Computational modeling of individual differences in short term memory search

2007
journal article
article
cris.lastimport.wos2024-04-10T00:30:09Z
dc.abstract.enModeling of individual or group differences, believed to be a powerful test for computational models, is still rare in current cognitive science. In this paper, we discuss alternative approaches to the computational modeling of both qualitative and quantitative differences among individuals as well as groups of individuals. Then, an example is presented of how accounting for individual differences in short term memory (STM) search can bring us insight into cognitive processes underlying this phenomenon, insight that otherways would be impossible. The two-phase computational model of memory search implements the idea of working memory (WM) focus of attention (FA): due to updating process a few items may be actively kept and easily accessed in ACT-R goal buffer. FA is being scanned serially first, and if the scan result is negative, a parallel chunk retrieval from active part of declarative memory outside the FA may run with certain probability. The model aptly simulates steep decrease in accuracy as well as steep increase in latency for responses to five most recent stimuli. The model also predicts the observed effect of faster negative responses than positive responses to less recent stimuli. Most important, with manipulation to only one of its parameters (i.e., the capacity of FA) our model is able to predict 94% of variance for two groups of participants that differed in latency patterns (i.e., ‘serial-like’ vs. ‘parallel-like’ groups) of the search process.pl
dc.affiliationWydział Filozoficzny : Instytut Psychologiipl
dc.affiliationWydział Filozoficzny : Instytut Filozofiipl
dc.contributor.authorChuderski, Adam - 200113 pl
dc.contributor.authorStettner, Zbigniewpl
dc.contributor.authorOrzechowski, Jarosław - 131195 pl
dc.date.accessioned2016-10-24T06:53:09Z
dc.date.available2016-10-24T06:53:09Z
dc.date.issued2007pl
dc.description.number3pl
dc.description.physical161-173pl
dc.description.volume8pl
dc.identifier.doi10.1016/j.cogsys.2007.06.001pl
dc.identifier.eissn1389-0417pl
dc.identifier.issn2214-4366pl
dc.identifier.urihttp://ruj.uj.edu.pl/xmlui/handle/item/31642
dc.languageengpl
dc.language.containerengpl
dc.rightsDodaję tylko opis bibliograficzny*
dc.rights.licencebez licencji
dc.rights.uri*
dc.subject.enfocus of attentionpl
dc.subject.enshort term memorypl
dc.subject.encomputational modelingpl
dc.subject.enindividual differencespl
dc.subtypeArticlepl
dc.titleComputational modeling of individual differences in short term memory searchpl
dc.title.journalCognitive Systems Researchpl
dc.typeJournalArticlepl
dspace.entity.typePublication
cris.lastimport.wos
2024-04-10T00:30:09Z
dc.abstract.enpl
Modeling of individual or group differences, believed to be a powerful test for computational models, is still rare in current cognitive science. In this paper, we discuss alternative approaches to the computational modeling of both qualitative and quantitative differences among individuals as well as groups of individuals. Then, an example is presented of how accounting for individual differences in short term memory (STM) search can bring us insight into cognitive processes underlying this phenomenon, insight that otherways would be impossible. The two-phase computational model of memory search implements the idea of working memory (WM) focus of attention (FA): due to updating process a few items may be actively kept and easily accessed in ACT-R goal buffer. FA is being scanned serially first, and if the scan result is negative, a parallel chunk retrieval from active part of declarative memory outside the FA may run with certain probability. The model aptly simulates steep decrease in accuracy as well as steep increase in latency for responses to five most recent stimuli. The model also predicts the observed effect of faster negative responses than positive responses to less recent stimuli. Most important, with manipulation to only one of its parameters (i.e., the capacity of FA) our model is able to predict 94% of variance for two groups of participants that differed in latency patterns (i.e., ‘serial-like’ vs. ‘parallel-like’ groups) of the search process.
dc.affiliationpl
Wydział Filozoficzny : Instytut Psychologii
dc.affiliationpl
Wydział Filozoficzny : Instytut Filozofii
dc.contributor.authorpl
Chuderski, Adam - 200113
dc.contributor.authorpl
Stettner, Zbigniew
dc.contributor.authorpl
Orzechowski, Jarosław - 131195
dc.date.accessioned
2016-10-24T06:53:09Z
dc.date.available
2016-10-24T06:53:09Z
dc.date.issuedpl
2007
dc.description.numberpl
3
dc.description.physicalpl
161-173
dc.description.volumepl
8
dc.identifier.doipl
10.1016/j.cogsys.2007.06.001
dc.identifier.eissnpl
1389-0417
dc.identifier.issnpl
2214-4366
dc.identifier.uri
http://ruj.uj.edu.pl/xmlui/handle/item/31642
dc.languagepl
eng
dc.language.containerpl
eng
dc.rights*
Dodaję tylko opis bibliograficzny
dc.rights.licence
bez licencji
dc.rights.uri*
dc.subject.enpl
focus of attention
dc.subject.enpl
short term memory
dc.subject.enpl
computational modeling
dc.subject.enpl
individual differences
dc.subtypepl
Article
dc.titlepl
Computational modeling of individual differences in short term memory search
dc.title.journalpl
Cognitive Systems Research
dc.typepl
JournalArticle
dspace.entity.type
Publication
Affiliations

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