{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T22:48:26Z","timestamp":1790635706251,"version":"4.1.0"},"reference-count":61,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T00:00:00Z","timestamp":1748995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T00:00:00Z","timestamp":1748995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"the Fundamental Research Fund for the Chengdu University of Information Technology","award":["No. KYTZ2023043"],"award-info":[{"award-number":["No. KYTZ2023043"]}]},{"name":"Higher Education Teaching Research and Reform Fund","award":["No. JYJG2024165"],"award-info":[{"award-number":["No. JYJG2024165"]}]},{"name":"One-time funding for the FT-042 Postdoctoral Research Station","award":["XM25-10691"],"award-info":[{"award-number":["XM25-10691"]}]},{"name":"the Natural Science Foundation of Sichuan Province","award":["No. 2023NSFSC0482"],"award-info":[{"award-number":["No. 2023NSFSC0482"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Brain Imaging and Behavior"],"DOI":"10.1007\/s11682-025-01026-5","type":"journal-article","created":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T03:27:34Z","timestamp":1749007654000},"page":"978-990","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Combining functional, structural, and morphological networks for multimodal classification of developing autistic brains"],"prefix":"10.1007","volume":"19","author":[{"given":"Changchun","family":"He","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jesus M.","family":"Cortes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Ding","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolong","family":"Shan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maoyang","family":"Zou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heng","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huafu","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianmin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xujun","family":"Duan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,6,4]]},"reference":[{"issue":"10","key":"1026_CR1","doi-asserted-by":"publisher","first-page":"4034","DOI":"10.1093\/cercor\/bhv191","volume":"26","author":"AE Abbott","year":"2016","unstructured":"Abbott, A. E., Nair, A., Keown, C. L., Datko, M., Jahedi, A., Fishman, I., & Muller, R. (2016). Patterns of atypical functional connectivity and behavioral links in autism differ between default, salience, and executive networks. Cerebral Cortex, 26(10), 4034\u20134045.","journal-title":"Cerebral Cortex"},{"issue":"1","key":"1026_CR2","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.neuroimage.2006.08.032","volume":"34","author":"AL Alexander","year":"2007","unstructured":"Alexander, A. L., Lee, J. E., Lazar, M., Boudos, R., DuBray, M. B., Oakes, T. R., & McMahon, W. M. (2007). Diffusion tensor imaging of the corpus callosum in autism. Neuroimage, 34(1), 61\u201373.","journal-title":"Neuroimage"},{"issue":"11","key":"1026_CR3","doi-asserted-by":"publisher","first-page":"e28044","DOI":"10.1371\/journal.pone.0028044","volume":"6","author":"SH Ameis","year":"2011","unstructured":"Ameis, S. H., Fan, J., Rockel, C., Voineskos, A. N., Lobaugh, N. J., Soorya, L., & Anagnostou, E. (2011). Impaired structural connectivity of socio-emotional circuits in autism spectrum disorders: A diffusion tensor imaging study. Plos One, 6(11), e28044.","journal-title":"Plos One"},{"issue":"1","key":"1026_CR4","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.neuroimage.2007.07.007","volume":"38","author":"J Ashburner","year":"2007","unstructured":"Ashburner, J. (2007). A fast diffeomorphic image registration algorithm. Neuroimage, 38(1), 95\u2013113.","journal-title":"Neuroimage"},{"issue":"3","key":"1026_CR5","doi-asserted-by":"publisher","first-page":"839","DOI":"10.1016\/j.neuroimage.2005.02.018","volume":"26","author":"J Ashburner","year":"2005","unstructured":"Ashburner, J., & Friston, K. J. (2005). Unified