Computational modeling of the negative priming effect based on inhibition patterns and working memory

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dc.contributor.authorChung, Dongilko
dc.contributor.authorRaz, Amirko
dc.contributor.authorLee, Jaewonko
dc.contributor.authorJeong, Jaeseungko
dc.date.accessioned2014-11-25T05:36:46Z-
dc.date.available2014-11-25T05:36:46Z-
dc.date.created2013-11-22-
dc.date.created2013-11-22-
dc.date.issued2013-11-
dc.identifier.citationFRONTIERS IN COMPUTATIONAL NEUROSCIENCE, v.7-
dc.identifier.issn1662-5188-
dc.identifier.urihttp://hdl.handle.net/10203/191133-
dc.description.abstractNegative priming (NP), slowing down of the response for target stimuli that have been previously exposed, but ignored, has been reported in multiple psychological paradigms including the Stroop task. Although NP likely results from the interplay of selective attention, episodic memory retrieval, working memory, and inhibition mechanisms, a comprehensive theoretical account of NP is currently unavailable. This lacuna may result from the complexity of stimuli combinations in NP. Thus, we aimed to investigate the presence of different degrees of the NP effect according to prime-probe combinations within a classic Stroop task. We recorded reaction times (RTs) from 66 healthy participants during Stroop task performance and examined three different NP subtypes, defined according to the type of the Stroop probe in prime probe pairs. Our findings show significant RT differences among NP subtypes that a reputatively due to the presence of differential disinhibition, i.e., release from inhibition. Among the several potential origins for differential subtypes of NP, we investigated the involvement of selective attention and/or working memory using a parallel distributed processing (PDP) model (employing selective at tention only) and a modified PDP model with working memory (PDP-WM, employing both selective attention and working memory). Our findings demonstrate that, unlike the conventional PDP model, the PDP-WM successfully simulates different levels of NP effects that closely follow the behavioral data. This outcome suggests that working memory engages in the reaccumulation of the evidence for target response and induces differential NP effects. Our computational model complements earlier efforts and may pave the road to further insights into an integrated theoretical account of complex NP effects.-
dc.languageEnglish-
dc.publisherFRONTIERS RESEARCH FOUNDATION-
dc.subjectOBSESSIVE-COMPULSIVE DISORDER-
dc.subjectREDUCED COGNITIVE INHIBITION-
dc.subjectPREFRONTAL CORTEX-
dc.subjectSELECTIVE ATTENTION-
dc.subjectINDIVIDUAL-DIFFERENCES-
dc.subjectDISTRACTOR INHIBITION-
dc.subjectSTIMULUS REPETITION-
dc.subjectSTROOP INTERFERENCE-
dc.subjectEPISODIC MEMORY-
dc.subjectVISUAL MEMORY-
dc.titleComputational modeling of the negative priming effect based on inhibition patterns and working memory-
dc.typeArticle-
dc.identifier.wosid000327819100001-
dc.identifier.scopusid2-s2.0-84888411542-
dc.type.rimsART-
dc.citation.volume7-
dc.citation.publicationnameFRONTIERS IN COMPUTATIONAL NEUROSCIENCE-
dc.identifier.doi10.3389/fncom.2013.00166-
dc.contributor.localauthorJeong, Jaeseung-
dc.contributor.nonIdAuthorChung, Dongil-
dc.contributor.nonIdAuthorRaz, Amir-
dc.contributor.nonIdAuthorLee, Jaewon-
dc.description.isOpenAccessY-
dc.type.journalArticleArticle-
dc.subject.keywordAuthornegative priming-
dc.subject.keywordAuthordisinhibition-
dc.subject.keywordAuthorStroop task-
dc.subject.keywordAuthorworking memory-
dc.subject.keywordAuthorparallel distributed processing-
dc.subject.keywordPlusOBSESSIVE-COMPULSIVE DISORDER-
dc.subject.keywordPlusREDUCED COGNITIVE INHIBITION-
dc.subject.keywordPlusPREFRONTAL CORTEX-
dc.subject.keywordPlusSELECTIVE ATTENTION-
dc.subject.keywordPlusINDIVIDUAL-DIFFERENCES-
dc.subject.keywordPlusDISTRACTOR INHIBITION-
dc.subject.keywordPlusSTIMULUS REPETITION-
dc.subject.keywordPlusSTROOP INTERFERENCE-
dc.subject.keywordPlusEPISODIC MEMORY-
dc.subject.keywordPlusVISUAL MEMORY-
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