探索神经连接矩阵的交互式Web应用程序
Interactive Web Application for Exploring Matrices of Neural Connectivity
摘要：
我们在这里提出了一个基于浏览器的应用程序，用于可视化具有大量成对关系的3D堆叠数据矩阵中的连接模式。可视化连接矩阵，寻找趋势和模式，并动态地操纵这些值是来自不同领域的科学家面临的挑战，包括神经科学和基因组学。特别是，高维神经数据包括通过脑电图（EEG），皮层电图（ECoG），脑磁图（MEG）和功能MRI采集的数据。神经连接数据包含不同大脑区域之间每个边缘的多变量属性，这促使我们开发轻量级，开源，易于使用的可视化工具来探索这些连接矩阵，以突出感兴趣的连接。在这里，我们提出了一个客户端，移动兼容的可视化工具，完全在HTML5/JavaScript，允许在浏览器中操作用户定义的文件，探索大脑的连接。可视化可以在不同的维度上同时突出显示数据的不同方面。输入文件是JSON格式的，并且已经编写了自定义Python脚本来将MATLAB或Python数据文件解析为JSON-JSON格式。我们展示了通过人类ECoG记录获取的连接数据的分析，作为我们的应用程序的特定领域的实现。我们设想这种交互式工具在寻求可视化成对连接领域的应用。
英文摘要：
We present here a browser-based application for visualizing patterns of connectivity in 3D stacked data matrices with large numbers of pairwise relations. Visualizing a connectivity matrix, looking for trends and patterns, and dynamically manipulating these values is a challenge for scientists from diverse fields, including neuroscience and genomics. In particular, high-dimensional neural data include those acquired via electroencephalography (EEG), electrocorticography (ECoG), magnetoencephalography (MEG), and functional MRI. Neural connectivity data contains multivariate attributes for each edge between different brain regions, which motivated our lightweight, open source, easy-to-use visualization tool for the exploration of these connectivity matrices to highlight connections of interest. Here we present a client-side, mobile-compatible visualization tool written entirely in HTML5/JavaScript that allows in-browser manipulation of user-defined files for exploration of brain connectivity. Visualizations can highlight different aspects of the data simultaneously across different dimensions. Input files are in JSON format, and custom Python scripts have been written to parse MATLAB or Python data files into JSON-loadable format. We demonstrate the analysis of connectivity data acquired via human ECoG recordings as a domain-specific implementation of our application. We envision applications for this interactive tool in fields seeking to visualize pairwise connectivity.
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