segmentation. Neuroimage, 26(3), 839\u2013851.","journal-title":"Neuroimage"},{"issue":"1","key":"1026_CR6","first-page":"133","volume":"29","author":"Association American Psychiatric","year":"2013","unstructured":"Association American Psychiatric (2013). Diagnostic and statistical manual of mental disorders, 5th edition: DSM-5. Psychosomatics, 29(1), 133\u2013134.","journal-title":"Psychosomatics"},{"issue":"1","key":"1026_CR7","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/0010-0277(85)90022-8","volume":"21","author":"S Baron-Cohen","year":"1985","unstructured":"Baron-Cohen, S., Leslie, A. M., & Frith, U. (1985). Does the autistic child have a theory of Mind?? Cognition, 21(1), 37\u201346.","journal-title":"Cognition"},{"issue":"1","key":"1026_CR8","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.neuroimage.2007.04.060","volume":"37","author":"DB Bashat","year":"2007","unstructured":"Bashat, D. B., Kronfeld-Duenias, V., Zachor, D. A., Ekstein, P. M., Hendler, T., Tarrasch, R., & Sira, L. B. (2007). Accelerated maturation of white matter in young children with autism: A high B value DWI study. Neuroimage, 37(1), 40\u201347.","journal-title":"Neuroimage"},{"issue":"12","key":"1026_CR9","doi-asserted-by":"publisher","first-page":"4663","DOI":"10.1002\/hbm.24312","volume":"39","author":"P Bonifazi","year":"2018","unstructured":"Bonifazi, P., Erramuzpe, A., Diez, I., Gabilondo, I., Boisgontier, M. P., Pauwels, L., & Cortes, J. M. (2018). Structure\u2013function multi-scale connectomics reveals a major role of the fronto\u2010striato\u2010thalamic circuit in brain aging. Human Brain Mapping, 39(12), 4663\u20134677.","journal-title":"Human Brain Mapping"},{"issue":"3","key":"1026_CR10","doi-asserted-by":"publisher","first-page":"873","DOI":"10.1016\/j.neuroimage.2010.01.011","volume":"50","author":"Y Cheng","year":"2010","unstructured":"Cheng, Y., Chou, K. H., Chen, I. Y., Fan, Y. T., Decety, J., & Lin, C. P. (2010). Atypical development of white matter microstructure in adolescents with autism spectrum disorders. Neuroimage, 50(3), 873\u2013882.","journal-title":"Neuroimage"},{"issue":"2","key":"1026_CR11","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1109\/TCDS.2017.2680408","volume":"10","author":"BA Cociu","year":"2017","unstructured":"Cociu, B. A., Das, S., Billeci, L., Jamal, W., Maharatna, K., Calderoni, S., & Muratori, F. (2017). Multimodal functional and structural brain connectivity analysis in autism: A preliminary integrated approach with EEG, fMRI, and DTI. IEEE Transactions on Cognitive and Developmental Systems, 10(2), 213\u2013226.","journal-title":"IEEE Transactions on Cognitive and Developmental Systems"},{"issue":"3","key":"1026_CR12","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1001\/jama.290.3.337","volume":"290","author":"E Courchesne","year":"2003","unstructured":"Courchesne, E., Carper, R., & Akshoomoff, N. (2003). Evidence of brain overgrowth in the first year of life in autism. Jama, 290(3), 337\u2013344.","journal-title":"Jama"},{"issue":"2","key":"1026_CR13","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1016\/j.neuron.2007.10.016","volume":"56","author":"E Courchesne","year":"2007","unstructured":"Courchesne, E., Pierce, K., Schumann, C. M., Redcay, E., Buckwalter, J. A., Kennedy, D. P., & Morgan, J. (2007). Mapping early brain development in autism. Neuron, 56(2), 399\u2013413.","journal-title":"Neuron"},{"key":"1026_CR14","doi-asserted-by":"publisher","first-page":"1433","DOI":"10.1007\/s10803-013-2008-3","volume":"44","author":"N David","year":"2014","unstructured":"David, N., Schultz, J., Milne, E., Schunke, O., Sch\u00f6ttle, D., M\u00fcnchau, A., & Engel, A. K. (2014). Right temporoparietal Gray matter predicts accuracy of social perception in the autism spectrum. Journal of Autism and Developmental Disorders, 44, 1433\u20131446.","journal-title":"Journal of Autism and Developmental