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We demonstrate the utility of using the distribution of connectivity on a study of resting\u2010state functional magnetic resonance imaging association with an intervention. The method uses the estimated density of connectivity between nodes of interest as a functional covariate. Moreover, we demonstrate the utility of the procedure in an instance where connectivity is naturally considered an outcome by reversing the predictor\/response relationship using case\/control methodology. The method utilizes the density quantile, the density evaluated at empirical quantiles, instead of the empirical density directly. This improved the performance of the method by highlighting tail behavior, though we emphasize that by being flexible and non\u2010parametric, the technique can detect effects related to the central portion of the density. To demonstrate the method in an application, we consider 47 primary progressive aphasia patients with various levels of language abilities. These patients were randomly assigned to two treatment arms, transcranial direct\u2010current stimulation and language therapy versus sham (language therapy only), in a clinical trial. We use the method to analyze the effect of direct stimulation on functional connectivity. As such, we estimate the density of correlations among the regions of interest and study the difference in the density post\u2010intervention between treatment arms. We discover that it is the tail of the density, rather than the mean or lower order moments of the distribution, that demonstrates a significant impact in the classification. The new approach has several benefits. Among them, it drastically reduces the number of multiple comparisons compared with edge\u2010wise analysis. In addition, it allows for the investigation of the impact of functional connectivity on the outcomes where the connectivity is not geometrically localized.<\/jats:p>","DOI":"10.1002\/hbm.26112","type":"journal-article","created":{"date-parts":[[2022,11,13]],"date-time":"2022-11-13T12:00:25Z","timestamp":1668340825000},"page":"170-185","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Differences in functional connectivity distribution after transcranial direct\u2010current stimulation: A connectivity density point of view"],"prefix":"10.1002","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9322-4438","authenticated-orcid":false,"given":"Bohao","family":"Tang","sequence":"first","affiliation":[{"name":"Department of Biostatistics Johns Hopkins University  Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4766-5934","authenticated-orcid":false,"given":"Yi","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Health Data Science Indiana University School of Medicine  Indianapolis Indiana USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2653-5591","authenticated-orcid":false,"given":"Archana","family":"Venkataraman","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering Johns Hopkins University  Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6020-5532","authenticated-orcid":false,"given":"Kyrana","family":"Tsapkini","sequence":"additional","affiliation":[{"name":"Department of Neurology Johns Hopkins Medicine  Baltimore Maryland USA"},{"name":"Department of Cognitive Science Johns Hopkins Medicine  Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2289-0828","authenticated-orcid":false,"given":"Martin A.","family":"Lindquist","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Johns Hopkins University  Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"James","family":"Pekar","sequence":"additional","affiliation":[{"name":"F.M. Kirby Research Center for Functional Brain Imaging Kennedy Krieger Institute  Baltimore Maryland USA"},{"name":"Department of Radiology and Radiological Science Johns Hopkins University Medicine  Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0793-9497","authenticated-orcid":false,"given":"Brian","family":"Caffo","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Johns Hopkins University  Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,11,13]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2015.00175"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.04.042"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1995.tb02031.x"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1996.10476660"},{"key":"e_1_2_8_6_1","first-page":"330","article-title":"Remarques sur le si\u00e8ge de la facult\u00e9 du langage articul\u00e9, suivies d'une observation d'aph\u00e9mie (perte de la parole)","volume":"6","author":"Broca P.","year":"1861","journal-title":"Bulletin et Memoires de la Societe Anatomique de Paris"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrn2575"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.1048"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2013.00151"},{"key":"e_1_2_8_10_1","first-page":"1","article-title":"Wasserstein regression","author":"Chen Y.","year":"2021","journal-title":"Journal of the American Statistical Association"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00429-009-0208-6"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1089\/brain.2011.0043"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1214\/15-STS527"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1214\/08-AOAS206"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10114-005-0678-2"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.03.078"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2018.05.023"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/0165-0173(85)90023-2"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1089\/brain.2011.0008"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinph.2005.12.003"},{"key":"e_1_2_8_21_1","volume-title":"Stochastic finite elements: A spectral approach","author":"Ghanem R. 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