The Connectome Visualization Utility: Software for Visualization of Human Brain Networks
In analysis of the human connectome, the connectivity of the human brain is collected from multiple imaging modalities and analyzed using graph theoretical techniques. The dimensionality of human connectivity data is high, and making sense of the complex networks in connectomics requires sophisticat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | en_US |
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Public Library of Science
2014
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| Online Access: | http://hdl.handle.net/1721.1/92493 |
| _version_ | 1811080460842827776 |
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| author | LaPlante, Roan A. Douw, Linda Tang, Wei Stufflebeam, Steven M. |
| author2 | Harvard University--MIT Division of Health Sciences and Technology |
| author_facet | Harvard University--MIT Division of Health Sciences and Technology LaPlante, Roan A. Douw, Linda Tang, Wei Stufflebeam, Steven M. |
| author_sort | LaPlante, Roan A. |
| collection | MIT |
| description | In analysis of the human connectome, the connectivity of the human brain is collected from multiple imaging modalities and analyzed using graph theoretical techniques. The dimensionality of human connectivity data is high, and making sense of the complex networks in connectomics requires sophisticated visualization and analysis software. The current availability of software packages to analyze the human connectome is limited. The Connectome Visualization Utility (CVU) is a new software package designed for the visualization and network analysis of human brain networks. CVU complements existing software packages by offering expanded interactive analysis and advanced visualization features, including the automated visualization of networks in three different complementary styles and features the special visualization of scalar graph theoretical properties and modular structure. By decoupling the process of network creation from network visualization and analysis, we ensure that CVU can visualize networks from any imaging modality. CVU offers a graphical user interface, interactive scripting, and represents data uses transparent neuroimaging and matrix-based file types rather than opaque application-specific file formats. |
| first_indexed | 2024-09-23T11:31:44Z |
| format | Article |
| id | mit-1721.1/92493 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:31:44Z |
| publishDate | 2014 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/924932022-09-27T20:07:43Z The Connectome Visualization Utility: Software for Visualization of Human Brain Networks LaPlante, Roan A. Douw, Linda Tang, Wei Stufflebeam, Steven M. Harvard University--MIT Division of Health Sciences and Technology Stufflebeam, Steven M. In analysis of the human connectome, the connectivity of the human brain is collected from multiple imaging modalities and analyzed using graph theoretical techniques. The dimensionality of human connectivity data is high, and making sense of the complex networks in connectomics requires sophisticated visualization and analysis software. The current availability of software packages to analyze the human connectome is limited. The Connectome Visualization Utility (CVU) is a new software package designed for the visualization and network analysis of human brain networks. CVU complements existing software packages by offering expanded interactive analysis and advanced visualization features, including the automated visualization of networks in three different complementary styles and features the special visualization of scalar graph theoretical properties and modular structure. By decoupling the process of network creation from network visualization and analysis, we ensure that CVU can visualize networks from any imaging modality. CVU offers a graphical user interface, interactive scripting, and represents data uses transparent neuroimaging and matrix-based file types rather than opaque application-specific file formats. National Institutes of Health (U.S.) (Grant R01-NS069696) National Institutes of Health (U.S.) (Grant U01-MH093765) National Institutes of Health (U.S.) (Grant P41-RR14075) United States. Defense Advanced Research Projects Agency 2014-12-23T22:17:44Z 2014-12-23T22:17:44Z 2014-12 2014-08 Article http://purl.org/eprint/type/JournalArticle 1932-6203 http://hdl.handle.net/1721.1/92493 LaPlante, Roan A., Linda Douw, Wei Tang, and Steven M. Stufflebeam. “The Connectome Visualization Utility: Software for Visualization of Human Brain Networks.” Edited by Daniele Marinazzo. PLoS ONE 9, no. 12 (December 1, 2014): e113838. en_US http://dx.doi.org/10.1371/journal.pone.0113838 PLoS ONE Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ application/pdf Public Library of Science Public Library of Science |
| spellingShingle | LaPlante, Roan A. Douw, Linda Tang, Wei Stufflebeam, Steven M. The Connectome Visualization Utility: Software for Visualization of Human Brain Networks |
| title | The Connectome Visualization Utility: Software for Visualization of Human Brain Networks |
| title_full | The Connectome Visualization Utility: Software for Visualization of Human Brain Networks |
| title_fullStr | The Connectome Visualization Utility: Software for Visualization of Human Brain Networks |
| title_full_unstemmed | The Connectome Visualization Utility: Software for Visualization of Human Brain Networks |
| title_short | The Connectome Visualization Utility: Software for Visualization of Human Brain Networks |
| title_sort | connectome visualization utility software for visualization of human brain networks |
| url | http://hdl.handle.net/1721.1/92493 |
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