{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:27:28Z","timestamp":1740122848924,"version":"3.37.3"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"21-22","license":[{"start":{"date-parts":[[2018,7,25]],"date-time":"2018-07-25T00:00:00Z","timestamp":1532476800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,7,25]],"date-time":"2018-07-25T00:00:00Z","timestamp":1532476800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["51307010"],"award-info":[{"award-number":["51307010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"University Natural Science Research Program of Jiangsu Province","award":["17KJB510003"],"award-info":[{"award-number":["17KJB510003"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2020,6]]},"DOI":"10.1007\/s11042-018-6424-4","type":"journal-article","created":{"date-parts":[[2018,7,25]],"date-time":"2018-07-25T20:05:39Z","timestamp":1532549139000},"page":"15075-15093","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Rich club characteristics of dynamic brain functional networks in resting state"],"prefix":"10.1007","volume":"79","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6547-8449","authenticated-orcid":false,"given":"Zhuqing","family":"Jiao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Cai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yin","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Zou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuihua","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,7,25]]},"reference":[{"issue":"3","key":"6424_CR1","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1038\/nn.4497","volume":"20","author":"M Breakspear","year":"2017","unstructured":"Breakspear M (2017) Dynamic models of large-scale brain activity. Nat Neurosci 20(3):340\u2013352","journal-title":"Nat Neurosci"},{"issue":"2","key":"6424_CR2","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1016\/j.neuron.2014.10.015","volume":"84","author":"VD Calhoun","year":"2014","unstructured":"Calhoun VD, Miller R, Pearlson G, Adal T (2014) The chronnectome: time-varying connectivity networks as the next frontier in fMRI data discovery. Neuron 84(2):262\u2013274","journal-title":"Neuron"},{"issue":"9","key":"6424_CR3","doi-asserted-by":"publisher","first-page":"3282","DOI":"10.1002\/hbm.23240","volume":"37","author":"XB Chen","year":"2016","unstructured":"Chen XB, Zhang H, Gao YZ, Wee CY, Li G, Shen DG (2016) High-order resting-state functional connectivity network for MCI classification. Hum Brain Mapp 37(9):3282\u20133296","journal-title":"Hum Brain Mapp"},{"issue":"3","key":"6424_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s12021-016-9321-x","volume":"15","author":"XB Chen","year":"2017","unstructured":"Chen XB, Zhang H, Lee SW, Shen DG (2017) Hierarchical high-order functional connectivity networks and selective feature fusion for MCI classification. Neuroinformatics 15(3):1\u201314","journal-title":"Neuroinformatics"},{"issue":"2","key":"6424_CR5","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1038\/nphys209","volume":"2","author":"V Colizza","year":"2006","unstructured":"Colizza V, Flammini A, Serrano MA, Vespignani A (2006) Detecting rich-club ordering in complex networks. Nat Phys 2(2):110\u2013115","journal-title":"Nat Phys"},{"issue":"8","key":"6424_CR6","doi-asserted-by":"publisher","first-page":"3087","DOI":"10.1002\/hbm.22830","volume":"36","author":"M Daianu","year":"2015","unstructured":"Daianu M, Jahanshad N, Nir TM, Jack CR Jr, Weiner MW, Bernstein MA, Thompson PM (2015) Rich club analysis in the Alzheimer's disease connectome reveals a relatively undisturbed structural core network. Hum Brain Mapp 36(8):3087\u20133103","journal-title":"Hum Brain Mapp"},{"issue":"C","key":"6424_CR7","doi-asserted-by":"publisher","first-page":"298","DOI":"10.1016\/j.nicl.2014.07.003","volume":"5","author":"E