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. 2019 Feb 1;3(2):427–454. doi: 10.1162/netn_a_00071

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© 2018 Massachusetts Institute of Technology

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/legalcode.

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Figure 4. — Percentage of edges significantly related to motion after de-noising for the dispersion index. More effective de-noising pipelines reduced the relationship between dispersion and motion. Bars are ordered such that the least effective de-noising pipelines are on the left and the most effective are on the right. Panel A illustrates the results after correcting for multiple comparisons. Panel B depicts the results without controlling for multiple comparisons.