{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T20:50:36Z","timestamp":1762375836298},"reference-count":49,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2014,5,23]],"date-time":"2014-05-23T00:00:00Z","timestamp":1400803200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"name":"NIH (T.L)","award":["R01 DA-033393","R01 AG-042599"],"award-info":[{"award-number":["R01 DA-033393","R01 AG-042599"]}]},{"name":"NSF CAREER Award (T.L)","award":["IIS-1149260"],"award-info":[{"award-number":["IIS-1149260"]}]},{"name":"NSF (T.L)","award":["CBET-1302089"],"award-info":[{"award-number":["CBET-1302089"]}]},{"name":"Start-up funding and Sesseel Award from Yale University (J.Z)."}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Human Brain Mapping"],"published-print":{"date-parts":[[2014,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Modeling abnormal temporal dynamics of functional interactions in psychiatric disorders has been of great interest in the neuroimaging field, and thus a variety of methods have been proposed so far. However, the temporal dynamics and disease\u2010related abnormalities of functional interactions within specific data\u2010driven discovered subnetworks have been rarely explored yet. In this work, we propose a novel computational framework composed of an effective Bayesian connectivity change point model for modeling functional brain interactions and their dynamics simultaneously and an effective variant of nonnegative matrix factorization for assessing the functional interaction abnormalities within subnetworks. This framework has been applied on the resting state fmagnetic resonance imaging (fMRI) datasets of 23 children with attention\u2010deficit\/hyperactivity disorder (ADHD) and 45 normal control (NC) children, and has revealed two atomic functional interaction patterns (AFIPs) discovered for ADHD and another two AFIPs derived for NC. Together, these four AFIPs could be grouped into two pairs, one common pair representing the common AFIPs in ADHD and NC, and the other abnormal pair representing the abnormal AFIPs in ADHD. Interestingly, by comparing the abnormal AFIP pair, two data\u2010driven abnormal functional subnetworks are derived. Strikingly, by evaluating the approximation based on the four AFIPs, all of the ADHD children were successfully differentiated from NCs without any false positive. <jats:italic>Hum Brain Mapp 35:5262\u20135278, 2014<\/jats:italic>. \u00a9 <jats:bold>2014 Wiley Periodicals, Inc.<\/jats:bold><\/jats:p>","DOI":"10.1002\/hbm.22548","type":"journal-article","created":{"date-parts":[[2014,5,23]],"date-time":"2014-05-23T11:42:42Z","timestamp":1400845362000},"page":"5262-5278","source":"Crossref","is-referenced-by-count":31,"title":["Atomic dynamic functional interaction patterns for characterization of ADHD"],"prefix":"10.1002","volume":"35","author":[{"given":"Jinli","family":"Ou","sequence":"first","affiliation":[{"name":"School of Biomedical Engineering &amp; Instrument Science, Zhejiang University  Hangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhichao","family":"Lian","sequence":"additional","affiliation":[{"name":"Department of Statistics Yale University New Haven, CT"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering &amp; Instrument Science, Zhejiang University  Hangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiang","family":"Li","sequence":"additional","affiliation":[{"name":"Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center The University of Georgia Athens Georgia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Mental Health, Peking University Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yun","family":"Hao","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Fudan University Shanghai China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dajiang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center The University of Georgia Athens Georgia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongxin","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering &amp; Instrument Science, Zhejiang University  Hangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yufeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Mental Health, Peking University Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaowu","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering &amp; Instrument Science, Zhejiang University  Hangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Statistics Yale University New Haven, CT"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianming","family":"Liu","sequence":"additional","affiliation":[{"name":"Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center The University of Georgia Athens Georgia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2014,5,23]]},"reference":[{"key":"e_1_2_6_2_1","article-title":"Tracking whole\u2010brain connectivity dynamics in the resting state","author":"Allen EA","year":"2012","journal-title":"Cerebral cortex"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1018985108"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0308531101"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2011.11.007"},{"key":"e_1_2_6_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF01246098"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.12.011"},{"key":"e_1_2_6_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejpn.2012.01.009"},{"key":"e_1_2_6_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.01.053"},{"key":"e_1_2_6_10_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972757.70"},{"key":"e_1_2_6_11_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrn2201"},{"key":"e_1_2_6_12_1","doi-asserted-by":"publisher","DOI":"10.1198\/016214502760047131"},{"key":"e_1_2_6_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.460020107"},{"key":"e_1_2_6_14_1","unstructured":"GelmanA CarlinJB SternHS DonaldBR. (2003): Bayesian Data Analysis: Chapman & Hall\/CRC Texts in Statistical Science.London:CRC press."