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Memory & Cognition

, Volume 46, Issue 3, pp 450–463 | Cite as

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

  • Rui Cao
  • Richard M. Shiffrin
  • Robert M. Nosofsky
Article

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

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

Notes

Author note

This work was supported by AFOSR Grant FA9550-14-1-0307 to Robert Nosofsky.

References

  1. Anderson, J. R., & Schooler, L. J. (1991). Reflections of the environment in memory. Psychological Science, 2, 396–408.CrossRefGoogle Scholar
  2. Brady, T. F., Konkle, T., Alvarez, G. A., & Oliva, A. (2008). Visual long-term memory has a massive storage capacity for object details. Proceedings of the National Academy of Sciences of the United States of America, 105, 14325–14329.CrossRefPubMedPubMedCentralGoogle Scholar
  3. Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision, 10, 433–436.CrossRefPubMedGoogle Scholar
  4. Donkin, C., & Nosofsky, R. M. (2012a). A power-law model of psychological memory strength in short-and long-term recognition. Psychological Science, 23, 625–634.CrossRefPubMedGoogle Scholar
  5. Donkin, C., & Nosofsky, R. M. (2012b). The structure of short-term memory scanning: An investigation using response time distribution models. Psychonomic Bulletin & Review, 19, 363–394.CrossRefGoogle Scholar
  6. Howard, M. W., & Kahana, M. J. (2002). A distributed representation of temporal context. Journal of Mathematical Psychology, 46, 269–299.CrossRefGoogle Scholar
  7. Logan, G. D. (1988). Toward an instance theory of automatization. Psychological Review, 95, 492–527.CrossRefGoogle Scholar
  8. Logan, G. D. (1990). Repetition priming and automaticity: Common underlying mechanisms?. Cognitive Psychology, 22, 1–35.CrossRefGoogle Scholar
  9. Logan, G. D., & Stadler, M. A. (1991). Mechanisms of performance improvement in consistent mapping memory search: Automaticity or strategy shift. Journal of Experimental Psychology: Learning, Memory, and Cognition, 17(3), 478-496.Google Scholar
  10. McElree, B., & Dosher, B. A. (1989). Serial position and set size in short-term memory: Time course of recognition. Journal of Experimental Psychology: General, 18, 346–373.CrossRefGoogle Scholar
  11. Monsell, S. (1978). Recency, immediate recognition memory, and reaction time. Cognitive Psychology, 10, 465–501.CrossRefGoogle Scholar
  12. Nosofsky, R. M. (2016). An exemplar-retrieval model of short-term memory search: Linking categorization and probe recognition. Psychology of Learning and Motivation, 65, 47–84.CrossRefGoogle Scholar
  13. Nosofsky, R. M., Cao, R., Cox, G. E., & Shiffrin R. M. (2014). Familiarity and categorization processes in memory search. Cognitive Psychology, 75, 97–129.CrossRefPubMedGoogle Scholar
  14. Nosofsky, R. M., Cox, G. E., Cao, R., & Shiffrin, R. M. (2014). An exemplar-familiarity model predicts short-term and long-term probe recognition across diverse forms of memory search. Journal of Experimental Psychology: Learning, Memory, and Cognition, 40, 1524.PubMedGoogle Scholar
  15. Nosofsky, R. M., Little, D. R., Donkin, C., & Fific, M. (2011). Short-term memory scanning viewed as exemplar-based categorization. Psychological Review, 188, 280–315.CrossRefGoogle Scholar
  16. Nosofsky, R. M., & Palmeri, T. J. (1997). An exemplar-based random walk model of speeded classification. Psychological Review, 104, 266–300.CrossRefPubMedGoogle Scholar
  17. Nosofsky, R. M., & Stanton, R. D. (2005). Speeded classification in a probabilistic category structure: Contrasting exemplar-retrieval, decision-boundary, and prototype models. Journal of Experimental Psychology: Human Perception and Performance, 31, 608–629.PubMedGoogle Scholar
  18. Ratcliff, R. (1978). A theory of memory retrieval. Psychological Review, 85, 59–108.CrossRefGoogle Scholar
  19. Schneider, W., & Fisk, A. D. (1982). Degree of consistent training: Improvements in search performance and automatic process development. Perception & Psychophysics, 31, 160–168.CrossRefGoogle Scholar
  20. Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review, 84, 1–66.CrossRefGoogle Scholar
  21. Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theory. Psychological Review, 84, 127–190.CrossRefGoogle Scholar
  22. Sternberg, S. (1966). High-speed scanning in human memory. Science, 153, 652– 654.CrossRefPubMedGoogle Scholar
  23. Sternberg, S. (2016). In defence of high-speed memory scanning. The Quarterly Journal of Experimental Psychology, 69, 2020–2075.CrossRefPubMedGoogle Scholar
  24. Strayer, D. L., & Kramer, A. F. (1994). Strategies and automaticity: I. Basic findings and conceptual framework. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 318–341.Google Scholar
  25. Wixted, J. T., & Ebbesen, E. B. (1991). On the form of forgetting. Psychological Science, 2, 409–415.CrossRefGoogle Scholar
  26. Wolfe, J. M., Boettcher, S. E., Josephs, E. L., Cunningham, C. A., & Drew, T. (2015). You look familiar, but I don’t care: Lure rejection in hybrid visual and memory search is not based on familiarity. Journal of Experimental Psychology: Human Perception and Performance, 41, 1576.PubMedPubMedCentralGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2017

Authors and Affiliations

  • Rui Cao
    • 1
  • Richard M. Shiffrin
    • 1
  • Robert M. Nosofsky
    • 1
  1. 1.Department of Psychological and Brain SciencesIndiana UniversityBloomingtonUSA

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