{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T13:09:39Z","timestamp":1792069779228,"version":"4.4.0"},"reference-count":77,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T00:00:00Z","timestamp":1750809600000},"content-version":"vor","delay-in-days":10,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1\u2010R01 MH117807\u201001A1"],"award-info":[{"award-number":["1\u2010R01 MH117807\u201001A1"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Human Brain Mapping"],"published-print":{"date-parts":[[2025,6,15]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Diffusion MRI\u2010based structural connectomes are increasingly used to investigate brain connectivity changes associated with various disorders. However, small sample sizes in individual studies, along with highly heterogeneous disorder\u2010related manifestations, underscore the need to pool datasets across multiple studies to be able to identify coherent and generalizable connectivity patterns linked to these disorders. Yet, combining datasets introduces site\u2010related differences due to variations in scanner hardware or acquisition protocols. These differences highlight the necessity for statistical data harmonization to mitigate site\u2010related effects on structural connectomes while preserving the biological information associated with participant demographics and the disorders. While several paradigms exist for harmonizing normally distributed neuroimaging measures, this paper represents the first effort to establish a harmonization framework specifically tailored for the structural connectome. We conduct a thorough investigation of various statistical harmonization methods, adapting them to accommodate the unique distributional characteristics and graph\u2010based properties of structural connectomes. Through rigorous evaluation, we show that our MATCH algorithm, based on the gamma\u2010distributed model, consistently outperforms existing approaches in modeling structural connectomes, enabling the effective removal of site\u2010related biases in both edge\u2010based and downstream graph analyses while preserving biological variability. Two real\u2010world applications further highlight the utility of our harmonization framework in addressing challenges in multi\u2010site structural connectome analysis. Specifically, harmonization with MATCH enhances the generalizability of connectome\u2010based machine learning predictors to new datasets and increases statistical power for detecting group\u2010level differences. Our work provides essential guidelines for harmonizing multi\u2010site structural connectomes, paving the way for more robust discoveries through collaborative research in the era of team science and big data.<\/jats:p>","DOI":"10.1002\/hbm.70256","type":"journal-article","created":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T00:48:21Z","timestamp":1750898901000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Big Data, Small Bias: Harmonizing Diffusion\n                    <scp>MRI<\/scp>\n                    \u2010Based Structural Connectomes to Mitigate Site\u2010Related Bias in Data Integration"],"prefix":"10.1002","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4404-9741","authenticated-orcid":false,"given":"Rui Sherry","family":"Shen","sequence":"first","affiliation":[{"name":"Department of Bioengineering University of Pennsylvania  Philadelphia Pennsylvania USA"},{"name":"Diffusion &amp; Connectomics in Precision Healthcare Research, Department of Radiology Perelman School of Medicine, University of Pennsylvania  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Drew","family":"Parker","sequence":"additional","affiliation":[{"name":"Diffusion &amp; Connectomics in Precision Healthcare Research, Department of Radiology Perelman School of Medicine, University of Pennsylvania  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew An","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Public Health Sciences Medical University of South Carolina  Charleston South Carolina USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin E.","family":"Yerys","sequence":"additional","affiliation":[{"name":"Center for Autism Research Children's Hospital of Philadelphia  Philadelphia Pennsylvania USA"},{"name":"Department of Child and Adolescent Psychiatry and Behavioral Science Children's Hospital of Philadelphia  Philadelphia Pennsylvania USA"},{"name":"Advancing Transition and Learning for Adult Success Center, Children's Hospital of Philadelphia  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Birkan","family":"Tun\u00e7","sequence":"additional","affiliation":[{"name":"Center for Autism Research Children's Hospital of Philadelphia  Philadelphia Pennsylvania USA"},{"name":"Department of Child and Adolescent Psychiatry and Behavioral Science Children's Hospital of Philadelphia  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy P. L.","family":"Roberts","sequence":"additional","affiliation":[{"name":"Program in Advanced Imaging Research, Department of Radiology Children's Hospital of Philadelphia  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Russell T.","family":"Shinohara","sequence":"additional","affiliation":[{"name":"Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics University of Pennsylvania  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ragini","family":"Verma","sequence":"additional","affiliation":[{"name":"Diffusion &amp; Connectomics in Precision Healthcare Research, Department of Radiology Perelman School of Medicine, University of Pennsylvania  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,6,25]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.10.045"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1053-8119(03)00336-7"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.10.019"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3501813"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2007.06.004"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-022-04554-y"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0135247"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.09.054"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrn3475"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhy032"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.25688"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2006.01.021"},{"key":"e_1_2_11_14_1","unstructured":"Dhollander T. 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