{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T18:48:15Z","timestamp":1791312495095,"version":"4.3.1"},"reference-count":29,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","jocn-journal.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Clinical Neuroscience"],"published-print":{"date-parts":[[2021,9]]},"DOI":"10.1016\/j.jocn.2021.07.016","type":"journal-article","created":{"date-parts":[[2021,7,26]],"date-time":"2021-07-26T12:34:27Z","timestamp":1627302867000},"page":"276-282","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":33,"special_numbering":"C","title":["Graph-theory based degree centrality combined with machine learning algorithms can predict response to treatment with antiepileptic medications in children with epilepsy"],"prefix":"10.1016","volume":"91","author":[{"given":"Xueyu","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tian","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongmei","family":"Jiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yibing","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Libo","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.jocn.2021.07.016_b0005","unstructured":"Knox AT, Glauser T, Tenney J, Lytton WW, Holland K. Modeling pathogenesis and treatment response in childhood absence epilepsy. Epilepsia."},{"key":"10.1016\/j.jocn.2021.07.016_b0010","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1111\/epi.14067","article-title":"Ictal connectivity in childhood absence epilepsy: associations with outcome","volume":"59","author":"Tenney","year":"2018","journal-title":"Epilepsia"},{"key":"10.1016\/j.jocn.2021.07.016_b0015","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.jns.2016.12.054","article-title":"Altered degree centrality in childhood absence epilepsy: a resting-state fMRI study","volume":"373","author":"Wang","year":"2017","journal-title":"J Neurol Sci"},{"key":"10.1016\/j.jocn.2021.07.016_b0020","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1002\/mrm.1910340409","article-title":"Functional connectivity in the motor cortex of resting human brain using echo-planar MRI","volume":"34","author":"Biswal","year":"1995","journal-title":"Magn Reson Med"},{"key":"10.1016\/j.jocn.2021.07.016_b0025","doi-asserted-by":"crossref","first-page":"1860","DOI":"10.1523\/JNEUROSCI.5062-08.2009","article-title":"Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer's disease","volume":"29","author":"Buckner","year":"2009","journal-title":"J Neurosci"},{"key":"10.1016\/j.jocn.2021.07.016_b0030","doi-asserted-by":"crossref","unstructured":"Sporns O, Honey CJ, K\u00f6tter R. Identification and classification of hubs in brain networks. PloS one. 2007;2:e1049.","DOI":"10.1371\/journal.pone.0001049"},{"key":"10.1016\/j.jocn.2021.07.016_b0035","doi-asserted-by":"crossref","unstructured":"Hwang H, Kim H, Kim SH, Kim SH, Lim BC, Chae J-H, et al. Long-term effectiveness of ethosuximide, valproic acid, and lamotrigine in childhood absence epilepsy.34:344-8.","DOI":"10.1016\/j.braindev.2011.08.007"},{"key":"10.1016\/j.jocn.2021.07.016_b0040","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1089\/brain.2019.0702","article-title":"Graph theory analysis of functional connectivity combined with machine learning approaches demonstrates widespread network differences and predicts clinical variables in temporal lobe epilepsy","volume":"10","author":"Mazrooyisebdani","year":"2020","journal-title":"Brain Connect"},{"key":"10.1016\/j.jocn.2021.07.016_b0045","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11684-019-0733-5","article-title":"Machine learning for detecting mesial temporal lobe epilepsy by structural and functional neuroimaging","author":"Zhou","year":"2020","journal-title":"Front Med"},{"key":"10.1016\/j.jocn.2021.07.016_b0050","doi-asserted-by":"crossref","first-page":"1221","DOI":"10.1111\/epi.16540","article-title":"Functional connectome contractions in temporal lobe epilepsy: microstructural underpinnings and predictors of surgical outcome","volume":"61","author":"Larivi\u00e8re","year":"2020","journal-title":"Epilepsia"},{"key":"10.1016\/j.jocn.2021.07.016_b0055","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.yebeh.2019.04.006","article-title":"Prediction of antiepileptic drug treatment outcomes of patients with newly diagnosed epilepsy by machine learning","volume":"96","author":"Yao","year":"2019","journal-title":"Epilepsy Behav"},{"key":"10.1016\/j.jocn.2021.07.016_b0060","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.jns.2016.12.054","article-title":"Altered degree centrality in childhood absence epilepsy: a resting-state fMRI study","volume":"373","author":"Wang","year":"2017","journal-title":"J Neurol Sci"},{"key":"10.1016\/j.jocn.2021.07.016_b0065","doi-asserted-by":"crossref","unstructured":"Song K, Li J, Zhu Y, Ren F, Cao L, Huang ZG. Altered Small-World Functional Network Topology in Patients with Optic Neuritis: A Resting-State fMRI Study. Dis Markers. 