{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:28:30Z","timestamp":1742912910809,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030319007"},{"type":"electronic","value":"9783030319014"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-31901-4_21","type":"book-chapter","created":{"date-parts":[[2019,10,9]],"date-time":"2019-10-09T23:04:53Z","timestamp":1570662293000},"page":"176-185","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Cortical and Subcortical Contributions to Predicting Intelligence Using 3D ConvNets"],"prefix":"10.1007","author":[{"given":"Yukai","family":"Zou","sequence":"first","affiliation":[]},{"given":"Ikbeom","family":"Jang","sequence":"additional","affiliation":[]},{"given":"Timothy G.","family":"Reese","sequence":"additional","affiliation":[]},{"given":"Jinxia","family":"Yao","sequence":"additional","affiliation":[]},{"given":"Wenbin","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Joseph V.","family":"Rispoli","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,10,10]]},"reference":[{"issue":"4","key":"21_CR1","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1111\/mono.12038","volume":"78","author":"Natacha Akshoomoff","year":"2013","unstructured":"Akshoomoff, N., et al.: NIH toolbox cognition battery (CB): composite scores of crystallized, fluid, and overall cognition. Monographs of the Society for Research in Child Development (2013). https:\/\/doi.org\/10.1111\/mono.12038","journal-title":"Monographs of the Society for Research in Child Development"},{"key":"21_CR2","doi-asserted-by":"publisher","DOI":"10.1017\/cbo9780511571312","volume-title":"Human Cognitive Abilities","author":"JB Carroll","year":"2009","unstructured":"Carroll, J.B.: Human Cognitive Abilities. Cambridge University Press, Cambridge (2009). https:\/\/doi.org\/10.1017\/cbo9780511571312"},{"key":"21_CR3","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.neuroimage.2017.07.059","volume":"163","author":"JH Cole","year":"2017","unstructured":"Cole, J.H., et al.: Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker. NeuroImage 163, 115\u2013124 (2017). https:\/\/doi.org\/10.1016\/j.neuroimage.2017.07.059","journal-title":"NeuroImage"},{"key":"21_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3389\/fninf.2017.00001","volume":"11","author":"DA Dickie","year":"2017","unstructured":"Dickie, D.A., et al.: Whole brain magnetic resonance image atlases: a systematic review of existing atlases and caveats for use in population imaging. Front. Neuroinformatics 11, 1 (2017). https:\/\/doi.org\/10.3389\/fninf.2017.00001","journal-title":"Front. Neuroinformatics"},{"key":"21_CR5","doi-asserted-by":"publisher","first-page":"1432","DOI":"10.1093\/brain\/awm042","volume":"130","author":"NF Dronkers","year":"2007","unstructured":"Dronkers, N.F., Plaisant, O., Iba-Zizen, M.T., Cabanis, E.A.: Paul Broca\u2019s historic cases: high resolution MR imaging of the brains of Leborgne and Lelong. Brain 130, 1432\u20131441 (2007). https:\/\/doi.org\/10.1093\/brain\/awm042","journal-title":"Brain"},{"key":"21_CR6","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1016\/j.neuroimage.2010.07.033","volume":"54","author":"V Fonov","year":"2011","unstructured":"Fonov, V., Evans, A.C., Botteron, K., Almli, C.R., McKinstry, R.C., Collins, D.L.: Unbiased average age-appropriate atlases for pediatric studies. NeuroImage 54, 313\u2013327 (2011). https:\/\/doi.org\/10.1016\/j.neuroimage.2010.07.033","journal-title":"NeuroImage"},{"key":"21_CR7","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1016\/j.pneurobio.2008.09.004","volume":"86","author":"JA Grahn","year":"2008","unstructured":"Grahn, J.A., Parkinson, J.A., Owen, A.M.: The cognitive functions of the caudate nucleus. Prog. Neurobiol. 86, 141\u2013155 (2008). https:\/\/doi.org\/10.1016\/j.pneurobio.2008.09.004","journal-title":"Prog. Neurobiol."},{"key":"21_CR8","doi-asserted-by":"publisher","unstructured":"Hagler, D.J., et al.: Image processing and analysis methods for the adolescent brain cognitive development study. bioRxiv p. 457739 (2018). https:\/\/doi.org\/10.1101\/457739","DOI":"10.1101\/457739"},{"key":"21_CR9","unstructured":"Ioffe, S., Szegedy, C.: Batch normalization: accelerating deep network training by reducing internal covariate shift. arXiv e-prints arXiv:1502.03167 (2015)"},{"key":"21_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.dcn.2018.02.002","volume":"32","author":"Terry L. Jernigan","year":"2018","unstructured":"Jernigan, T.: Introduction. Developmental Cognitive Neuroscience (2018). https:\/\/doi.org\/10.1016\/j.dcn.2018.02.002","journal-title":"Developmental Cognitive Neuroscience"},{"key":"21_CR11","unstructured":"Kingma, D.P., Ba, J.L.: Adam: a method for stochastic gradient descent. In: ICLR: International Conference on Learning Representations (2015). https:\/\/arxiv.org\/pdf\/1412.6980.pdf"},{"key":"21_CR12","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1111\/j.0956-7976.2004.01503003.x","volume":"15","author":"SC Li","year":"2004","unstructured":"Li, S.C., Lindenberger, U., Hommel, B., Aschersleben, G., Prinz, W., Baltes, P.B.: Transformations in the couplings among intellectual abilities and constituent cognitive processes across the life span. Psychol. Sci. 15, 155\u2013163 (2004). https:\/\/doi.org\/10.1111\/j.0956-7976.2004.01503003.x","journal-title":"Psychol. Sci."