{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T02:00:49Z","timestamp":1774922449249,"version":"3.50.1"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319590493","type":"print"},{"value":"9783319590509","type":"electronic"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-59050-9_32","type":"book-chapter","created":{"date-parts":[[2017,5,22]],"date-time":"2017-05-22T12:36:11Z","timestamp":1495456571000},"page":"398-410","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Tensor Statistical Model for Quantifying Dynamic Functional Connectivity"],"prefix":"10.1007","author":[{"given":"Yingying","family":"Zhu","sequence":"first","affiliation":[]},{"given":"Xiaofeng","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Minjeong","family":"Kim","sequence":"additional","affiliation":[]},{"given":"Jin","family":"Yan","sequence":"additional","affiliation":[]},{"given":"Guorong","family":"Wu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,5,23]]},"reference":[{"key":"32_CR1","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1038\/35084005","volume":"412","author":"NK Logothetis","year":"2001","unstructured":"Logothetis, N.K., Pauls, J., Augath, M., Trinath, T., Oeltermann, A.: Neurophysiological investigation of the basis of the fMRI signal. Nature 412, 150\u2013157 (2001)","journal-title":"Nature"},{"key":"32_CR2","doi-asserted-by":"publisher","first-page":"44428","DOI":"10.1371\/journal.pone.0044428","volume":"7","author":"MN Mousss","year":"2012","unstructured":"Mousss, M.N., Steen, M.R., Laurienti, P.J., Hayasaka, S.: Consistency of network modules in resting-state fMRI connectome data. PLoS One 7, 44428 (2012)","journal-title":"PLoS One"},{"issue":"4","key":"32_CR3","doi-asserted-by":"publisher","first-page":"987","DOI":"10.3233\/JAD-150400","volume":"48","author":"M Bilello","year":"2015","unstructured":"Bilello, M.: Correlating cognitive decline with white matter lesion and brain atrophy magnetic resonance imaging measurements in Alzheimer\u2019s disease. J. Alzheimers Dis. 48(4), 987\u2013994 (2015)","journal-title":"J. Alzheimers Dis."},{"key":"32_CR4","doi-asserted-by":"publisher","first-page":"938","DOI":"10.1016\/j.neuroimage.2012.01.090","volume":"62","author":"BB Biswal","year":"2012","unstructured":"Biswal, B.B.: Resting state fMRI: a personal history. NeuroImage 62, 938\u2013944 (2012)","journal-title":"NeuroImage"},{"key":"32_CR5","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1016\/j.euroneuro.2010.03.008","volume":"20","author":"M Heuvel","year":"2010","unstructured":"Heuvel, M., Pol, H.: Exploring the brain network: a review on resting-state fMRI functional connectivity. Eur. Neuropsychopharmacol. 20, 519\u2013534 (2010)","journal-title":"Eur. Neuropsychopharmacol."},{"key":"32_CR6","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.metabol.2014.10.030","volume":"64","author":"DB Miller","year":"2015","unstructured":"Miller, D.B., O\u2019Callaghan, J.: Biomarkers of Parkinson\u2019s disease. Metabolism 64, 40\u201346 (2015)","journal-title":"Metabolism"},{"key":"32_CR7","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1016\/j.neuron.2011.09.006","volume":"72","author":"JD Power","year":"2011","unstructured":"Power, J.D., Cohen, A.L., Nelson, S.M., Wig, G.S., Barnes, K.A., Church, J.A.: Functional network organization of the human brain. Neuron 72, 665\u2013678 (2011)","journal-title":"Neuron"},{"key":"32_CR8","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1016\/j.neuroimage.2013.05.079","volume":"80","author":"RM Hutchison","year":"2013","unstructured":"Hutchison, R.M., Womelsdorf, T., Allen, E.A., Bandettini, P.A., Calhoun, V.D., Corbetta, M.: Dynamic functional connectivity: promise, issues, and interpretations. Neuroimage 80, 360\u2013378 (2013)","journal-title":"Neuroimage"},{"key":"32_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1007\/978-3-319-46720-7_13","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2016","author":"Y Zhu","year":"2016","unstructured":"Zhu, Y., Zhu, X., Zhang, H., Gao, W., Shen, D., Wu, G.: Reveal consistent spatial-temporal patterns from dynamic functional connectivity for autism spectrum disorder identification. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9900, pp. 106\u2013114. Springer, Cham (2016). doi:10.1007\/978-3-319-46720-7_13"},{"key":"32_CR10","doi-asserted-by":"publisher","first-page":"212","DOI":"10.1111\/cns.12499","volume":"22","author":"C Wee","year":"2016","unstructured":"Wee, C., Yap, P., Shen, D.: Diagnosis of autism spectrum disorders using temporally distinct resting-state functional connectivity networks. CNS Neurosci. Ther. 22, 212\u2013219 (2016)","journal-title":"CNS Neurosci. Ther."},{"key":"32_CR11","doi-asserted-by":"publisher","first-page":"937","DOI":"10.1016\/j.neuroimage.2013.07.019","volume":"83","author":"N Leonardi","year":"2013","unstructured":"Leonardi, N.: Principal components of functional connectivity: a new approach to study dynamic brain connectivity during rest. NeuroImage 83, 937\u2013950 (2013)","journal-title":"NeuroImage"},{"key":"32_CR12","first-page":"75","volume":"31","author":"MP Heuvel","year":"2011","unstructured":"Heuvel, M.P., Sporns, O.: Rich-club organization of the human connectome. J. Neurosci. 31, 75\u201386 (2011)","journal-title":"J. Neurosci."},{"key":"32_CR13","first-page":"186","volume":"10","author":"E Bullmore","year":"2009","unstructured":"Bullmore, E., Sporns, O.: Complex brain networks: graph theoretical analysis of structural and functional systems. Nature 10, 186\u2013198 (2009)","journal-title":"Nature"},{"key":"32_CR14","doi-asserted-by":"crossref","unstructured":"Zhu, Y., Huang, D., De La Torre, F., Lucey, S.: Complex non-rigid motion 3D reconstruction by union of subspaces. In: CVPR (2014)","DOI":"10.1109\/CVPR.2014.200"},{"key":"32_CR15","doi-asserted-by":"crossref","unstructured":"Zhu, Y., Lucey, S.: 3D motion reconstruction for real-world camera motion. In: CVPR (2011)","DOI":"10.1109\/CVPR.2011.5995650"},{"key":"32_CR16","doi-asserted-by":"publisher","first-page":"641","DOI":"10.1007\/s00429-013-0524-8","volume":"219","author":"C Wee","year":"2014","unstructured":"Wee, C., Yap, P., Zhang, D., Wang, L., Shen, D.: Group-constrained sparse fMRI connectivity modeling for mild cognitive impairment identification. Brain Struct. Funct. 219, 641\u2013656 (2014)","journal-title":"Brain Struct. Funct."},{"key":"32_CR17","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1109\/TPAMI.2013.2295311","volume":"37","author":"Y Zhu","year":"2015","unstructured":"Zhu, Y., Lucey, S.: Convolutional sparse coding for trajectory reconstruction. IEEE Trans. Pattern Anal. Mach. Intell. 37, 529\u2013540 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Lecture Notes in Computer Science","Information Processing in Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-59050-9_32","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,5]],"date-time":"2024-03-05T14:05:02Z","timestamp":1709647502000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-59050-9_32"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319590493","9783319590509"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-59050-9_32","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"23 May 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IPMI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Information Processing in Medical Imaging","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Boone","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 June 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 June 2017","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":"ipmi2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ipmi2017.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}