Damaraju","year":"2014","unstructured":"Damaraju E, Allen EA, Belger A, Ford JM, McEwen S, Mathalon DH, Mueller BA, Pearlson GD, Potkin SG, Preda A, Turner JA, Vaidya JG, van Erp TG, Calhoun VD (2014) Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia. NeuroImage: Clin 5(C):298\u2013308","journal-title":"NeuroImage: Clin"},{"issue":"3\u20134","key":"6424_CR8","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1007\/s00429-010-0283-8","volume":"215","author":"C Ech\u00e1varri","year":"2011","unstructured":"Ech\u00e1varri C, Aalten P, Uylings H, Jacobs H, Visser P, Gronenschild E, Verhey F, Burgmans S (2011) Atrophy in the parahippocampal gyrus as an early biomarker of Alzheimer\u2019s disease. Brain Struct Funct 215(3\u20134):265\u2013271","journal-title":"Brain Struct Funct"},{"unstructured":"Geng YY, Liang RZ, Li WZ, Wang JB, Liang GY, Xu CH, Wang JY (2016) Learning convolutional neural network to maximize pos@ top performance measure. ESANN 2017 proceedings, European symposium on artificial neural networks, Computational intelligence and machine learning: 589\u2013594","key":"6424_CR9"},{"doi-asserted-by":"crossref","unstructured":"Geng YY, Zhang GH, Li WZ, Gu Y, Liang RZ, Liang GY, Wang JB, Wu YB, Patil N, Wang JY (2017) A novel image tag completion method based on convolutional neural transformation. Lect Notes Comput Sci 10614:539\u2013546","key":"6424_CR10","DOI":"10.1007\/978-3-319-68612-7_61"},{"issue":"20","key":"6424_CR11","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1016\/j.neuroimage.2013.04.056","volume":"80","author":"A Griffa","year":"2013","unstructured":"Griffa A, Baumann PS, Thiran JP, Hagmann P (2013) Structural connectomics in brain diseases. Neuroimage 80(20):515\u2013526","journal-title":"Neuroimage"},{"issue":"2","key":"6424_CR12","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1093\/schbul\/sbt162","volume":"40","author":"C Guusje","year":"2014","unstructured":"Guusje C, Kahn RS, De RMA, Wiepke C, van den Heuvel M (2014) Impaired Rich Club connectivity in unaffected siblings of schizophrenia patients. Schizophr Bull 40(2):438\u2013448","journal-title":"Schizophr Bull"},{"issue":"8","key":"6424_CR13","doi-asserted-by":"publisher","first-page":"2332","DOI":"10.1093\/brain\/awv145","volume":"138","author":"DL Harrington","year":"2015","unstructured":"Harrington DL, Rubinov M, Durgerian S, Mourany L, Reece C, Koenig K, Long JD, Paulsen JS (2015) Network topology and functional connectivity disturbances precede the onset of Huntington\u2019s disease. Brain 138(8):2332\u20132346","journal-title":"Brain"},{"issue":"3","key":"6424_CR14","doi-asserted-by":"publisher","first-page":"809","DOI":"10.1007\/s11227-013-1010-z","volume":"67","author":"ZQ Jiao","year":"2014","unstructured":"Jiao ZQ, Zou L, Cao Y, Qian N, Ma ZH (2014) Effective connectivity analysis of fMRI data based on network motifs. J Supercomput 67(3):809\u2013819","journal-title":"J Supercomput"},{"issue":"3","key":"6424_CR15","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1504\/IJSNET.2016.078374","volume":"21","author":"ZQ Jiao","year":"2016","unstructured":"Jiao ZQ, Wang H, Ma K (2016) The connectivity measurement in complex directed networks by motif structure. Int J Sensor Netw 21(3):197\u2013204","journal-title":"Int J Sensor Netw"},{"issue":"2","key":"6424_CR16","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1504\/IJSNET.2017.084674","volume":"24","author":"ZQ Jiao","year":"2017","unstructured":"Jiao ZQ, Ma K, Rong YL, Wang H, Zou L (2017) Adaptive synchronization in small-world networks with Lorenz chaotic oscillators. Int J Sensor Netw 24(2):90\u201397","journal-title":"Int J Sensor Netw"},{"doi-asserted-by":"publisher","unstructured":"Jiao ZQ, Ma K, Wang H, Zou L, Zhang YD (2017) Research on node properties of resting-state brain