},{"key":"21_CR13","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1176\/appi.ajp.2017.17040469","volume":"175","author":"A Pfefferbaum","year":"2018","unstructured":"Pfefferbaum, A., et al.: Altered brain developmental trajectories in adolescents after initiating drinking. Am. J. Psychiatry 175, 370\u2013380 (2018). https:\/\/doi.org\/10.1176\/appi.ajp.2017.17040469","journal-title":"Am. J. Psychiatry"},{"key":"21_CR14","doi-asserted-by":"publisher","first-page":"229","DOI":"10.3389\/fnins.2014.00229","volume":"8","author":"SM Plis","year":"2014","unstructured":"Plis, S.M., et al.: Deep learning for neuroimaging: a validation study. Front. Neurosci. 8, 229 (2014). https:\/\/doi.org\/10.3389\/fnins.2014.00229","journal-title":"Front. Neurosci."},{"key":"21_CR15","doi-asserted-by":"publisher","first-page":"798","DOI":"10.1002\/hbm.20906","volume":"31","author":"T Rohlfing","year":"2010","unstructured":"Rohlfing, T., Zahr, N.M., Sullivan, E.V., Pfefferbaum, A.: The SRI24 multichannel atlas of normal adult human brain structure. Hum. Brain Mapp. 31, 798\u2013819 (2010). https:\/\/doi.org\/10.1002\/hbm.20906","journal-title":"Hum. Brain Mapp."},{"key":"21_CR16","doi-asserted-by":"publisher","first-page":"21","DOI":"10.3758\/BF03210739","volume":"3","author":"JP Rushton","year":"1996","unstructured":"Rushton, J.P., Ankney, C.D.: Brain size and cognitive ability: correlations with age, sex, social class, and race. Psychon. Bull. Rev. 3, 21\u201336 (1996). https:\/\/doi.org\/10.3758\/BF03210739","journal-title":"Psychon. Bull. Rev."},{"key":"21_CR17","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1038\/nature22073","volume":"545","author":"LI Schmitt","year":"2017","unstructured":"Schmitt, L.I., Wimmer, R.D., Nakajima, M., Happ, M., Mofakham, S., Halassa, M.M.: Thalamic amplification of cortical connectivity sustains attentional control. Nature 545, 219 (2017). https:\/\/doi.org\/10.1038\/nature22073","journal-title":"Nature"},{"key":"21_CR18","unstructured":"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15, 1929\u20131958 (2014)"},{"key":"21_CR19","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1002\/mrm.23228","volume":"68","author":"MD Tisdall","year":"2012","unstructured":"Tisdall, M.D., Hess, A.T., Reuter, M., Meintjes, E.M., Fischl, B., Van Der Kouwe, A.J.: Volumetric navigators for prospective motion correction and selective reacquisition in neuroanatomical MRI. Magn. Reson. Med. 68, 389\u2013399 (2012). https:\/\/doi.org\/10.1002\/mrm.23228","journal-title":"Magn. Reson. Med."},{"key":"21_CR20","doi-asserted-by":"publisher","first-page":"e0117295","DOI":"10.1371\/journal.pone.0117295","volume":"10","author":"L Wang","year":"2015","unstructured":"Wang, L., Wee, C.Y., Suk, H.I., Tang, X., Shen, D.: MRI-based intelligence quotient (IQ) estimation with sparse learning. PLoS One 10, e0117295 (2015). https:\/\/doi.org\/10.1371\/journal.pone.0117295","journal-title":"PLoS One"},{"key":"21_CR21","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1002\/mrm.22176","volume":"63","author":"N White","year":"2010","unstructured":"White, N., et al.: PROMO: real-time prospective motion correction in MRI using image-based tracking. Magn. Reson. Med. 63, 91\u2013105 (2010). https:\/\/doi.org\/10.1002\/mrm.22176","journal-title":"Magn. Reson. Med."}],"container-title":["Lecture Notes in Computer Science","Adolescent Brain Cognitive Development Neurocognitive Prediction"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-31901-4_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T00:03:52Z","timestamp":1728518632000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-31901-4_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030319007","9783030319014"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-31901-4_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"10 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ABCD-NP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Challenge in Adolescent Brain Cognitive Development Neurocognitive Prediction","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenzhen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"abcdnp2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sibis.sri.com\/abcd-np-challenge\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"29","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":"24","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":"83% - 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":"2","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":"8","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The papers were written as a report to the submission for the challenge. All submissions were monitored by the organizers and the results were evaluated on a novel set of testing data. The papers were further reviewed by the chairs and organizers for quality assurance.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}