@inproceedings{37a28f76215d47bd9e078d6223582374,
title = "Graph Modularity and Randomness Measures: A Comparative Study",
abstract = "The human brain connectome exhibits a specific structure diagram that is understood to not be wired for randomness. However, aberrant connectivity has been detected and moreover linked to multiple neuropsychiatric and neurological diseases. Graph theory has provided a set of methods to evaluate disruption of brain structure organization. An alternative approach evaluates the difference between brain connectivity matrices and random matrices aiming at assessing randomness. This work compares both approaches within the context of random connectivity. Results indicate the correlation between the two assessments depends on the degree and can be as high as 0.3. Consequently, the two concepts can be treated as complementary, but addressing different aspects of randomness.",
keywords = "fMRI, functional connectivity, graph theory, modularity, random matrix theory",
author = "Vergara, {Victor M.} and Qingbao Yu and Calhoun, {Vince D.}",
note = "Funding Information: ACKNOWLEDGMENT This work was supported by NIH grants 2R01EB005846, P20GM103472, and R01REB020407 – and NSF grant 1539067 to VDC. The author(s) declare that there was no other financial support or compensation that can be perceived as constituting a potential conflict of interest. Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2018 ; Conference date: 08-04-2018 Through 10-04-2018",
year = "2018",
month = sep,
day = "21",
doi = "10.1109/SSIAI.2018.8470322",
language = "English (US)",
series = "Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "33--36",
booktitle = "2018 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2018 - Proceedings",
}