{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T08:33:35Z","timestamp":1780389215912,"version":"3.54.1"},"reference-count":64,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2019,4,7]],"date-time":"2019-04-07T00:00:00Z","timestamp":1554595200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["DA031292-01, DA10218, DA11434, DA023203"],"award-info":[{"award-number":["DA031292-01, DA10218, DA11434, DA023203"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Neuroscience Research"],"published-print":{"date-parts":[[2019,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Static functional connectivity (FC) analyses based on functional magnetic resonance imaging (fMRI) data have been extensively explored for studying various psychiatric conditions in the brain, including cocaine addiction. A recently emerging, more powerful technique, dynamic functional connectivity (DFC), studies how the FC dynamics change during the course of the fMRI experiments. The aim in this paper was to develop a computational approach, using a machine learning framework, to determine if DFC features were more successful than FC features in the classification of cocaine\u2010dependent patients and healthy controls. fMRI data were obtained from of 25 healthy and 58 cocaine\u2010dependent participants while performing a motor response inhibition task, stop signal task. Group independent component analysis was carried out on all participant data to compute spatially independent components (ICs). Eight ICs were selected manually as relevant brain networks, which were used to classify healthy versus cocaine\u2010dependent participants. FC and DFC measures of the chosen IC pairs were used as features for the classification algorithm. Support Vector Machines were used for both feature selection\/reduction and participant classification. Based on DFC with only seven IC pairs, participants were successfully classified with 95% accuracy (and with 90% accuracy with three IC pairs), whereas static FC yielded only 81% accuracy. Visual, sensorimotor, default mode, and executive control networks, amygdala, and insula played the most significant role in the DFC\u2010based classification. These findings support the use of DFC\u2010based classification of fMRI data as a potential biomarker for the identification of cocaine dependence.<\/jats:p>","DOI":"10.1002\/jnr.24421","type":"journal-article","created":{"date-parts":[[2019,4,8]],"date-time":"2019-04-08T04:34:55Z","timestamp":1554698095000},"page":"790-803","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Classification of cocaine\u2010dependent participants with dynamic functional connectivity from functional magnetic resonance imaging data"],"prefix":"10.1002","volume":"97","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2056-077X","authenticated-orcid":false,"given":"Unal","family":"Sakoglu","sequence":"first","affiliation":[{"name":"Computer Engineering University of Houston \u2013 Clear Lake Houston Texas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mutlu","family":"Mete","sequence":"additional","affiliation":[{"name":"Department of Computer Science Texas A&amp;M University \u2013 Commerce Commerce Texas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Esquivel","sequence":"additional","affiliation":[{"name":"Department of Computer Science Texas A&amp;M University \u2013 Commerce Commerce Texas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katya","family":"Rubia","sequence":"additional","affiliation":[{"name":"Institute of Psychiatry King\u2019s College London London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Briggs","sequence":"additional","affiliation":[{"name":"Department of Radiology University of Texas Southwestern Medical Center Dallas Texas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bryon","family":"Adinoff","sequence":"additional","affiliation":[{"name":"Department of Psychiatry University of Texas Southwestern Medical Center Dallas Texas"},{"name":"VA North Texas Health Care System Dallas Texas"},{"name":"School of Medicine University of Colorado Denver Colorado"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2019,4,7]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/9781119998938.ch11"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/npp.2013.119"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhs352"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pneurobio.2013.06.005"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.12.001"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.20204"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.1048"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10484-005-6384-0"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.3389\/neuro.09.017.2009"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.10.057"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1038\/sj.npp.1300543"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2006.01.021"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1111\/adb.12011"},{"key":"e_1_2_9_16_1","unstructured":"Esquivel J. Mete M. &Sakoglu U.(2013).Software for analyzing brain\u2019s dynamic functional connectivity from fMRI data. Paper presented at the IEEE Annual Medical Device Symposium."},{"key":"e_1_2_9_17_1","unstructured":"Esquivel J. Mete M. &Sakoglu U.