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Therefore, discovering more precise biological\ninformation from neuroimaging biomarkers is crucial for accurate and automatic detection of AD.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title>Methods:<\/jats:title>\n<jats:p> We innovatively used a Visibility Graph (VG) to construct the time-dependent brain networks\nas well as functional connectivity network to investigate the underlying dynamics of AD brain based on\nfunctional magnetic resonance imaging. There were 32 AD patients and 29 Normal Controls (NCs) from\nthe Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI) database. First, the VG method mapped the\ntime series of single brain region into networks. By extracting topological properties of the networks, the\nmost significant features were selected as discriminant features into a supporting vector machine for\nclassification. Furthermore, in order to detect abnormalities of these brain regions in the whole AD\nbrain, functional connectivity among different brain regions was calculated based on the correlation of\nregional degree sequences.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title>Results:<\/jats:title>\n<jats:p>According to the topology abnormalities exploration of local complex networks, we found several\nabnormal brain regions, including left insular, right posterior cingulate gyrus and other cortical regions.\nThe accuracy of characteristics of the brain regions extracted from local complex networks was\n88.52%. Association analysis demonstrated that the left inferior opercular part of frontal gyrus, right\nmiddle occipital gyrus, right superior parietal gyrus and right precuneus played a tremendous role in\nAD.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title>Conclusion:<\/jats:title>\n<jats:p>These results would be helpful in revealing the underlying pathological mechanism of the\ndisease.<\/jats:p>\n<\/jats:sec>","DOI":"10.2174\/1567205017666200213100607","type":"journal-article","created":{"date-parts":[[2020,2,13]],"date-time":"2020-02-13T16:35:01Z","timestamp":1581611701000},"page":"69-79","update-policy":"https:\/\/doi.org\/10.2174\/bsp_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Disrupted Time-Dependent and Functional Connectivity Brain Network in Alzheimer's Disease: A Resting-State fMRI Study Based on Visibility Graph"],"prefix":"10.2174","volume":"17","author":[{"given":"Zhongke","family":"Gao","sequence":"first","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanhua","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Ma","sequence":"additional","affiliation":[{"name":"Principal Researcher at Tencent, Guangdong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qing","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"family":"and for the Alzheimer\u2019s Disease Neuroimaging Initiative","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"965","reference":[{"key":"ref=1","doi-asserted-by":"publisher","first-page":"6999","DOI":"10.1007\/s12035-016-0224-5","volume":"54","author":"Ma C.","unstructured":"Ma C.; Wang J.; Zhang J.; Chen K.; Li X.; Shu N.; Disrupted brain structural connectivity: pathological interactions between genetic apoe \u03b54 status and developed MCI xondition. 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IEEE Trans Neural Netw Learn Syst (2019).,30(9),2755-2763","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"ref=25","doi-asserted-by":"publisher","first-page":"4972","DOI":"10.1073\/pnas.0709247105","volume":"105","author":"Lacasa L.","unstructured":"Lacasa L.; Luque B.; Ballesteros F.; Luque J.; Nu\u00f1o J.C.; From time series to complex networks: the visibility graph. Proc Natl Acad Sci USA (2008).,105(13),4972-4975","journal-title":"Proc Natl Acad Sci USA"},{"key":"ref=26","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1016\/j.neuroimage.2017.05.047","volume":"156","author":"Yu M.","unstructured":"Yu M.; Hillebrand A.; Gouw A.A.; Stam C.J.; Horizontal visibility graph transfer entropy (HVG-TE): a novel metric to characterize directed connectivity in large-scale brain networks. 