functional networks by using node activity and ALFF. Multimedia Tools Appl. \n                  https:\/\/doi.org\/10.1007\/s11042-017-5163-2","key":"6424_CR17","DOI":"10.1007\/s11042-017-5163-2"},{"issue":"10","key":"6424_CR18","doi-asserted-by":"publisher","first-page":"1634","DOI":"10.2741\/4562","volume":"22","author":"ZQ Jiao","year":"2017","unstructured":"Jiao ZQ, Wang H, Ma K, Zou L, Xiang JB (2017) Directed connectivity of brain default networks using GCA and motif. Front Biosci 22(10):1634\u20131643","journal-title":"Front Biosci"},{"issue":"1","key":"6424_CR19","doi-asserted-by":"publisher","first-page":"44","DOI":"10.2174\/1871527314666161124120040","volume":"16","author":"ZQ Jiao","year":"2017","unstructured":"Jiao ZQ, Ma K, Wang H, Zou L, Xiang JB (2017) Functional connectivity analysis of brain default mode networks using Hamiltonian path. CNS Neurol Disord Drug Targets 16(1):44\u201350","journal-title":"CNS Neurol Disord Drug Targets"},{"issue":"2","key":"6424_CR20","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1166\/jmihi.2017.2029","volume":"7","author":"ZQ Jiao","year":"2017","unstructured":"Jiao ZQ, Wang H, Ma K, Zou L, Xiang JB, Wang SH (2017) Effective connectivity in the default network using granger causal analysis. J Med Imaging Health Inform 7(2):407\u2013415","journal-title":"J Med Imaging Health Inform"},{"issue":"19","key":"6424_CR21","doi-asserted-by":"publisher","first-page":"198701","DOI":"10.1103\/PhysRevLett.87.198701","volume":"87","author":"V Latora","year":"2001","unstructured":"Latora V, Marchiori M (2001) Efficient behavior of small-world networks. Phys Rev Lett 87(19):198701","journal-title":"Phys Rev Lett"},{"issue":"4","key":"6424_CR22","doi-asserted-by":"publisher","first-page":"1071","DOI":"10.1007\/s11424-015-4145-6","volume":"29","author":"HJ Li","year":"2016","unstructured":"Li HJ, Li HY (2016) Scalably revealing the dynamics of soft community structure in complex networks. J Syst Sci Complex 29(4):1071\u20131088","journal-title":"J Syst Sci Complex"},{"issue":"3","key":"6424_CR23","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0119678","volume":"10","author":"A Ma","year":"2014","unstructured":"Ma A, Mondrag\u00f3n RJ (2014) Rich-cores in networks. PLoS One 10(3):e0119678","journal-title":"PLoS One"},{"issue":"3","key":"6424_CR24","first-page":"2166","volume":"27","author":"S Markett","year":"2017","unstructured":"Markett S, de Reus MA, Reuter M, Montag C, Weber B, Schoene-Bake JC (2017) Serotonin and the brain's Rich Club-association between molecular genetic variation on the TPH2 gene and the structural connectome. Cereb Cortex 27(3):2166\u20132174","journal-title":"Cereb Cortex"},{"issue":"1","key":"6424_CR25","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1002\/hbm.23346","volume":"38","author":"HA Marusak","year":"2016","unstructured":"Marusak HA, Calhoun VD, Brown S, Crespo LM, Sala-Hamrick K, Gotlib IH, Thomason ME (2016) Dynamic functional connectivity of neurocognitive networks in children. Hum Brain Mapp 38(1):97\u2013108","journal-title":"Hum Brain Mapp"},{"issue":"11","key":"6424_CR26","doi-asserted-by":"publisher","first-page":"3327","DOI":"10.1093\/brain\/awv259","volume":"138","author":"P Mccolgan","year":"2015","unstructured":"Mccolgan P, Seunarine KK, Razi A, Cole JH, Gregory S, Durr A, Roos RAC, Stout JC, Landwehrmeyer B, Scahill RI, Clark CA, Rees G, Tabrizi SJ (2015) Selective vulnerability of Rich Club brain regions is an organizational principle of structural connectivity loss in Huntington\u2019s disease. Brain 138(11):3327\u20133344","journal-title":"Brain"},{"issue":"1","key":"6424_CR27","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1037\/neu0000317","volume":"31","author":"TT Nguyen","year":"2016","unstructured":"Nguyen TT, Kovacevic S, Dev SI, Lu K, Liu TT, Eyler LT (2016) Dynamic