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001031465 1001_ $$0P:(DE-HGF)0$$aKim, Sunghun$$b0
001031465 245__ $$aComparison of different group-level templates in gradient-based multimodal connectivity analysis
001031465 260__ $$aCambridge, MA$$bThe MIT Press$$c2024
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001031465 520__ $$aThe study of large-scale brain connectivity is increasingly adopting unsupervised approaches that derive low-dimensional spatial representations from high-dimensional connectomes, referred to as gradient analysis. When translating this approach to study interindividual variations in connectivity, one technical issue pertains to the selection of an appropriate group-level template to which individual gradients are aligned. Here, we compared different group-level template construction strategies using functional and structural connectome data from neurotypical controls and individuals with autism spectrum disorder (ASD) to identify between-group differences. We studied multimodal magnetic resonance imaging data obtained from the Autism Brain Imaging Data Exchange (ABIDE) Initiative II and the Human Connectome Project (HCP). We designed six template construction strategies that varied in whether (1) they included typical controls in addition to ASD; or (2) they mapped from one dataset onto another. We found that aligning a combined subject template of the ASD and control subjects from the ABIDE Initiative onto the HCP template exhibited the most pronounced effect size. This strategy showed robust identification of ASD-related brain regions for both functional and structural gradients across different study settings. Replicating the findings on focal epilepsy demonstrated the generalizability of our approach. Our findings will contribute to improving gradient-based connectivity research.
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001031465 7001_ $$0P:(DE-HGF)0$$aYoo, Seulki$$b1
001031465 7001_ $$0P:(DE-HGF)0$$aXie, Ke$$b2
001031465 7001_ $$0P:(DE-HGF)0$$aRoyer, Jessica$$b3
001031465 7001_ $$0P:(DE-HGF)0$$aLarivière, Sara$$b4
001031465 7001_ $$0P:(DE-HGF)0$$aByeon, Kyoungseob$$b5
001031465 7001_ $$0P:(DE-HGF)0$$aLee, Jong Eun$$b6
001031465 7001_ $$0P:(DE-HGF)0$$aPark, Yeongjun$$b7
001031465 7001_ $$0P:(DE-Juel1)173843$$aValk, Sofie L.$$b8$$ufzj
001031465 7001_ $$0P:(DE-HGF)0$$aBernhardt, Boris C.$$b9
001031465 7001_ $$0P:(DE-HGF)0$$aHong, Seok-Jun$$b10
001031465 7001_ $$0P:(DE-HGF)0$$aPark, Hyunjin$$b11$$eCorresponding author
001031465 7001_ $$0P:(DE-HGF)0$$aPark, Bo-yong$$b12$$eCorresponding author
001031465 773__ $$0PERI:(DE-600)2900481-0$$a10.1162/netn_a_00382$$gp. 1 - 23$$n4$$p1009–1031$$tNetwork neuroscience$$v8$$x2472-1751$$y2024
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001031465 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)173843$$aForschungszentrum Jülich$$b8$$kFZJ
001031465 9101_ $$0I:(DE-HGF)0$$6P:(DE-Juel1)173843$$a Max Planck Institute for Cognitive and Brain Sciences, Leipzig$$b8
001031465 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a  Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, Republic of Korea * Corresponding Authors: hyunjinp@skku.edu; boyongpark@korea.ac.kr$$b11
001031465 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea * Corresponding Authors: hyunjinp@skku.edu; boyongpark@korea.ac.kr$$b12
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