Disorders"},{"issue":"6","key":"1026_CR16","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1038\/mp.2013.78","volume":"19","author":"A Di Martino","year":"2014","unstructured":"Di Martino, A., Yan, C. G., Li, Q., Denio, E., Castellanos, F. X., Alaerts, K., & Dapretto, M. (2014). The autism brain imaging data exchange: Towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular Psychiatry, 19(6), 659\u2013667.","journal-title":"Molecular Psychiatry"},{"issue":"1","key":"1026_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/sdata.2017.10","volume":"4","author":"A Di Martino","year":"2017","unstructured":"Di Martino, A., O\u2019connor, D., Chen, B., Alaerts, K., Anderson, J. S., Assaf, M., & Bernaerts, S. (2017). Enhancing studies of the connectome in autism using the autism brain imaging data exchange II. Scientific Data, 4(1), 1\u201315.","journal-title":"Scientific Data"},{"issue":"519","key":"1026_CR17","doi-asserted-by":"publisher","first-page":"1211","DOI":"10.1080\/01621459.2016.1202117","volume":"112","author":"CJ DiCiccio","year":"2017","unstructured":"DiCiccio, C. J., & Romano, J. P. (2017). Robust permutation tests for correlation and regression coefficients. Journal of the American Statistical Association, 112(519), 1211\u20131220.","journal-title":"Journal of the American Statistical Association"},{"issue":"1","key":"1026_CR18","doi-asserted-by":"publisher","first-page":"10532","DOI":"10.1038\/srep10532","volume":"5","author":"I Diez","year":"2015","unstructured":"Diez, I., Bonifazi, P., Escudero, I., Mateos, B., Mu\u00f1oz, M. A., Stramaglia, S., & Cortes, J. M. (2015). A novel brain partition highlights the modular skeleton shared by structure and function. Scientific Reports, 5(1), 10532.","journal-title":"Scientific Reports"},{"issue":"5","key":"1026_CR19","doi-asserted-by":"publisher","first-page":"3271","DOI":"10.1093\/cercor\/bhz308","volume":"30","author":"G Dumas","year":"2020","unstructured":"Dumas, G., Moreau, Q., Tognoli, E., & Kelso, J. S. (2020). The human dynamic clamp reveals the fronto-parietal network linking real-time social coordination and cognition. Cerebral Cortex, 30(5), 3271\u20133285.","journal-title":"Cerebral Cortex"},{"key":"1026_CR20","doi-asserted-by":"crossref","unstructured":"ElNakieb, Y., Ali, M. T., Dekhil, O., Khalefa, M. E., Soliman, A., Shalaby, A., & Elmaghraby, A. (2018). Towards accurate personalized autism diagnosis using different imaging modalities: sMRI, fMRI, and DTI. Paper presented at the 2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).","DOI":"10.1109\/ISSPIT.2018.8642639"},{"key":"1026_CR21","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1016\/j.neuroimage.2013.05.054","volume":"80","author":"AC Evans","year":"2013","unstructured":"Evans, A. C. (2013). Networks of anatomical covariance. Neuroimage, 80, 489\u2013504.","journal-title":"Neuroimage"},{"issue":"6","key":"1026_CR22","doi-asserted-by":"publisher","first-page":"958","DOI":"10.1002\/ana.24533","volume":"78","author":"I Fishman","year":"2015","unstructured":"Fishman, I., Datko, M., Cabrera, Y., Carper, R. A., & M\u00fcller, R. A. (2015). Reduced integration and differentiation of the imitation network in autism: A combined functional connectivity magnetic resonance imaging and diffusion-weighted imaging study. Annals of Neurology, 78(6), 958\u2013969.","journal-title":"Annals of Neurology"},{"issue":"23","key":"1026_CR23","doi-asserted-by":"publisher","first-page":"2237","DOI":"10.1056\/NEJMra1706158","volume":"379","author":"MD Fox","year":"2018","unstructured":"Fox, M. D. (2018). Mapping symptoms to brain networks with the human connectome. New England Journal of Medicine, 379(23), 2237\u20132245.","journal-title":"New England Journal of Medicine"},{"issue":"3","key":"1026_CR25","doi-asserted-by":"publisher","first-page":"524","DOI":"10.1093\/cercor\/bhn102","volume":"19","author":"G Gong","year":"2009","unstructured":"Gong, G., He, Y., Concha, L., Lebel, C., Gross, D. W., Evans, A. C., & Beaulieu, C. (2009). Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. Cerebral Cortex, 19(3), 524\u2013536.","journal-title":"Cerebral Cortex"},{"issue":"2","key":"1026_CR24","doi-asserted-by":"publisher","first-page":"1239","DOI":"10.1016\/j.neuroimage.2011.08.017","volume":"59","author":"G Gong","year":"2012","unstructured":"Gong, G., He, Y., Chen, Z. J., & Evans, A. C. (2012). Convergence and divergence of thickness correlations with diffusion connections across the human cerebral cortex. Neuroimage, 59(2), 1239\u20131248.","journal-title":"Neuroimage"},{"key":"1026_CR26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-016-0028-x","volume":"7","author":"X Guo","year":"2017","unstructured":"Guo, X., Chen, H., Long, Z., Duan, X., Zhang, Y., & Chen, H. (2017). Atypical developmental trajectory of local spontaneous brain activity in autism spectrum disorder. Scientific Reports, 7, 1\u201310.","journal-title":"Scientific Reports"},{"key":"1026_CR27","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1023\/A:1012487302797","volume":"46","author":"I Guyon","year":"2002","unstructured":"Guyon, I., Weston, J., Barnhill, S., & Vapnik, V. (2002). Gene selection for cancer classification using support vector machines. Machine Learning, 46, 389\u2013422.","journal-title":"Machine Learning"},{"issue":"9","key":"1026_CR28","doi-asserted-by":"publisher","first-page":"5028","DOI":"10.1093\/cercor\/bhaa098","volume":"30","author":"C He","year":"2020","unstructured":"He, C., Chen, H., Uddin, L. Q., Erramuzpe, A., Bonifazi, P., Guo, X., & Li, L. (2020). Structure\u2013function connectomics reveals aberrant developmental trajectory occurring at preadolescence in the autistic brain. Cerebral Cortex, 30(9), 5028\u20135037.","journal-title":"Cerebral Cortex"},{"issue":"10","key":"1026_CR29","doi-asserted-by":"publisher","first-page":"3282","DOI":"10.1002\/hbm.25434","volume":"42","author":"C He","year":"2021","unstructured":"He, C., Cortes, J. M., Kang, X., Cao, J., Chen, H., Guo, X., & Xiao, J. (2021). Individual-based morphological brain network organization and its association with autistic symptoms in young children with autism spectrum disorder. Human Brain Mapping, 42(10), 3282\u20133294.","journal-title":"Human Brain Mapping"},{"issue":"15","key":"1026_CR30","doi-asserted-by":"publisher","first-page":"6169","DOI":"10.1073\/pnas.1219562110","volume":"110","author":"AM Hermundstad","year":"2013","unstructured":"Hermundstad, A. M., Bassett, D. S., Brown, K. S., Aminoff, E. M., Clewett, D., Freeman, S., & Miller, M. B. (2013). Structural foundations of resting-state and task-based functional connectivity in the human brain. Proceedings of the National Academy of Sciences, 110(15), 6169\u20136174.","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"1026_CR31","doi-asserted-by":"crossref","unstructured":"Honey, C. J., Sporns, O., Cammoun, L., Gigandet, X., Thiran, J. P., Meuli, R., & Hagmann, P. (2009). Predicting human resting-state functional connectivity from structural connectivity. Proceedings of the National Academy of Sciences, 106(6), 2035\u20132040.","DOI":"10.1073\/pnas.0811168106"},{"issue":"2","key":"1026_CR32","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1097\/WCO.0000000000000181","volume":"28","author":"SS Jeste","year":"2015","unstructured":"Jeste, S. S., Frohlich, J., & Loo, S. K. (2015). Electrophysiological biomarkers of diagnosis and outcome in neurodevelopmental disorders. Current Opinion in Neurology, 28(2), 110.","journal-title":"Current Opinion in Neurology"},{"issue":"1","key":"1026_CR33","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1097\/01.wnr.0000239965.21685.99","volume":"18","author":"TA Keller","year":"2007","unstructured":"Keller, T. A., Kana, R. K., & Just, M. A. (2007). A developmental study of the structural integrity of white matter in autism. Neuroreport, 18(1), 23\u201327.","journal-title":"Neuroreport"},{"key":"1026_CR35","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.jneumeth.2014.09.003","volume":"237","author":"X