functional connectivity in bipolar disorder is associated with executive function and processing speed: a preliminary study. Neuropsychology 31(1):73\u201383","journal-title":"Neuropsychology"},{"issue":"10","key":"6424_CR28","doi-asserted-by":"publisher","first-page":"878","DOI":"10.1093\/cercor\/bhv185","volume":"26","author":"F Pasquale","year":"2016","unstructured":"Pasquale F, Penna S, Sporns O, Romani G, Corbetta M (2016) A dynamic core network and global efficiency in the resting human brain. Cereb Cortex 26(10):878\u2013896","journal-title":"Cereb Cortex"},{"issue":"1","key":"6424_CR29","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1016\/j.pscychresns.2011.06.014","volume":"194","author":"SP Poulin","year":"2011","unstructured":"Poulin SP, Dautoff R, Morris JC, Barrett LF, Dickerson BC (2011) Alzheimer's disease neuroimaging initiative. Amygdala atrophy is prominent in early Alzheimer\u2019s disease and relates to symptom severity. Psychiatry Res 194(1):7\u201313","journal-title":"Psychiatry Res"},{"issue":"4","key":"6424_CR30","doi-asserted-by":"publisher","first-page":"798","DOI":"10.1016\/j.neuron.2013.07.035","volume":"79","author":"JD Power","year":"2013","unstructured":"Power JD, Schlaggar BL, Lessov-Schlaggar CN, Petersen SE (2013) Evidence for hubs in human functional brain networks. Neuron 79(4):798\u2013813","journal-title":"Neuron"},{"issue":"12","key":"6424_CR31","doi-asserted-by":"publisher","first-page":"6032","DOI":"10.1002\/hbm.22603","volume":"35","author":"S Ray","year":"2015","unstructured":"Ray S, Miller M, Karalunas S, Robertson C, Grayson DS, Cary RP, Hawkey E, Painter JG, Fombonne E, Nigg JT, Fair DA (2015) Structural and functional connectivity of the human brain in autism spectrum disorders and attention-deficit\/hyperactivity disorder: a rich club organization study. Hum Brain Mapp 35(12):6032\u20136048","journal-title":"Hum Brain Mapp"},{"issue":"3","key":"6424_CR32","doi-asserted-by":"publisher","first-page":"1059","DOI":"10.1016\/j.neuroimage.2009.10.003","volume":"52","author":"M Rubinov","year":"2010","unstructured":"Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52(3):1059\u20131069","journal-title":"Neuroimage"},{"issue":"5","key":"6424_CR33","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1016\/j.biopsych.2012.11.028","volume":"74","author":"YI Sheline","year":"2013","unstructured":"Sheline YI, Raichle ME (2013) Resting state functional connectivity in preclinical Alzheimer\u2019s disease. Biol Psychiatry 74(5):340\u2013347","journal-title":"Biol Psychiatry"},{"issue":"10","key":"6424_CR34","doi-asserted-by":"publisher","first-page":"1049","DOI":"10.1371\/journal.pone.0001049","volume":"2","author":"O Sporns","year":"2007","unstructured":"Sporns O, Honey C, K\u00f6tter R (2007) Identification and classification of hubs in brain networks. PLoS One 2(10):1049\u20131062","journal-title":"PLoS One"},{"issue":"12","key":"6424_CR35","doi-asserted-by":"publisher","first-page":"6185","DOI":"10.1002\/hbm.23821","volume":"38","author":"MJ Tobia","year":"2017","unstructured":"Tobia MJ, Hayashi K, Ballard G, Gotlib IH, Waugh CE (2017) Dynamic functional connectivity and individual differences in emotions during social stress. Hum Brain Mapp 38(12):6185\u20136205","journal-title":"Hum Brain Mapp"},{"issue":"1","key":"6424_CR36","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, Mazoyer B, 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"},{"issue":"44","key":"6424_CR37","doi-asserted-by":"publisher","first-page":"15775","DOI":"10.1523\/JNEUROSCI.3539-11.2011","volume":"31","author":"MDH Van","year":"2011","unstructured":"Van MDH, Sporns O (2011) Rich-club organization of the human connectome. J Neurosci 31(44):15775\u201315786","journal-title":"J Neurosci"},{"issue":"16","key":"6424_CR38","first-page":"16","volume":"4","author":"JH