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Int J Neural Syst (2017).,27(4)","journal-title":"Int J Neural Syst"},{"key":"ref=29","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065718500570","volume":"29","author":"Cai Q.","unstructured":"Cai Q.; Gao Z.K.; Yang Y.X.; Dang W.D.; Grebogi C.; Multiplex Limited Penetrable Horizontal Visibility Graph from EEG Signals for Driver Fatigue Detection. Int J Neural Syst (2019).,29(5)","journal-title":"Int J Neural Syst"},{"key":"ref=30","doi-asserted-by":"publisher","first-page":"1099","DOI":"10.1007\/s00702-010-0450-3","volume":"117","author":"Ahmadlou M.","unstructured":"Ahmadlou M.; Adeli H.; Adeli A.; New diagnostic EEG markers of the Alzheimer\u2019s disease using visibility graph. J Neural Transm (Vienna) (2010).,117(9),1099-1109","journal-title":"J Neural Transm (Vienna)"},{"key":"ref=31","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1038\/nrn2575","volume":"10","author":"Bullmore E.","unstructured":"Bullmore E.; Sporns O.; Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci (2009).,10(3),186-198","journal-title":"Nat Rev Neurosci"},{"key":"ref=32","doi-asserted-by":"publisher","first-page":"3723","DOI":"10.1093\/cercor\/bhu246","volume":"25","author":"Dai Z.","unstructured":"Dai Z.; Yan C.; Li K.; Wang Z.; Wang J.; Cao M.; Identifying and mapping connectivity patterns of brain network hubs in Alzheimer\u2019s disease. Cereb Cortex (2015).,25(10),3723-3742","journal-title":"Cereb Cortex"},{"key":"ref=33","doi-asserted-by":"publisher","DOI":"10.1209\/0295-5075\/86\/30001","volume":"86","author":"Lacasa L.","unstructured":"Lacasa L.; Luque B.; Luque J.; Nuno J.C.; The visibility graph: a new method for estimating the Hurst exponent of fractional Brownian motion. Epl-Europhys Lett (2009).,86(3)","journal-title":"Epl-Europhys Lett"},{"key":"ref=34","doi-asserted-by":"publisher","first-page":"1059","DOI":"10.1016\/j.neuroimage.2009.10.003","volume":"52","author":"Rubinov M.","unstructured":"Rubinov M.; Sporns O.; Complex network measures of brain connectivity: uses and interpretations. Neuroimage (2010).,52(3),1059-1069","journal-title":"Neuroimage"},{"key":"ref=35","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1080\/15427951.2014.982311","volume":"11","author":"Goel K.","unstructured":"Goel K.; Singh R.R.; Iyengar S.; Gupta S.; A faster algorithm to update betweenness centrality after node alteration. Internet Math (2015).,11(4-5),403-420","journal-title":"Internet Math"},{"key":"ref=36","doi-asserted-by":"publisher","first-page":"77","DOI":"10.3233\/JAD-160447","volume":"55","author":"Chang P.","unstructured":"Chang P.; Li X.; Ma C.; Zhang S.; Liu Z.; Chen K.; The effects of an APOE promoter polymorphism on human white matter connectivity during non-demented aging. 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Spectrochimica Acta Part a-Molecular and Biomolecular Spectroscopy (2020).,22(4)","journal-title":"Spectrochimica Acta Part a-Molecular and Biomolecular Spectroscopy"},{"key":"ref=40","doi-asserted-by":"publisher","DOI":"10.3390\/app8040636","author":"Dai S","year":"(2018).","unstructured":"Dai S; Niu D; Han Y.; Forecasting of Power grid investment in china based on support vector machine optimized by differential evolution algorithm and grey wolf optimization algorithm applied sciences-basel 84 (2018)."