(2014).DynaConn: Dynamic functional connectivity toolbox for fMRI. Retrieved fromhttp:\/\/www.drsakoglu.com\/p\/dynaconndfctoolbox.html"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bth261"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awx036"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1012487302797"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22386"},{"key":"e_1_2_9_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.drugalcdep.2018.09.013"},{"key":"e_1_2_9_23_1","doi-asserted-by":"publisher","DOI":"10.1001\/archgenpsychiatry.2009.2"},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.05.079"},{"key":"e_1_2_9_25_1","doi-asserted-by":"publisher","DOI":"10.1006\/nimg.2002.1132"},{"key":"e_1_2_9_26_1","doi-asserted-by":"publisher","DOI":"10.1038\/npp.2013.314"},{"key":"e_1_2_9_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.09.007"},{"key":"e_1_2_9_28_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamapsychiatry.2013.4091"},{"key":"e_1_2_9_29_1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1522-2594(200001)43:1<45::AID-MRM6>3.0.CO;2-0"},{"key":"e_1_2_9_30_1","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.3188-14.2015"},{"key":"e_1_2_9_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.06.052"},{"key":"e_1_2_9_32_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0186774"},{"key":"e_1_2_9_33_1","doi-asserted-by":"publisher","DOI":"10.1080\/17470218.2015.1008020"},{"key":"e_1_2_9_34_1","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.2018.17040415"},{"key":"e_1_2_9_35_1","doi-asserted-by":"publisher","DOI":"10.1111\/adb.12448"},{"key":"e_1_2_9_36_1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0193(1998)6:3<160::AID-HBM5>3.0.CO;2-1"},{"key":"e_1_2_9_37_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2014.00425"},{"key":"e_1_2_9_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.159"},{"issue":"1","key":"e_1_2_9_39_1","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1093\/brain\/107.1.328","article-title":"Localization of function in the cerebral cortex. Past, present and future","volume":"107","author":"Phillips C. G.","year":"1984","journal-title":"Brain"},{"key":"e_1_2_9_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.12.061"},{"key":"e_1_2_9_41_1","doi-asserted-by":"publisher","DOI":"10.1111\/add.12666"},{"key":"e_1_2_9_42_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1369-1600.2012.00446.x"},{"key":"e_1_2_9_43_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.drugalcdep.2013.04.008"},{"key":"e_1_2_9_44_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.drugalcdep.2013.02.009"},{"key":"e_1_2_9_45_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1053-8119(03)00275-1"},{"key":"e_1_2_9_46_1","unstructured":"Sakoglu U. &Bohra K.(2013).Effect of task\u2010related signal variance on functional connectivity: An FMRI simulation study.Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM) Annual Meeting."},{"key":"e_1_2_9_47_1","unstructured":"Sakoglu U. &Calhoun V. D.(2009).Dynamic windowing reveals task\u2010modulation of functional connectivity in schizophrenia patients vs healthy controls. Paper presented at the Proceedings 17th Scientific Meeting International Society for Magnetic Resonance in Medicine Honolulu."},{"key":"e_1_2_9_48_1","doi-asserted-by":"crossref","unstructured":"Sako\u011flu \u00dc. &Calhoun V. D.(2009).Temporal dynamics of functional network connectivity at rest: A comparison of schizophrenia patients and healthy controls. Paper presented at the Proceedings of the 15th Annual Meeting of the Organization for Human Brain Mapping (OHBM) San Francisco CA.","DOI":"10.1016\/S1053-8119(09)71811-7"},{"key":"e_1_2_9_49_1","doi-asserted-by":"crossref","unstructured":"Sako\u011flu \u00dc. Michael A. M. &Calhoun V. D.(2009).Classification of schizophrenia patients vs healthy controls with dynamic functional network connectivity. Paper presented at the Proceedings of the 15th Annual Meeting of the Organization for Human Brain Mapping (OHBM) San Francisco CA.","DOI":"10.1016\/S1053-8119(09)70216-2"},{"key":"e_1_2_9_50_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10334-010-0197-8"},{"key":"e_1_2_9_51_1","doi-asserted-by":"publisher","DOI":"10.1007\/s002130100917"},{"key":"e_1_2_9_52_1","doi-asserted-by":"publisher","DOI":"10.1080\/17470210801994971"},{"key":"e_1_2_9_53_1","doi-asserted-by":"publisher","DOI":"10.1037\/a0013170"},{"key":"e_1_2_9_54_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2008.07.005"},{"key":"e_1_2_9_55_1","doi-asserted-by":"publisher","DOI":"10.1002\/brb3.809"},{"key":"e_1_2_9_56_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.03.038"},{"key":"e_1_2_9_57_1","doi-asserted-by":"publisher","DOI":"10.1038\/npp.2017.280"},{"key":"e_1_2_9_58_1","volume-title":"Probability & statistics for engineers & scientists","author":"Walpole R.","year":"2012"},{"key":"e_1_2_9_59_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.drugalcdep.2018.07.037"},{"key":"e_1_2_9_60_1","doi-asserted-by":"publisher","DOI":"10.1037\/a0029092"},{"key":"e_1_2_9_61_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.21197"},{"key":"e_1_2_9_62_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41398-018-0164-0"},{"key":"e_1_2_9_63_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22819"},{"key":"e_1_2_9_64_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2018.00344"},{"key":"e_1_2_9_65_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2018.03.016"}],"container-title":["Journal of Neuroscience Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jnr.24421","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/jnr.24421","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jnr.24421","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,10]],"date-time":"2023-09-10T08:12:43Z","timestamp":1694333563000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/jnr.24421"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,7]]},"references-count":64,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2019,7]]}},"alternative-id":["10.1002\/jnr.24421"],"URL":"https:\/\/doi.org\/10.1002\/jnr.24421","archive":["Portico"],"relation":{},"ISSN":["0360-4012","1097-4547"],"issn-type":[{"value":"0360-4012","type":"print"},{"value":"1097-4547","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,7]]},"assertion":[{"value":"2018-10-21","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-03-11","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-04-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}