{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T15:05:01Z","timestamp":1758812701920,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031164514"},{"type":"electronic","value":"9783031164521"}],"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.springernature.com\/gp\/researchers\/text-and-data-mining"},{"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.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-16452-1_27","type":"book-chapter","created":{"date-parts":[[2022,9,15]],"date-time":"2022-09-15T21:25:46Z","timestamp":1663277146000},"page":"276-285","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Analyzing Brain Structural Connectivity as\u00a0Continuous Random Functions"],"prefix":"10.1007","author":[{"given":"William","family":"Consagra","sequence":"first","affiliation":[]},{"given":"Martin","family":"Cole","sequence":"additional","affiliation":[]},{"given":"Zhengwu","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,9,16]]},"reference":[{"issue":"141","key":"27_CR1","first-page":"1","volume":"22","author":"J Arroyo","year":"2021","unstructured":"Arroyo, J., Athreya, A., Cape, J., Chen, G., Priebe, C.E., Vogelstein, J.T.: Inference for multiple heterogeneous networks with a common invariant subspace. J. Mach. Learn. Res. JMLR 22(141), 1\u201349 (2021)","journal-title":"J. Mach. Learn. Res. JMLR"},{"issue":"365","key":"27_CR2","first-page":"1","volume":"2","author":"BB Avants","year":"2009","unstructured":"Avants, B.B., Tustison, N., Song, G.: Advanced normalization tools (ANTs). Insight J 2(365), 1\u201335 (2009)","journal-title":"Insight J"},{"issue":"1","key":"27_CR3","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","volume":"57","author":"Y Benjamini","year":"1995","unstructured":"Benjamini, Y., Hochberg, Y.: Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B (Methodol.) 57(1), 289\u2013300 (1995)","journal-title":"J. R. Stat. Soc. Ser. B (Methodol.)"},{"issue":"11","key":"27_CR4","doi-asserted-by":"publisher","first-page":"3481","DOI":"10.1002\/hbm.25447","volume":"42","author":"M Cole","year":"2021","unstructured":"Cole, M., et al.: Surface-based connectivity integration: an atlas-free approach to jointly study functional and structural connectivity. Hum. Brain Mapp. 42(11), 3481\u20133499 (2021)","journal-title":"Hum. Brain Mapp."},{"issue":"3","key":"27_CR5","doi-asserted-by":"publisher","first-page":"968","DOI":"10.1016\/j.neuroimage.2006.01.021","volume":"31","author":"RS Desikan","year":"2006","unstructured":"Desikan, R.S., et al.: An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31(3), 968\u2013980 (2006)","journal-title":"Neuroimage"},{"issue":"1","key":"27_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.neuroimage.2010.06.010","volume":"53","author":"C Destrieux","year":"2010","unstructured":"Destrieux, C., Fischl, B., Dale, A., Halgren, E.: Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. Neuroimage 53(1), 1\u201315 (2010)","journal-title":"Neuroimage"},{"issue":"520","key":"27_CR7","doi-asserted-by":"publisher","first-page":"1516","DOI":"10.1080\/01621459.2016.1219260","volume":"112","author":"D Durante","year":"2017","unstructured":"Durante, D., Dunson, D.B., Vogelstein, J.T.: Nonparametric Bayes modeling of populations of networks. J. Am. Stat. Assoc. 112(520), 1516\u20131530 (2017)","journal-title":"J. Am. Stat. Assoc."},{"issue":"4","key":"27_CR8","doi-asserted-by":"publisher","first-page":"914","DOI":"10.3758\/BF03193437","volume":"34","author":"SJ Estle","year":"2006","unstructured":"Estle, S.J., Green, L., Myerson, J., Holt, D.D.: Differential effects of amount on temporal and probability discounting of gains and losses. Mem. Cognit. 34(4), 914\u2013928 (2006). https:\/\/doi.org\/10.3758\/BF03193437","journal-title":"Mem. Cognit."},{"issue":"2","key":"27_CR9","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1006\/nimg.1998.0396","volume":"9","author":"B Fischl","year":"1999","unstructured":"Fischl, B., Sereno, M.I., Dale, A.M.: Cortical surface-based analysis: II: inflation, flattening, and a surface-based coordinate system. Neuroimage 9(2), 195\u2013207 (1999)","journal-title":"Neuroimage"},{"key":"27_CR10","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1016\/j.neuroimage.2013.04.127","volume":"80","author":"MF Glasser","year":"2013","unstructured":"Glasser, M.F., et al.: The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage 80, 105\u2013124 (2013)","journal-title":"Neuroimage"},{"issue":"25","key":"27_CR11","first-page":"723","volume":"13","author":"A Gretton","year":"2012","unstructured":"Gretton, A., Borgwardt, K.M., Rasch, M.J., Sch\u00f6lkopf, B., Smola, A.: A kernel two-sample test. J. Mach. Learn. Res. 13(25), 723\u2013773 (2012)","journal-title":"J. Mach. Learn. Res."