脑功能连通性的视觉分析

M. D. Ridder, Karsten Klein, Jinman Kim
{"title":"脑功能连通性的视觉分析","authors":"M. D. Ridder, Karsten Klein, Jinman Kim","doi":"10.5220/0005305901310138","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":326087,"journal":{"name":"International Conference on Information Visualization Theory and Applications","volume":"391 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"CereVA - Visual Analysis of Functional Brain Connectivity\",\"authors\":\"M. D. Ridder, Karsten Klein, Jinman Kim\",\"doi\":\"10.5220/0005305901310138\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":326087,\"journal\":{\"name\":\"International Conference on Information Visualization Theory and Applications\",\"volume\":\"391 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Information Visualization Theory and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0005305901310138\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Information Visualization Theory and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0005305901310138","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信