},{"key":"ref=41","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/j.neucom.2016.10.041","volume":"228","author":"Cervantes J.","unstructured":"Cervantes J.; Garcia-Lamont F.; Rodriguez-Mazahua L.; Lopez A.; Ruiz-Castilla J.; Trueba A.; PSO-based method for SVM classification on skewed data sets. Neurocomputing (2017).,228,187-197","journal-title":"Neurocomputing"},{"key":"ref=42","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199","volume":"2","author":"Chang C-C.","unstructured":"Chang C-C.; Lin C-J.; LIBSVM: A Library for Support Vector Machines. ACM Trans Intell Syst Technol (2011).,2(3)","journal-title":"ACM Trans Intell Syst Technol"},{"key":"ref=43","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.physa.2016.05.012","volume":"460","author":"Wang J","unstructured":"Wang J; Yang C; Wang RF; Yu HT; Cao YB; Liu J; Functional brain networks in Alzheimer's disease: EEG analysis based on limited penetrable visibility graph and phase space method. Physica a-Statistical Mechanics App (2016).,460,174-87","journal-title":"Physica a-Statistical Mechanics App"},{"key":"ref=44","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1126\/science.1135926","volume":"315","author":"Naqvi N.H.","unstructured":"Naqvi N.H.; Rudrauf D.; Damasio H.; Bechara A.; Damage to the insula disrupts addiction to cigarette smoking. Science (2007).,315(5811),531-534","journal-title":"Science"},{"key":"ref=45","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1007\/s00429-010-0255-z","volume":"214","author":"Kurth F.","unstructured":"Kurth F.; Zilles K.; Fox P.T.; Laird A.R.; Eickhoff S.B.; A link between the systems: functional differentiation and integration within the human insula revealed by meta-analysis. Brain Struct Funct (2010).,214(5-6),519-534","journal-title":"Brain Struct Funct"},{"key":"ref=46","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1177\/0284185114533329","volume":"56","author":"Zhao Z-L.","unstructured":"Zhao Z-L.; Fan F-M.; Lu J.; Li H-J.; Jia L-F.; Han Y.; Changes of gray matter volume and amplitude of low-frequency oscillations in amnestic MCI: An integrative multi-modal MRI study. Acta Radiol (2015).,56(5),614-621","journal-title":"Acta Radiol"},{"key":"ref=47","doi-asserted-by":"publisher","first-page":"708","DOI":"10.1016\/j.neuroimage.2004.07.006","volume":"23","author":"Karas G.B.","unstructured":"Karas G.B.; Scheltens P.; Rombouts S.A.; Visser P.J.; van Schijndel R.A.; Fox N.C.; Global and local gray matter loss in mild cognitive impairment and Alzheimer\u2019s disease. Neuroimage (2004).,23(2),708-716","journal-title":"Neuroimage"},{"key":"ref=48","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1007\/s00401-006-0127-z","volume":"112","author":"Braak H.","unstructured":"Braak H.; Alafuzoff I.; Arzberger T.; Kretzschmar H.; Del Tredici K.; Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol (2006).,112(4),389-404","journal-title":"Acta Neuropathol"},{"key":"ref=49","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1007\/s12013-014-0138-7","volume":"71","author":"He W.","unstructured":"He W.; Liu D.; Radua J.; Li G.; Han B.; Sun Z.; Meta-analytic comparison between PIB-PET and FDG-PET results in Alzheimer\u2019s disease and MCI. Cell Biochem Biophys (2015).,71(1),17-26","journal-title":"Cell Biochem Biophys"},{"key":"ref=50","doi-asserted-by":"publisher","first-page":"320","DOI":"10.1016\/j.neuroimage.2012.06.062","volume":"63","author":"Xie C.","unstructured":"Xie C.; Bai F.; Yu H.; Shi Y.; Yuan Y.; Chen G.; Abnormal insula functional network is associated with episodic memory decline in amnestic mild cognitive impairment. Neuroimage (2012).,63(1),320-327","journal-title":"Neuroimage"},{"key":"ref=51","doi-asserted-by":"publisher","first-page":"2349","DOI":"10.1523\/JNEUROSCI.5587-06.2007","volume":"27","author":"Seeley W.W.","unstructured":"Seeley W.W.; Menon V.; Schatzberg A.F.; Keller J.; Glover G.H.; Kenna H.; Dissociable intrinsic connectivity networks for salience processing and executive control. 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