},{"doi-asserted-by":"crossref","unstructured":"Lai, M.J., Schumaker, L.L.: Spline Functions on Triangulations. Encyclopedia of Mathematics and its Applications. Cambridge University Press (2007)","key":"27_CR12","DOI":"10.1017\/CBO9780511721588"},{"key":"27_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2022.118930","volume":"250","author":"S Mansour","year":"2022","unstructured":"Mansour, S., Seguin, C., Smith, R.E., Zalesky, A.: Connectome spatial smoothing (CSS): concepts, methods, and evaluation. Neuroimage 250, 118930 (2022)","journal-title":"Neuroimage"},{"key":"27_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.117695","volume":"229","author":"S Mansour","year":"2021","unstructured":"Mansour, S., Tian, Y., Yeo, B.T., Cropley, V., Zalesky, A.: High-resolution connectomic fingerprints: mapping neural identity and behavior. Neuroimage 229, 117695 (2021)","journal-title":"Neuroimage"},{"doi-asserted-by":"crossref","unstructured":"Moyer, D., Gutman, B.A., Faskowitz, J., Jahanshad, N., Thompson, P.M.: Continuous representations of brain connectivity using spatial point processes. Med. Image Anal. 41, 32\u201339 (2017). Special Issue on the 2016 Conference on Medical Image Computing and Computer Assisted Intervention (Analog to MICCAI 2015)","key":"27_CR15","DOI":"10.1016\/j.media.2017.04.013"},{"doi-asserted-by":"crossref","unstructured":"Nielsen, A.M., Witten, D.: The multiple random dot product graph model. arXiv preprint arXiv:1811.12172 (2018)","key":"27_CR16","DOI":"10.32614\/CRAN.package.multiRDPG"},{"issue":"7","key":"27_CR17","doi-asserted-by":"publisher","first-page":"1406","DOI":"10.1162\/jocn.2009.21107","volume":"21","author":"EA Olson","year":"2009","unstructured":"Olson, E.A., Collins, P.F., Hooper, C.J., Muetzel, R., Lim, K.O., Luciana, M.: White matter integrity predicts delay discounting behavior in 9- to 23-year-olds: a diffusion tensor imaging study. J. Cogn. Neurosci. 21(7), 1406\u20131421 (2009)","journal-title":"J. Cogn. Neurosci."},{"key":"27_CR18","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1016\/j.neuroimage.2017.08.045","volume":"161","author":"MM Owens","year":"2017","unstructured":"Owens, M.M., Gray, J.C., Amlung, M.T., Oshri, A., Sweet, L.H., MacKillop, J.: Neuroanatomical foundations of delayed reward discounting decision making. Neuroimage 161, 261\u2013270 (2017)","journal-title":"Neuroimage"},{"key":"27_CR19","doi-asserted-by":"publisher","first-page":"698","DOI":"10.3389\/fnhum.2014.00698","volume":"8","author":"A Sebastian","year":"2014","unstructured":"Sebastian, A., Jung, P., Krause-Utz, A., Lieb, K., Schmahl, C., T\u00fcscher, O.: Frontal dysfunctions of impulse control - a systematic review in borderline personality disorder and attention-deficit\/hyperactivity disorder. Front. Hum. Neurosci. 8, 698 (2014)","journal-title":"Front. Hum. Neurosci."},{"key":"27_CR20","doi-asserted-by":"publisher","first-page":"524","DOI":"10.1016\/j.neuroimage.2017.12.036","volume":"169","author":"E St-Onge","year":"2018","unstructured":"St-Onge, E., Daducci, A., Girard, G., Descoteaux, M.: Surface-enhanced tractography (SET). Neuroimage 169, 524\u2013539 (2018)","journal-title":"Neuroimage"},{"issue":"4","key":"27_CR21","doi-asserted-by":"publisher","first-page":"1459","DOI":"10.1016\/j.neuroimage.2007.02.016","volume":"35","author":"JD Tournier","year":"2007","unstructured":"Tournier, J.D., Calamante, F., Connelly, A.: Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. Neuroimage 35(4), 1459\u20131472 (2007)","journal-title":"Neuroimage"},{"issue":"10","key":"27_CR22","doi-asserted-by":"publisher","first-page":"2241","DOI":"10.1093\/cercor\/bhr291","volume":"22","author":"DC Van Essen","year":"2012","unstructured":"Van Essen, D.C., Glasser, M.F., Dierker, D.L., Harwell, J., Coalson, T.: Parcellations and hemispheric asymmetries of human cerebral cortex analyzed on surface-based atlases. Cereb. Cortex 22(10), 2241\u20132262 (2012)","journal-title":"Cereb. Cortex"},{"key":"27_CR23","first-page":"899","volume":"14","author":"XT Yuan","year":"2011","unstructured":"Yuan, X.T., Zhang, T.: Truncated power method for sparse eigenvalue problems. J. Mach. Learn. Res. 14, 899\u2013925 (2011)","journal-title":"J. Mach. Learn. Res."},{"issue":"3","key":"27_CR24","doi-asserted-by":"publisher","first-page":"970","DOI":"10.1016\/j.neuroimage.2009.12.027","volume":"50","author":"A Zalesky","year":"2010","unstructured":"Zalesky, A., et al.: Whole-brain anatomical networks: does the choice of nodes matter? Neuroimage 50(3), 970\u2013983 (2010)","journal-title":"Neuroimage"},{"key":"27_CR25","doi-asserted-by":"publisher","first-page":"330","DOI":"10.1016\/j.neuroimage.2019.04.027","volume":"197","author":"Z Zhang","year":"2019","unstructured":"Zhang, Z., Allen, G.I., Zhu, H., Dunson, D.: Tensor network factorizations: relationships between brain structural connectomes and traits. Neuroimage 197, 330\u2013343 (2019)","journal-title":"Neuroimage"}],"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\/978-3-031-16452-1_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T23:18:17Z","timestamp":1727997497000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-16452-1_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031164514","9783031164521"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-16452-1_27","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":"16 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)"}}]}}