{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T14:27:50Z","timestamp":1758810470358,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031164309"},{"type":"electronic","value":"9783031164316"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-16431-6_34","type":"book-chapter","created":{"date-parts":[[2022,9,14]],"date-time":"2022-09-14T21:02:58Z","timestamp":1663189378000},"page":"356-365","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Explainable Contrastive Multiview Graph Representation of\u00a0Brain, Mind, and\u00a0Behavior"],"prefix":"10.1007","author":[{"given":"Chongyue","family":"Zhao","sequence":"first","affiliation":[]},{"given":"Liang","family":"Zhan","sequence":"additional","affiliation":[]},{"given":"Paul M.","family":"Thompson","sequence":"additional","affiliation":[]},{"given":"Heng","family":"Huang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,9,15]]},"reference":[{"issue":"3","key":"34_CR1","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1038\/nn.4502","volume":"20","author":"DS Bassett","year":"2017","unstructured":"Bassett, D.S., Sporns, O.: Network neuroscience. Nat. Neurosci. 20(3), 353\u2013364 (2017)","journal-title":"Nat. Neurosci."},{"issue":"3","key":"34_CR2","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1038\/nrn2575","volume":"10","author":"E Bullmore","year":"2009","unstructured":"Bullmore, E., Sporns, O.: Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10(3), 186\u2013198 (2009)","journal-title":"Nat. Rev. Neurosci."},{"issue":"2","key":"34_CR3","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/S0959-4388(00)00197-5","volume":"11","author":"AM Dale","year":"2001","unstructured":"Dale, A.M., Halgren, E.: Spatiotemporal mapping of brain activity by integration of multiple imaging modalities. Curr. Opin. Neurobiol. 11(2), 202\u2013208 (2001)","journal-title":"Curr. Opin. Neurobiol."},{"key":"34_CR4","doi-asserted-by":"publisher","first-page":"426","DOI":"10.1016\/j.neuroimage.2013.04.087","volume":"80","author":"A Fornito","year":"2013","unstructured":"Fornito, A., Zalesky, A., Breakspear, M.: Graph analysis of the human connectome: promise, progress, and pitfalls. Neuroimage 80, 426\u2013444 (2013)","journal-title":"Neuroimage"},{"issue":"4","key":"34_CR5","doi-asserted-by":"publisher","first-page":"1273","DOI":"10.1016\/S1053-8119(03)00202-7","volume":"19","author":"KJ Friston","year":"2003","unstructured":"Friston, K.J., Harrison, L., Penny, W.: Dynamic causal modelling. Neuroimage 19(4), 1273\u20131302 (2003)","journal-title":"Neuroimage"},{"key":"34_CR6","doi-asserted-by":"publisher","unstructured":"Gadgil, S., Zhao, Q., Pfefferbaum, A., Sullivan, E.V., Adeli, E., Pohl, K.M.: Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis. In: Martel, A.L., et al. (eds.) MICCAI 2020. LNCS, vol. 12267, pp. 528\u2013538. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-59728-3_52","DOI":"10.1007\/978-3-030-59728-3_52"},{"issue":"7615","key":"34_CR7","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1038\/nature18933","volume":"536","author":"MF Glasser","year":"2016","unstructured":"Glasser, M.F., Coalson, T.S., Robinson, E.C., Hacker, C.D., Harwell, J., Yacoub, E., Ugurbil, K., Andersson, J., Beckmann, C.F., Jenkinson, M., et al.: A multi-modal parcellation of human cerebral cortex. Nature 536(7615), 171\u2013178 (2016)","journal-title":"Nature"},{"key":"34_CR8","doi-asserted-by":"crossref","unstructured":"Glasser, M.F., et al.: The minimal preprocessing pipelines for the human connectome project. Neuroimage 80, 105\u2013124 (2013)","DOI":"10.1016\/j.neuroimage.2013.04.127"},{"issue":"7","key":"34_CR9","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pbio.0060159","volume":"6","author":"P Hagmann","year":"2008","unstructured":"Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C.J., Wedeen, V.J., Sporns, O.: Mapping the structural core of human cerebral cortex. PLoS Biol. 6(7), e159 (2008)","journal-title":"PLoS Biol."},{"key":"34_CR10","doi-asserted-by":"crossref","unstructured":"Honey, C.J., et al.: Predicting human resting-state functional connectivity from structural connectivity. Proc. Natl. Acad. Sci. 106(6), 2035\u20132040 (2009)","DOI":"10.1073\/pnas.0811168106"},{"key":"34_CR11","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.neuroimage.2013.05.114","volume":"102","author":"J Jorge","year":"2014","unstructured":"Jorge, J., Van der Zwaag, W., Figueiredo, P.: EEG-fMRI integration for the study of human brain function. Neuroimage 102, 24\u201334 (2014)","journal-title":"Neuroimage"},{"key":"34_CR12","doi-asserted-by":"publisher","unstructured":"Kazi, A., et al.: InceptionGCN: receptive field aware graph convolutional network for disease prediction. In: Chung, A.C.S., Gee, J.C., Yushkevich, P.A., Bao, S. (eds.) IPMI 2019. LNCS, vol. 11492, pp. 73\u201385. