Systems Factorial Analysis of Item and Associative Retrieval

Gregory E. Cox, Amy H. Criss

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Using hierarchical Bayesian estimation of RT distributions, we present a novel application of Systems Factorial Technology (Townsend & Nozawa, 1995) to the retrieval of item and associative information from episodic memory. We find that item and associative information are retrieved concurrently, with positive memory evidence arising from a holistic match between the test pair and the contents of memory, in which both item and associative matches are pooled together into a single source. This retrieval architecture is inconsistent with both strictly serial processing and independence of item and associative information. Pooling of item and associative matches implies that while item and associative information may be separable, they are not qualitatively different, nor are qualitatively different processes (e.g., familiarity vs. recollection) used to retrieve these kinds of information.

Original languageEnglish (US)
Title of host publicationProceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016
EditorsAnna Papafragou, Daniel Grodner, Daniel Mirman, John C. Trueswell
PublisherThe Cognitive Science Society
Pages1589-1594
Number of pages6
ISBN (Electronic)9780991196739
StatePublished - 2016
Event38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016 - Philadelphia, United States
Duration: Aug 10 2016Aug 13 2016

Publication series

NameProceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016

Conference

Conference38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016
Country/TerritoryUnited States
CityPhiladelphia
Period8/10/168/13/16

Keywords

  • associative recognition
  • Bayesian statistics
  • Memory models
  • systems factorial technology

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

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