Kong","year":"2014","unstructured":"Kong, X., Wang, X., Huang, L., Pu, Y., Yang, Z., Dang, X., & Liu, J. (2014). Measuring individual morphological relationship of cortical regions. Journal of Neuroscience Methods, 237, 103\u2013107.","journal-title":"Journal of Neuroscience Methods"},{"key":"1026_CR34","doi-asserted-by":"crossref","unstructured":"Kong, X., Liu, Z., Huang, L., Wang, X., Yang, Z., Zhou, G., & Liu, J. (2015). Mapping individual brain networks using statistical similarity in regional morphology from MRI. Plos One, 10(11), e0141840.","DOI":"10.1371\/journal.pone.0141840"},{"key":"1026_CR36","doi-asserted-by":"crossref","unstructured":"Koyama, M. S., Martino, A. D., Kelly, C., Jutagir, D. R., Sunshine, J., Schwartz, S. J., & Milham, M. P. (2013). Cortical signatures of dyslexia And remediation: An intrinsic functional connectivity approach. Plos One, 8(2), e55454.","DOI":"10.1371\/journal.pone.0055454"},{"issue":"1","key":"1026_CR37","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1038\/s41398-019-0418-5","volume":"9","author":"HY Lin","year":"2019","unstructured":"Lin, H. Y., Perry, A., Cocchi, L., Roberts, J. A., Tseng, W. Y. I., Breakspear, M., & Gau, S. S. F. (2019). Development of frontoparietal connectivity predicts longitudinal symptom changes in young people with autism spectrum disorder. Translational Psychiatry, 9(1), 86.","journal-title":"Translational Psychiatry"},{"issue":"4","key":"1026_CR38","doi-asserted-by":"publisher","first-page":"984","DOI":"10.1002\/hbm.24854","volume":"41","author":"J Mu","year":"2020","unstructured":"Mu, J., Chen, T., Quan, S., Wang, C., Zhao, L., & Liu, J. (2020). Neuroimaging features of whole-brain functional connectivity predict attack frequency of migraine. Human Brain Mapping, 41(4), 984\u2013993.","journal-title":"Human Brain Mapping"},{"key":"1026_CR39","doi-asserted-by":"publisher","first-page":"732","DOI":"10.1016\/j.nicl.2015.02.024","volume":"7","author":"JS Nomi","year":"2015","unstructured":"Nomi, J. S., & Uddin, L. Q. (2015). Developmental changes in large-scale network connectivity in autism. NeuroImage: Clinical, 7, 732\u2013741.","journal-title":"NeuroImage: Clinical"},{"issue":"3","key":"1026_CR40","doi-asserted-by":"publisher","first-page":"2142","DOI":"10.1016\/j.neuroimage.2011.10.018","volume":"59","author":"JD Power","year":"2012","unstructured":"Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage, 59(3), 2142\u20132154.","journal-title":"Neuroimage"},{"key":"1026_CR41","doi-asserted-by":"publisher","first-page":"102181","DOI":"10.1016\/j.nicl.2020.102181","volume":"25","author":"M Raki\u0107","year":"2020","unstructured":"Raki\u0107, M., Cabezas, M., Kushibar, K., Oliver, A., & Llad\u00f3, X. (2020). Improving the detection of autism spectrum disorder by combining structural and functional MRI information. NeuroImage: Clinical, 25, 102181.","journal-title":"NeuroImage: Clinical"},{"key":"1026_CR42","doi-asserted-by":"crossref","unstructured":"Rasero, J., Jimenez-Marin, A., Diez, I., Toro, R., Hasan, M. T., & Cortes, J. M. (2023). The Neurogenetics of Functional Connectivity Alterations in Autism: Insights From Subtyping in 657 Individuals. Biological Psychiatry.","DOI":"10.1016\/j.biopsych.2023.04.014"},{"key":"1026_CR43","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1016\/j.neuroimage.2015.10.057","volume":"125","author":"AT Reid","year":"2016","unstructured":"Reid, A. T., Lewis, J., Bezgin, G., Khundrakpam, B., Eickhoff, S. B., McIntosh, A. R., & Evans, A. C. (2016). A cross-modal, cross-species comparison of connectivity measures in the primate brain. Neuroimage, 125, 311\u2013331.","journal-title":"Neuroimage"},{"key":"1026_CR44","doi-asserted-by":"crossref","unstructured":"Roland, J. L., Snyder, A. Z., Hacker, C. D., Mitra, A., Shimony, J. S., Limbrick, D. D., & Leuthardt, E. C. (2017). On the role of the corpus callosum in interhemispheric functional connectivity