Wang","year":"2010","unstructured":"Wang JH, Zuo X, He Y (2010) Graph-based network analysis of resting-state functional MRI. Front Syst Neurosci 4(16):16","journal-title":"Front Syst Neurosci"},{"issue":"7","key":"6424_CR39","first-page":"0978","volume":"22","author":"X Wang","year":"2017","unstructured":"Wang X, Ren YS, Zhang WS (2017) Multi-task fused lasso metllod for constructing dynamic functional brain network of resting-state fMRI. J Image Graph 22(7):0978\u20130987","journal-title":"J Image Graph"},{"issue":"3","key":"6424_CR40","doi-asserted-by":"publisher","first-page":"3701","DOI":"10.1007\/s11042-016-3401-7","volume":"77","author":"SH Wang","year":"2018","unstructured":"Wang SH, Du SD, Atangana A, Liu AJ, Lu ZY (2018) Application of stationary wavelet entropy in pathological brain detection. Multimedia Tools Appl 77(3):3701\u20133714","journal-title":"Multimedia Tools Appl"},{"issue":"5","key":"6424_CR41","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1007\/s10916-018-0932-7","volume":"42","author":"SH Wang","year":"2018","unstructured":"Wang SH, Phillips P, Sui Y, Liu B, Yang M, Cheng H (2018) Classification of Alzheimer's disease based on eight-layer convolutional neural network with leaky rectified linear unit and max pooling. J Med Syst 42(5):85","journal-title":"J Med Syst"},{"issue":"2","key":"6424_CR42","doi-asserted-by":"publisher","first-page":"342","DOI":"10.1007\/s11682-015-9408-2","volume":"10","author":"CY Wee","year":"2016","unstructured":"Wee CY, Yang S, Yap PT, Shen D (2016) Sparse temporally dynamic resting-state functional connectivity networks for early MCI identification. Brain Imaging Behav 10(2):342\u2013356","journal-title":"Brain Imaging Behav"},{"issue":"5","key":"6424_CR43","doi-asserted-by":"publisher","first-page":"194","DOI":"10.3390\/e18050194","volume":"18","author":"M Yang","year":"2016","unstructured":"Yang M, Zhang Y, Li JW, Zou L, Lu SY, Liu B, Yang JQ, Zhang YD (2016) Detection of left-sided and right-sided hearing loss via fractional Fourier transform. Entropy 18(5):194","journal-title":"Entropy"},{"issue":"1","key":"6424_CR44","first-page":"18","volume":"34","author":"ZQ Yao","year":"2012","unstructured":"Yao ZQ, Shang KK, Xu XK (2012) Fundamental statistics of weighted networks. J Univ Shanghai Sci Technol 34(1):18\u201326","journal-title":"J Univ Shanghai Sci Technol"},{"issue":"s1","key":"6424_CR45","doi-asserted-by":"publisher","DOI":"10.7717\/peerj.1251","volume":"3","author":"YD Zhang","year":"2015","unstructured":"Zhang YD, Wang SH (2015) Detection of Alzheimer's disease by displacement field and machine learning. Peerj 3(s1):e1251","journal-title":"Peerj"},{"key":"6424_CR46","first-page":"66","volume":"9","author":"YD Zhang","year":"2015","unstructured":"Zhang YD, Dong ZC, Phillips P, Wang SH, Ji GL, Yang JQ, Yuan TF (2015) Detection of subjects and brain regions related to Alzheimer's disease using 3D MRI scans based on eigenbrain and machine learning. Front Comput Neurosci 9:66","journal-title":"Front Comput Neurosci"},{"key":"6424_CR47","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.bspc.2015.05.014","volume":"21","author":"YD Zhang","year":"2015","unstructured":"Zhang YD, Wang SD, Phillips P, Dong ZC, Ji GL, Yang JQ (2015) Detection of Alzheimer's disease and mild cognitive impairment based on structural volumetric MR images using 3D-DWT and WTA-KSVM trained by PSOTVAC. Biomed Signal Process Control 21:58\u201373","journal-title":"Biomed Signal Process Control"},{"key":"6424_CR48","doi-asserted-by":"publisher","first-page":"5937","DOI":"10.1109\/ACCESS.2016.2611530","volume":"4","author":"YD Zhang","year":"2016","unstructured":"Zhang YD, Chen XQ, Zhan TM, Jiao ZQ, Sun Y, Chen ZM, Yao Y, Fang LT, Lv YD, Wang SH (2016) Fractal dimension estimation for developing pathological brain detection