的图形表示,允许不同可视化的紧密集成。通过连接网络的节点链接可视化和数据的矩阵视图,数据在解剖背景下以3D体绘制的形式呈现。此外,我们的方法提供了连通性网络的图理论分析。我们的解决方案支持多个分析任务,包括连接性网络的比较、相关模式的分析和网络的聚合,例如在人口中。
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CereVA - Visual Analysis of Functional Brain Connectivity
We present CereVA, a web-based interface for the visual analysis of brain activity data. CereVA combines 2D and 3D visualizations and allows the user to interactively explore and compare brain activity data sets. The web-based interface combines several linked graphical representations of the network data, allowing for tight integration of different visualizations. The data is presented in the anatomical context within a 3D volume rendering, by node-link visualizations of connectivity networks, and by a matrix view of the data. In addition, our approach provides graph-theoretical analysis of the connectivity networks. Our solution supports several analysis tasks, including the comparison of connectivity networks, the analysis of correlation patterns, and the aggregation of networks, e.g. over a population.
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