},{"key":"e_1_2_6_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-40811-3_12"},{"key":"e_1_2_6_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2007.05.019"},{"key":"e_1_2_6_17_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1012801612483"},{"key":"e_1_2_6_18_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btn526"},{"key":"e_1_2_6_19_1","doi-asserted-by":"publisher","DOI":"10.1097\/00004583-199707000-00021"},{"key":"e_1_2_6_20_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btm134"},{"key":"e_1_2_6_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpr.2006.01.005"},{"key":"e_1_2_6_22_1","doi-asserted-by":"publisher","DOI":"10.1038\/44565"},{"key":"e_1_2_6_23_1","doi-asserted-by":"crossref","unstructured":"LiT DingC. (2006): The Relationships Among Various Nonnegative Matrix Factorization Methods for Clustering; 18\u201022 Dec. 2006; Data Mining Sixth International Conference on Hongkong ICDM '06. pp.362\u2013371.","DOI":"10.1109\/ICDM.2006.160"},{"key":"e_1_2_6_24_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22290"},{"key":"e_1_2_6_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-012-9157-y"},{"key":"e_1_2_6_26_1","unstructured":"LianZ LiX XingJ LvJ JiangX ZhuD XuJ PotenzaMN LiuT ZhangJ: Exploring functional brain dynamics via a bayesian connectivity change point model; IEEE 11th International Symposium on Biomedical Imaging (ISBI) (in press)."},{"key":"e_1_2_6_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.01.004"},{"key":"e_1_2_6_28_1","volume-title":"Monte Carlo Strategies in Scientific Computing","author":"Liu JS","year":"2008"},{"key":"e_1_2_6_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11682-011-9123-6"},{"key":"e_1_2_6_30_1","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.0333-10.2010"},{"key":"e_1_2_6_31_1","unstructured":"MaechlerM RousseeuwP StruyfA HubertM HornikK. (2012). Cluster: Cluster Analysis Basics and Extensions. R package version. 1(2)."},{"key":"e_1_2_6_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.08.030"},{"key":"e_1_2_6_33_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-7-366"},{"key":"e_1_2_6_34_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrn893"},{"key":"e_1_2_6_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.08.007"},{"key":"e_1_2_6_36_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btp009"},{"key":"e_1_2_6_37_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.98.2.676"},{"key":"e_1_2_6_38_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.08.061"},{"key":"e_1_2_6_39_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176344136"},{"key":"e_1_2_6_40_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1121329109"},{"key":"e_1_2_6_41_1","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9868.00293"},{"key":"e_1_2_6_42_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9780898719574"},{"key":"e_1_2_6_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2041361"},{"key":"e_1_2_6_44_1","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001407005983"},{"key":"e_1_2_6_45_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-012-9165-y"},{"key":"e_1_2_6_46_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33418-4_30"},{"key":"e_1_2_6_47_1","article-title":"Inferring functional interaction and transition patterns via dynamic bayesian variable partition models","author":"Zhang J","journal-title":"Hum Brain Mapp"},{"key":"e_1_2_6_48_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2013.07.003"},{"key":"e_1_2_6_49_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.08.037"},{"key":"e_1_2_6_50_1","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhs072"}],"container-title":["Human Brain Mapping"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fhbm.22548","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/hbm.22548","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/hbm.22548","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/hbm.22548","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T17:13:38Z","timestamp":1693588418000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/hbm.22548"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,5,23]]},"references-count":49,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2014,10]]}},"alternative-id":["10.1002\/hbm.22548"],"URL":"https:\/\/doi.org\/10.1002\/hbm.22548","archive":["Portico"],"relation":{},"ISSN":["1065-9471","1097-0193"],"issn-type":[{"value":"1065-9471","type":"print"},{"value":"1097-0193","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,5,23]]}}}