in humans. Proceedings of the National Academy of Sciences, 114(50), 13278\u201313283.","DOI":"10.1073\/pnas.1707050114"},{"key":"1026_CR46","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2202-13-99","volume":"13","author":"W Sato","year":"2012","unstructured":"Sato, W., Toichi, M., Uono, S., & Kochiyama, T. (2012). Impaired social brain network for processing dynamic facial expressions in autism spectrum disorders. Bmc Neuroscience, 13, 1\u201317.","journal-title":"Bmc Neuroscience"},{"key":"1026_CR45","doi-asserted-by":"publisher","first-page":"395","DOI":"10.3389\/fnhum.2017.00395","volume":"11","author":"W Sato","year":"2017","unstructured":"Sato, W., Kochiyama, T., Uono, S., Yoshimura, S., Kubota, Y., Sawada, R., & Toichi, M. (2017). Reduced Gray matter volume in the social brain network in adults with autism spectrum disorder. Frontiers in Human Neuroscience, 11, 395.","journal-title":"Frontiers in Human Neuroscience"},{"issue":"3","key":"1026_CR47","doi-asserted-by":"publisher","first-page":"1622","DOI":"10.1016\/j.neuroimage.2012.05.026","volume":"62","author":"F Shi","year":"2012","unstructured":"Shi, F., Yap, P. T., Gao, W., Lin, W., Gilmore, J. H., & Shen, D. (2012). Altered structural connectivity in neonates at genetic risk for schizophrenia: A combined study using morphological and white matter networks. Neuroimage, 62(3), 1622\u20131633.","journal-title":"Neuroimage"},{"issue":"4","key":"1026_CR48","doi-asserted-by":"publisher","first-page":"253","DOI":"10.4258\/hir.2010.16.4.253","volume":"16","author":"YJ Son","year":"2010","unstructured":"Son, Y. J., Kim, H. G., Kim, E. H., Choi, S., & Lee, S. K. (2010). Application of support vector machine for prediction of medication adherence in heart failure patients. Healthcare Informatics Research, 16(4), 253\u2013259.","journal-title":"Healthcare Informatics Research"},{"key":"1026_CR49","doi-asserted-by":"crossref","unstructured":"Spisak, T., Jakab, A., Kis, S. A., Opposits, G., Aranyi, C., Berenyi, E., & Emri, M. (2014). Voxel-wise motion artifacts in population-level whole-brain connectivity analysis of resting-state FMRI. Plos One, 9(9), e104947.","DOI":"10.1371\/journal.pone.0104947"},{"issue":"1","key":"1026_CR50","first-page":"15","volume":"1","author":"AA Spurgin","year":"2007","unstructured":"Spurgin, A. A. (2007). Diffusion tensor imaging in children and adolescents: A technology review. Stanford J Neurosci, 1(1), 15\u201317.","journal-title":"Stanford J Neurosci"},{"issue":"3","key":"1026_CR51","doi-asserted-by":"publisher","first-page":"738","DOI":"10.1016\/j.celrep.2013.10.001","volume":"5","author":"K Supekar","year":"2013","unstructured":"Supekar, K., Uddin, L. Q., Khouzam, A., Phillips, J., Gaillard, W. D., Kenworthy, L. E., & Menon, V. (2013). Brain hyperconnectivity in children with autism and its links to social deficits. Cell Reports, 5(3), 738\u2013747.","journal-title":"Cell Reports"},{"issue":"1","key":"1026_CR52","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1016\/j.neuroimage.2004.05.007","volume":"23","author":"J Tohka","year":"2004","unstructured":"Tohka, J., Zijdenbos, A., & Evans, A. (2004). Fast and robust parameter Estimation for statistical partial volume models in brain MRI. Neuroimage, 23(1), 84\u201397.","journal-title":"Neuroimage"},{"issue":"1","key":"1026_CR53","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1006\/nimg.2001.0978","volume":"15","author":"N Tzourio-Mazoyer","year":"2002","unstructured":"Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., & Joliot, M. (2002). Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage, 15(1), 273\u2013289.","journal-title":"Neuroimage"},{"key":"1026_CR54","doi-asserted-by":"publisher","first-page":"458","DOI":"10.3389\/fnhum.2013.00458","volume":"7","author":"LQ Uddin","year":"2013","unstructured":"Uddin, L. Q., Supekar, K., & Menon, V. (2013). Reconceptualizing functional brain connectivity in autism from a developmental perspective. Frontiers in Human Neuroscience, 7, 458.","journal-title":"Frontiers in Human Neuroscience"},{"key":"1026_CR56","unstructured":"Wang, R., Benner, T., Sorensen, A. G., & Wedeen, V. J. (2007). Diffusion toolkit: a software package for diffusion imaging data processing and tractography. Paper presented at the Proc Intl Soc Mag Reson Med."