NetBat: A network-driven harmonization method for structural connectivity

As the practice of aggregating multi-site neuroimaging data has become more common, the field of neuroscience has increasingly recognized the importance of harmonization , or the removal of scanner effects from brain imaging data. While many harmonization methods exist, like ComBat and CovBat, few e...

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Main Authors: Gustav R. Sjobeck, Mahbaneh Eshaghzadeh Torbati, Davneet S. Minhas, Charles S. DeCarli, James D. Wilson, Dana L. Tudorascu
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:NeuroImage
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Online Access:http://www.sciencedirect.com/science/article/pii/S1053811925003209
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author Gustav R. Sjobeck
Mahbaneh Eshaghzadeh Torbati
Davneet S. Minhas
Charles S. DeCarli
James D. Wilson
Dana L. Tudorascu
author_facet Gustav R. Sjobeck
Mahbaneh Eshaghzadeh Torbati
Davneet S. Minhas
Charles S. DeCarli
James D. Wilson
Dana L. Tudorascu
author_sort Gustav R. Sjobeck
collection DOAJ
description As the practice of aggregating multi-site neuroimaging data has become more common, the field of neuroscience has increasingly recognized the importance of harmonization , or the removal of scanner effects from brain imaging data. While many harmonization methods exist, like ComBat and CovBat, few explicitly incorporate the network structure of the brain. Researchers studying structural connectivity are therefore not guaranteed to model the true underlying brain network. This study offers a new harmonization method, called NetBat, which was designed to incorporate network parameters from the weighted stochastic block model (WSBM) as covariates in the popular ComBat harmonization method. NetBat is demonstrated through analysis of eighteen neurotypical individuals each scanned on four MRI scanners. Results suggest that under tested circumstances NetBat provides more accurate overall harmonization and better retention of network structure than competing methods.
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institution Kabale University
issn 1095-9572
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publishDate 2025-08-01
publisher Elsevier
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series NeuroImage
spelling doaj-art-33a33d1f0a294ecbb0088294ba7f38ce2025-08-20T03:29:31ZengElsevierNeuroImage1095-95722025-08-0131712131710.1016/j.neuroimage.2025.121317NetBat: A network-driven harmonization method for structural connectivityGustav R. Sjobeck0Mahbaneh Eshaghzadeh Torbati1Davneet S. Minhas2Charles S. DeCarli3James D. Wilson4Dana L. Tudorascu5University of Pittsburgh, Department of Psychiatry, United States of America; Correspondence to: Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, United States of America.University of Pittsburgh, Department of Psychiatry, United States of AmericaUniversity of Pittsburgh, Department of Psychiatry, United States of AmericaUniversity of California, Davis, Department of Neurology, United States of AmericaUniversity of San Francisco, Department of Mathematics and Statistics, United States of AmericaUniversity of Pittsburgh, Department of Psychiatry, United States of AmericaAs the practice of aggregating multi-site neuroimaging data has become more common, the field of neuroscience has increasingly recognized the importance of harmonization , or the removal of scanner effects from brain imaging data. While many harmonization methods exist, like ComBat and CovBat, few explicitly incorporate the network structure of the brain. Researchers studying structural connectivity are therefore not guaranteed to model the true underlying brain network. This study offers a new harmonization method, called NetBat, which was designed to incorporate network parameters from the weighted stochastic block model (WSBM) as covariates in the popular ComBat harmonization method. NetBat is demonstrated through analysis of eighteen neurotypical individuals each scanned on four MRI scanners. Results suggest that under tested circumstances NetBat provides more accurate overall harmonization and better retention of network structure than competing methods.http://www.sciencedirect.com/science/article/pii/S1053811925003209Network harmonizationStructural connectivityMulti-scan studies
spellingShingle Gustav R. Sjobeck
Mahbaneh Eshaghzadeh Torbati
Davneet S. Minhas
Charles S. DeCarli
James D. Wilson
Dana L. Tudorascu
NetBat: A network-driven harmonization method for structural connectivity
NeuroImage
Network harmonization
Structural connectivity
Multi-scan studies
title NetBat: A network-driven harmonization method for structural connectivity
title_full NetBat: A network-driven harmonization method for structural connectivity
title_fullStr NetBat: A network-driven harmonization method for structural connectivity
title_full_unstemmed NetBat: A network-driven harmonization method for structural connectivity
title_short NetBat: A network-driven harmonization method for structural connectivity
title_sort netbat a network driven harmonization method for structural connectivity
topic Network harmonization
Structural connectivity
Multi-scan studies
url http://www.sciencedirect.com/science/article/pii/S1053811925003209
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