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dc.contributor.authorSengor, N. S.
dc.contributor.authorGurvit, H.
dc.contributor.authorGuzelis, C.
dc.contributor.authorKaplan, G. Buyukaksoy
dc.date.accessioned2021-03-05T20:44:09Z
dc.date.available2021-03-05T20:44:09Z
dc.identifier.citationKaplan G. B. , Sengor N. S. , Gurvit H., Guzelis C., "Modelling the Stroop effect: A connectionist approach", NEUROCOMPUTING, cilt.70, ss.1414-1423, 2007
dc.identifier.issn0925-2312
dc.identifier.othervv_1032021
dc.identifier.otherav_d5999ad6-faed-4de4-b2ba-e0e2fd02c17e
dc.identifier.urihttp://hdl.handle.net/20.500.12627/140938
dc.identifier.urihttps://doi.org/10.1016/j.neucom.2006.05.009
dc.description.abstractA connectionist model, which simulates the operation of prefrontal circuits during Stroop task is proposed. The Stroop test has traditionally been used as a measure of cognitive inhibition. The task is to inhibit an over-learned, habitual response (i.e., reading color words) in favor of an unusual, novel requirement (i.e., naming incongruously printed colors of color words). The longer durations in completing the task indicate an inability to inhibit habitual but contextually inappropriate response tendencies, which is suggestive of a prefrontal dysfunction. The connectionist model is designed adapting artificial neural networks (ANNs) in such a way that each ANN corresponds to a particular neuroanatomic component of the prefrontal circuit which is likely to take part in the execution of the Stroop task. The ability of the proposed model to simulate the normal and the abnormal performance on the Stroop task is tested. The simulation results show that the model is consistent with the clinical data. (c) 2006 Elsevier B.V. All rights reserved.
dc.language.isoeng
dc.subjectMühendislik ve Teknoloji
dc.subjectAlgoritmalar
dc.subjectBilgisayar Bilimleri
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectBilgisayar Bilimi
dc.subjectBİLGİSAYAR BİLİMİ, YAPAY ZEKA
dc.titleModelling the Stroop effect: A connectionist approach
dc.typeMakale
dc.relation.journalNEUROCOMPUTING
dc.contributor.department, ,
dc.identifier.volume70
dc.identifier.startpage1414
dc.identifier.endpage1423
dc.contributor.firstauthorID182210


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