},{"key":"1026_CR55","doi-asserted-by":"crossref","unstructured":"Wang, H., Jin, X., Zhang, Y., & Wang, J. (2016). Single-subject morphological brain networks: Connectivity mapping, topological characterization and test\u2013retest reliability. Brain and Behavior, 6(4), e00448.","DOI":"10.1002\/brb3.448"},{"issue":"11","key":"1026_CR57","doi-asserted-by":"publisher","first-page":"e112411","DOI":"10.1371\/journal.pone.0112411","volume":"9","author":"H Yamada","year":"2014","unstructured":"Yamada, H., Abe, O., Shizukuishi, T., Kikuta, J., Shinozaki, T., Dezawa, K., & Imamura, Y. (2014). Efficacy of distortion correction on diffusion imaging: Comparison of FSL eddy and eddy_correct using 30 and 60 directions diffusion encoding. Plos One, 9(11), e112411.","journal-title":"Plos One"},{"key":"1026_CR58","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1007\/s12021-016-9299-4","volume":"14","author":"CG Yan","year":"2016","unstructured":"Yan, C. G., Wang, X. D., Zuo, X. N., & Zang, Y. F. (2016). DPABI: Data processing & analysis for (resting-state) brain imaging. Neuroinformatics, 14, 339\u2013351.","journal-title":"Neuroinformatics"},{"issue":"2","key":"1026_CR59","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.jaac.2015.11.011","volume":"55","author":"YN Yoncheva","year":"2016","unstructured":"Yoncheva, Y. N., Somandepalli, K., Reiss, P. T., Kelly, C., Di Martino, A., Lazar, M., & Castellanos, F. X. (2016). Mode of anisotropy reveals global diffusion alterations in attention-deficit\/hyperactivity disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 55(2), 137\u2013145.","journal-title":"Journal of the American Academy of Child & Adolescent Psychiatry"},{"issue":"10","key":"1026_CR60","doi-asserted-by":"publisher","first-page":"2912","DOI":"10.1093\/brain\/awr223","volume":"134","author":"Z Zhang","year":"2011","unstructured":"Zhang, Z., Liao, W., Chen, H., Mantini, D., Ding, J. R., Xu, Q., & Jiao, Q. (2011). Altered functional\u2013structural coupling of large-scale brain networks in idiopathic generalized epilepsy. Brain, 134(10), 2912\u20132928.","journal-title":"Brain"},{"issue":"2","key":"1026_CR61","first-page":"422","volume":"46","author":"W Zhao","year":"2020","unstructured":"Zhao, W., Guo, S., Linli, Z., Yang, A. C., Lin, C. P., & Tsai, S. J. (2020). Functional, anatomical, and morphological networks highlight the role of basal ganglia\u2013thalamus\u2013cortex circuits in schizophrenia. Schizophrenia Bulletin, 46(2), 422\u2013431.","journal-title":"Schizophrenia Bulletin"}],"container-title":["Brain Imaging and Behavior"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11682-025-01026-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11682-025-01026-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11682-025-01026-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T10:04:41Z","timestamp":1760349881000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11682-025-01026-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,4]]},"references-count":61,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2025,10]]}},"alternative-id":["1026"],"URL":"https:\/\/doi.org\/10.1007\/s11682-025-01026-5","relation":{},"ISSN":["1931-7565"],"issn-type":[{"value":"1931-7565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,4]]},"assertion":[{"value":"17 May 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 June 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study was approved by the institutional review boards of the New York University and the San Diego State University Institutional Review Boards.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}