2021 Jun 14;2021:9948751. doi: 10.1155\/2021\/9948751. PMID: 34221189; PMCID: PMC8219459.","DOI":"10.1155\/2021\/9948751"},{"key":"10.1016\/j.jocn.2021.07.016_b0070","doi-asserted-by":"crossref","first-page":"3265","DOI":"10.1002\/hbm.24596","article-title":"Neural correlates of dynamic changes in working memory performance during one night of sleep deprivation","volume":"40","author":"Zhu","year":"2019","journal-title":"Hum Brain Mapp"},{"key":"10.1016\/j.jocn.2021.07.016_b0075","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1007\/s12021-013-9178-1","article-title":"PRoNTo: pattern recognition for neuroimaging toolbox","volume":"11","author":"Schrouff","year":"2013","journal-title":"Neuroinformatics"},{"key":"10.1016\/j.jocn.2021.07.016_b0080","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1038\/nrn3214","article-title":"The economy of brain network organization","volume":"13","author":"Bullmore","year":"2012","journal-title":"Nat Rev Neurosci"},{"key":"10.1016\/j.jocn.2021.07.016_b0085","doi-asserted-by":"crossref","first-page":"1929","DOI":"10.1073\/pnas.1214900110","article-title":"Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain","volume":"110","author":"Liang","year":"2013","journal-title":"Proc Natl Acad Sci"},{"key":"10.1016\/j.jocn.2021.07.016_b0090","doi-asserted-by":"crossref","first-page":"694","DOI":"10.1016\/j.neuroimage.2008.12.066","article-title":"Mapping functional connectivity based on synchronized CMRO2 fluctuations during the resting state","volume":"45","author":"Wu","year":"2009","journal-title":"Neuroimage"},{"key":"10.1016\/j.jocn.2021.07.016_b0095","doi-asserted-by":"crossref","first-page":"13642","DOI":"10.1073\/pnas.1303346110","article-title":"Energetic cost of brain functional connectivity","volume":"110","author":"Tomasi","year":"2013","journal-title":"Proc Natl Acad Sci"},{"key":"10.1016\/j.jocn.2021.07.016_b0100","doi-asserted-by":"crossref","first-page":"1380","DOI":"10.1111\/epi.12733","article-title":"Improved mapping of interictal epileptiform discharges with EEG-f MRI and voxel-wise functional connectivity analysis","volume":"55","author":"Liu","year":"2014","journal-title":"Epilepsia"},{"key":"10.1016\/j.jocn.2021.07.016_b0105","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1111\/jsr.12582","article-title":"Dynamics of cerebral responses to sustained attention performance during one night of sleep deprivation","volume":"27","author":"Zhu","year":"2018","journal-title":"J Sleep Res"},{"key":"10.1016\/j.jocn.2021.07.016_b0110","doi-asserted-by":"crossref","unstructured":"Li Q, Cao W, Liao X, Chen Z, Yang T, Gong Q, et al. Altered resting state functional network connectivity in children absence epilepsy. J Neurol Sci. 354:79-85.","DOI":"10.1016\/j.jns.2015.04.054"},{"key":"10.1016\/j.jocn.2021.07.016_b0115","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1001\/archneur.62.3.371","article-title":"Evolving concepts on the pathophysiology of absence seizures: the cortical focus theory","volume":"62","author":"Meeren","year":"2005","journal-title":"Arch Neurol"},{"key":"10.1016\/j.jocn.2021.07.016_b0120","doi-asserted-by":"crossref","first-page":"31","DOI":"10.3389\/fneur.2014.00031","article-title":"The role of functional neuroimaging in pre-surgical epilepsy evaluation","volume":"5","author":"Pittau","year":"2014","journal-title":"Front Neurol"},{"key":"10.1016\/j.jocn.2021.07.016_b0125","doi-asserted-by":"crossref","unstructured":"Pardoe H, Pell GS, Abbott DF, Berg AT, Jackson GD. Multi-site voxel-based morphometry: methods and a feasibility demonstration with childhood absence epilepsy. Neuroimage.42:611-6.","DOI":"10.1016\/j.neuroimage.2008.05.007"},{"key":"10.1016\/j.jocn.2021.07.016_b0130","doi-asserted-by":"crossref","unstructured":"Chan CH, Briellmann RS, Pell GS, Scheffer IE, Abbott DF, Jackson GD. Thalamic atrophy in childhood absence epilepsy. 2006.","DOI":"10.1111\/j.1528-1167.2006.00435.x"},{"key":"10.1016\/j.jocn.2021.07.016_b0135","doi-asserted-by":"crossref","unstructured":"Yang T, Guo Z, Luo C, Li Q, Yan B, Liu L, et al. White matter impairment in the basal ganglia-thalamocortical circuit of drug-na?ve childhood absence epilepsy.99:267-73.","DOI":"10.1016\/j.eplepsyres.2011.12.006"},{"key":"10.1016\/j.jocn.2021.07.016_b0140","doi-asserted-by":"crossref","unstructured":"Yi, Shao, Feng-Qin, Cai, Yu-Lin, Zhong, et al. Altered intrinsic regional spontaneous brain activity in patients with optic neuritis: a resting-state functional magnetic resonance imaging study. Neuropsych Dis Treatent. 2015.","DOI":"10.2147\/NDT.S92968"},{"key":"10.1016\/j.jocn.2021.07.016_b0145","article-title":"Dynamic functional MRI study of absence seizures. Chinese","author":"Zhang","year":"2013","journal-title":"J Magn Reson Imaging"}],"container-title":["Journal of Clinical Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0967586821003672?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0967586821003672?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,18]],"date-time":"2025-10-18T21:28:55Z","timestamp":1760822935000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0967586821003672"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9]]},"references-count":29,"alternative-id":["S0967586821003672"],"URL":"https:\/\/doi.org\/10.1016\/j.jocn.2021.07.016","relation":{},"ISSN":["0967-5868"],"issn-type":[{"value":"0967-5868","type":"print"}],"subject":[],"published":{"date-parts":[[2021,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Graph-theory based degree centrality combined with machine learning algorithms can predict response to treatment with antiepileptic medications in children with epilepsy","name":"articletitle","label":"Article Title"},{"value":"Journal of Clinical Neuroscience","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jocn.2021.07.016","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}]}}