Literature DB >> 29264863

Item frequency in probe-recognition memory search: Converging evidence for a role of item-response learning.

Rui Cao1, Richard M Shiffrin1, Robert M Nosofsky2.   

Abstract

In short-term probe-recognition tasks, observers make speeded old-new recognition judgments for items that are members of short lists. However, long-term memory (LTM) for items from previous lists influences current-list performance. The current experiment pursued the nature of these long-term influences-in particular, whether they emerged from item-familiarity or item-response-learning mechanisms. Subjects engaged in varied-mapping (VM) and consistent-mapping (CM) short-term probe-recognition tasks (e.g., Schneider & Shiffrin, Psychological Review, 84, 1-66, 1977). The key manipulation was to vary the frequency with which individual items were presented across trials. We observed a striking dissociation: Whereas increased presentation frequency led to benefits in performance for both old and new test probes in CM search, it resulted in interference effects for both old and new test probes in VM search. Formal modeling suggested that a form of item-response learning took place in both conditions: Each presentation of a test probe led to the storage of that test probe-along with its associated "old" or "new" response-as an exemplar in LTM. These item-response pairs were retrieved along with current-list items in driving observers' old-- recognition judgments. We conclude that item-response learning is a core component of the LTM mechanisms that influence CM and VM memory search.

Keywords:  Computational modeling; Long term memory; Memory search; Response times; Short-term probe recognition

Mesh:

Year:  2018        PMID: 29264863     DOI: 10.3758/s13421-017-0777-1

Source DB:  PubMed          Journal:  Mem Cognit        ISSN: 0090-502X


  13 in total

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Authors:  Robert M Nosofsky; Roger D Stanton
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4.  Short-term memory scanning viewed as exemplar-based categorization.

Authors:  Robert M Nosofsky; Daniel R Little; Christopher Donkin; Mario Fific
Journal:  Psychol Rev       Date:  2011-04       Impact factor: 8.934

5.  The Psychophysics Toolbox.

Authors:  D H Brainard
Journal:  Spat Vis       Date:  1997

6.  An exemplar-based random walk model of speeded classification.

Authors:  R M Nosofsky; T J Palmeri
Journal:  Psychol Rev       Date:  1997-04       Impact factor: 8.934

7.  Familiarity and categorization processes in memory search.

Authors:  Robert M Nosofsky; Rui Cao; Gregory E Cox; Richard M Shiffrin
Journal:  Cogn Psychol       Date:  2014-09-18       Impact factor: 3.468

Review 8.  In defence of high-speed memory scanning.

Authors:  Saul Sternberg
Journal:  Q J Exp Psychol (Hove)       Date:  2016-10       Impact factor: 2.143

9.  You look familiar, but I don't care: Lure rejection in hybrid visual and memory search is not based on familiarity.

Authors:  Jeremy M Wolfe; Sage E P Boettcher; Emilie L Josephs; Corbin A Cunningham; Trafton Drew
Journal:  J Exp Psychol Hum Percept Perform       Date:  2015-07-20       Impact factor: 3.332

10.  Visual long-term memory has a massive storage capacity for object details.

Authors:  Timothy F Brady; Talia Konkle; George A Alvarez; Aude Oliva
Journal:  Proc Natl Acad Sci U S A       Date:  2008-09-11       Impact factor: 11.205

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