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Cited by 59Data Visualization and AnalyticsFunctional Brain Connectivity StudiesComputer Graphics and Visualization Techniques

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Three-Dimensional Mean-Shift Edge Bundling for the Visualization of Functional Connectivity in the Brain

Bottger, Joachim, Schafer, Alexander, Lohmann, Gabriele, Villringer, Arno, Margulies, Daniel S.·2014·IEEE Transactions on Visualization and Computer Graphics
DOI 10.1109/tvcg.2013.114
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Abstract

Functional connectivity, a flourishing new area of research in human neuroscience, carries a substantial challenge for visualization: while the end points of connectivity are known, the precise path between them is not. Although a large body of work already exists on the visualization of anatomical connectivity, the functional counterpart lacks similar development. To optimize the clarity of whole-brain and complex connectivity patterns in three-dimensional brain space, we develop mean-shift edge bundling, which reveals the multitude of connections as derived from correlations in the brain activity of cortical regions.

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Crossref · 10.1109/tvcg.2013.114

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3 of 3 references verified0 citation errors · 0 not checkable

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  • Techniques borrowed from other complex network displays, such as hierarchical edge bundling, can be used to clarify the display of heavily connected graphs, with the caveat that this risks interpreting edges in brain networks as actual white matter tracts.

    “Techniques borrowed from other complex network displays, such as hierarchical edge bundling,17 can be used to clarify the display of such information, although with the caveat that this can risk interpreting edges in brain networks as actual white matter tracts (c).”

    From Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery (2016) · cites this paper as [17]

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Research works printed but not linked: 54

  1. 10.1038/jcbfm.1993.4 · DOI
  2. 10.1002/mrm.1910340409 · DOI · Paper page
  3. 10.1038/nrn2201 · DOI · Paper page
  4. 10.1038/361109a0 · DOI
  5. 10.1016/S0720-048X(02)00328-5 · DOI
  6. 10.1002/(SICI)1522-2594(199909)42:3<526::AID-MRM15>3.0.CO;2-J · DOI
  7. 10.1109/TVCG.2010.199 · DOI
  8. 10.1073/pnas.96.18.10422 · DOI · Paper page
  9. 10.1002/1531-8249(199902)45:2<265::AID-ANA21>3.0.CO;2-3 · DOI
  10. Wedeen, Diffusion Aniostropy and White Matter Tracts
  11. 10.1109/TVCG.2011.82 · DOI
  12. 10.1109/TVCG.2009.138 · DOI
  13. 10.1109/TVCG.2007.70602 · DOI
  14. Berres, Tractography in Context: Multimodal Visualization of Probabilistic Tractograms in Anatomical Context, 9
  15. 10.1117/12.843808 · DOI
  16. 10.1016/j.neuroimage.2013.04.111 · DOI
  17. 10.1016/j.neuroimage.2011.09.016 · DOI
  18. 10.1006/cbmr.1996.0014 · DOI · Paper page
  19. 10.1007/s00701-011-0985-6 · DOI
  20. van Dixhoorn, Visual Analysis of Integrated Resting State Functional Brain Connectivity and Anatomy, 57
  21. 10.1007/s10334-010-0228-5 · DOI
  22. 10.1098/rstb.2005.1637 · DOI
  23. 10.1080/00207450500505761 · DOI
  24. 10.1093/cercor/bhi016 · DOI
  25. 10.1523/JNEUROSCI.3874-05.2006 · DOI · Paper page
  26. 10.1111/j.1460-9568.2010.07279.x · DOI
  27. 10.1093/cercor/bhn059 · DOI · Paper page
  28. 10.1016/j.conb.2011.08.005 · DOI
  29. 10.1016/j.neuroimage.2012.12.054 · DOI
  30. 10.1109/TVCG.2006.147 · DOI
  31. McGonigle, Visualizing Functional Connectivity in fMRI Using Hierarchical Edge Bundles
  32. 10.1016/j.neuroimage.2012.01.107 · DOI
  33. 10.1109/APVIS.2007.329288 · DOI
  34. 10.1111/j.1467-8659.2009.01450.x · DOI
  35. 10.1111/j.1467-8659.2012.03079.x · DOI
  36. 10.1109/PACIFICVIS.2011.5742389 · DOI
  37. 10.1109/IV.2010.53 · DOI
  38. 10.1109/TVCG.2008.135 · DOI
  39. 10.1109/TVCG.2011.233 · DOI
  40. 10.1111/j.1467-8659.2009.01680.x · DOI
  41. 10.1073/pnas.0911855107 · DOI · Paper page
  42. 10.1016/j.neuron.2011.11.004 · DOI
  43. 10.1016/j.jneumeth.2011.09.031 · DOI
  44. 10.1152/jn.90777.2008 · DOI · Paper page
  45. 10.1016/j.neuroimage.2011.05.078 · DOI
  46. 10.1109/TIT.1975.1055330 · DOI
  47. 10.1006/nimg.1998.0395 · DOI · Paper page
  48. 10.1073/pnas.0905267106 · DOI · Paper page
  49. 10.1038/nn.3423 · DOI · Paper page
  50. 10.1016/j.acra.2009.02.001 · DOI
  51. 10.1227/01.NEU.0000350868.95634.CA · DOI
  52. 10.1006/nimg.1998.0396 · DOI · Paper page
  53. 10.1016/j.neuroimage.2005.01.042 · DOI
  54. 10.1523/JNEUROSCI.2259-13.2013 · DOI

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Metadata

Authors
Bottger, J., Schafer, A., Lohmann, G., Villringer, A., & Margulies, D. S.
Affiliations
Max Planck Institute for Human Cognitive and Brain Sciences (DE)
ORCID
Venue
IEEE Transactions on Visualization and Computer Graphics
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2014-03
Volume
20
Issue
3
Pages
471-480
ISSN
1077-2626 (ISSN-L)
DOI
10.1109/tvcg.2013.114
OpenAlex
W2122169399
Cited by
59
References
3
Citations by year
2026: 1 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 5 · 2020: 2 · 2019: 6 · 2018: 6 · 2017: 13 · 2016: 9 · 2015: 7 · 2014: 4
FWCI
7.88
Type
journal article
Language
en
Open access
closed
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations
  • IEEE Transactions on Visualization and Computer Graphics (publishedVersion)
  • PubMed (publishedVersion)
  • Max Planck Digital Library (submittedVersion)
  • MPG.PuRe (Max Planck Society) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Data Visualization and Analytics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
Keywords
functional connectivity, edge bundling, 3D visualization, whole-brain connectivity, cortical regions, network visualization
MeSH terms
Algorithms, Brain, Brain Mapping, Computer Graphics, Humans, Magnetic Resonance Imaging, Imaging, Three-Dimensional

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