system based on Minkowski-Bouligand method. IEEE Access 4:5937\u20135947","journal-title":"IEEE Access"},{"key":"6424_CR49","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2016\/9416435","volume":"3","author":"YD Zhang","year":"2016","unstructured":"Zhang YD, Yang JQ, Yang JF, Liu AJ, Sun P (2016) A novel compressed sensing method for magnetic resonance imaging: exponential wavelet iterative shrinkage-thresholding algorithm with random shift. Int J Biomed Imaging 3:1\u201310","journal-title":"Int J Biomed Imaging"},{"issue":"4","key":"6424_CR50","doi-asserted-by":"publisher","first-page":"1163","DOI":"10.3233\/JAD-150988","volume":"50","author":"YD Zhang","year":"2016","unstructured":"Zhang YD, Wang SH, Phillips P, Yang JQ, Yuan TF (2016) Three-dimensional eigenbrain for the detection of subjects and brain regions related with Alzheimer\u2019s disease. J Alzheimers Dis 50(4):1163\u20131179","journal-title":"J Alzheimers Dis"},{"issue":"16","key":"6424_CR51","doi-asserted-by":"publisher","first-page":"C167","DOI":"10.1016\/j.jacc.2017.07.613","volume":"70","author":"YD Zhang","year":"2017","unstructured":"Zhang YD, Yang M, Wang SH (2017) Two-level iterative compressed sensing for cardiovascular magnetic resonance imaging. J Am Coll Cardiol 70(16):C167","journal-title":"J Am Coll Cardiol"},{"doi-asserted-by":"crossref","unstructured":"Zhang GH, Liang GY, Li WZ, Fang J, Wang JB, Geng YY, Wang JY (2017) Learning convolutional ranking-score function by query preference regularization. Lect Notes Comput Sci 10585:1\u20138","key":"6424_CR52","DOI":"10.1007\/978-3-319-68935-7_1"},{"issue":"1","key":"6424_CR53","doi-asserted-by":"publisher","first-page":"6530","DOI":"10.1038\/s41598-017-06509-0","volume":"7","author":"Y Zhang","year":"2017","unstructured":"Zhang Y, Zhang H, Chen XB, Lee SW, Shen DG (2017) Hybrid high-order functional connectivity networks using resting-state functional MRI for mild cognitive impairment diagnosis. Sci Rep 7(1):6530","journal-title":"Sci Rep"},{"issue":"3","key":"6424_CR54","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1109\/LCOMM.2004.823426","volume":"8","author":"S Zhou","year":"2003","unstructured":"Zhou S, Mondragon RJ (2003) The rich-club phenomenon in the internet topology. IEEE Commun Lett 8(3):180\u2013182","journal-title":"IEEE Commun Lett"},{"issue":"3","key":"6424_CR55","doi-asserted-by":"publisher","first-page":"364","DOI":"10.1002\/tee.22226","volume":"11","author":"XX Zhou","year":"2016","unstructured":"Zhou XX, Zhang YD, Ji GL, Yang JQ, Dong ZC, Wang SH, Zhang GS, Phillips P (2016) Detection of abnormal MR brains based on wavelet entropy and feature selection. IEEJ Trans Electr Electron Eng 11(3):364\u2013373","journal-title":"IEEJ Trans Electr Electron Eng"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-018-6424-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-018-6424-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-018-6424-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,6,26]],"date-time":"2020-06-26T19:31:57Z","timestamp":1593199917000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-018-6424-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,25]]},"references-count":55,"journal-issue":{"issue":"21-22","published-print":{"date-parts":[[2020,6]]}},"alternative-id":["6424"],"URL":"https:\/\/doi.org\/10.1007\/s11042-018-6424-4","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2018,7,25]]},"assertion":[{"value":"1 June 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 June 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 July 2018","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 July 2018","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"We have no conflicts of interest to disclose with regard to the subject matter of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}