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-20351-1_6","DOI":"10.1007\/978-3-030-20351-1_6"},{"key":"34_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"320","DOI":"10.1007\/978-3-030-00931-1_37","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2018","author":"H Li","year":"2018","unstructured":"Li, H., Fan, Y.: Brain decoding from functional MRI using long short-term memory recurrent neural networks. In: Frangi, A.F., Schnabel, J.A., Davatzikos, C., Alberola-L\u00f3pez, C., Fichtinger, G. (eds.) MICCAI 2018. LNCS, vol. 11072, pp. 320\u2013328. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-00931-1_37"},{"key":"34_CR14","doi-asserted-by":"publisher","unstructured":"Li, X., Dvornek, N.C., Zhou, Y., Zhuang, J., Ventola, P., Duncan, J.S.: Graph neural network for interpreting task-fMRI biomarkers. In: Shen, D., et al. (eds.) MICCAI 2019. LNCS, vol. 11768, pp. 485\u2013493. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-32254-0_54","DOI":"10.1007\/978-3-030-32254-0_54"},{"key":"34_CR15","doi-asserted-by":"crossref","unstructured":"Margulies, D.S., et al.: Situating the default-mode network along a principal gradient of macroscale cortical organization. Proc. Natl. Acad. Sci. 113(44), 12574\u201312579 (2016)","DOI":"10.1073\/pnas.1608282113"},{"issue":"1","key":"34_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41467-019-12765-7","volume":"10","author":"MG Preti","year":"2019","unstructured":"Preti, M.G., Van De Ville, D.: Decoupling of brain function from structure reveals regional behavioral specialization in humans. Nat. Commun. 10(1), 1\u20137 (2019)","journal-title":"Nat. Commun."},{"issue":"4","key":"34_CR17","doi-asserted-by":"publisher","first-page":"1628","DOI":"10.1016\/j.neuroimage.2009.05.096","volume":"47","author":"KE Stephan","year":"2009","unstructured":"Stephan, K.E., Tittgemeyer, M., Kn\u00f6sche, T.R., Moran, R.J., Friston, K.J.: Tractography-based priors for dynamic causal models. Neuroimage 47(4), 1628\u20131638 (2009)","journal-title":"Neuroimage"},{"key":"34_CR18","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1016\/j.neubiorev.2019.04.018","volume":"102","author":"BM Turner","year":"2019","unstructured":"Turner, B.M., Palestro, J.J., Mileti\u0107, S., Forstmann, B.U.: Advances in techniques for imposing reciprocity in brain-behavior relations. Neurosci. Biobehav. Rev. 102, 327\u2013336 (2019)","journal-title":"Neurosci. Biobehav. Rev."},{"key":"34_CR19","doi-asserted-by":"crossref","unstructured":"Yan, Y., Zhu, J., Duda, M., Solarz, E., Sripada, C., Koutra, D.: GroupINN: grouping-based interpretable neural network for classification of limited, noisy brain data. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 772\u2013782 (2019)","DOI":"10.1145\/3292500.3330921"},{"key":"34_CR20","doi-asserted-by":"crossref","unstructured":"Yu, B., Yin, H., Zhu, Z.: Spatio-temporal graph convolutional networks: a deep learning framework for traffic forecasting. arXiv preprint arXiv:1709.04875 (2017)","DOI":"10.24963\/ijcai.2018\/505"},{"issue":"6","key":"34_CR21","doi-asserted-by":"publisher","first-page":"3358","DOI":"10.1109\/TGRS.2018.2798663","volume":"56","author":"C Zhao","year":"2018","unstructured":"Zhao, C., Gao, X., Emery, W.J., Wang, Y., Li, J.: An integrated spatio-spectral-temporal sparse representation method for fusing remote-sensing images with different resolutions. IEEE Trans. Geosci. Remote Sens. 56(6), 3358\u20133370 (2018)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"34_CR22","doi-asserted-by":"publisher","unstructured":"Zhao, C., Li, H., Jiao, Z., Du, T., Fan, Y.: A 3D convolutional encapsulated long short-term memory (3DConv-LSTM) model for denoising fMRI data. In: Martel, A.L., et al. (eds.) MICCAI 2020. LNCS, vol. 12267, pp. 479\u2013488. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-59728-3_47","DOI":"10.1007\/978-3-030-59728-3_47"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-16431-6_34","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T20:15:35Z","timestamp":1710360935000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-16431-6_34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031164309","9783031164316"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-16431-6_34","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"15 September 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Singapore","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Singapore","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft Conference","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1831","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"574","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"31% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}