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Theoretical note: Exploring Luce's (1963) low-threshold model applied to recognition memory.

Ryan M McAdoo1, Scott D Gronlund1

  • 1Department of Psychology.

Journal of Experimental Psychology. Learning, Memory, and Cognition
|June 14, 2019
PubMed
Summary
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Recognition memory may involve both discrete and continuous processes. This study shows that Luce's low-threshold model (discrete) and signal detection theory (continuous) both explain recognition data, but for different memory strengths.

Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Memory Research

Background:

  • The mediation of recognition memory by discrete versus continuous processes remains a significant debate in cognitive psychology.
  • Luce's low-threshold model, a discrete process model, has been historically overlooked but quantitatively matches data previously thought to support continuous models like signal detection theory.
  • Previous research indicated quantitative equivalence between discrete and continuous models, prompting further investigation into their distinct explanatory roles.

Purpose of the Study:

  • To replicate and extend the finding that Luce's low-threshold model quantitatively matches recognition memory data as well as signal detection theory.
  • To investigate the differential fit of discrete (low-threshold) and continuous (signal detection theory) models to recognition memory data based on stimulus encoding strength.

Related Experiment Videos

  • To propose an alternative framework for recognition memory that integrates both discrete and continuous mediation through strategic control processes.

    • Main Methods:

    • Replication of previous findings across 8 distinct experiments.
    • Quantitative comparison of the predictive accuracy of Luce's low-threshold model and signal detection theory.
    • Analysis of model performance in relation to the encoding strength of stimuli presented during recognition tasks.

    Main Results:

    • The low-threshold model and signal detection theory were found to quantitatively describe recognition memory data similarly across 8 experiments.
    • A key finding revealed that the low-threshold model better explains data from strongly encoded stimuli.
    • Conversely, signal detection theory demonstrated a superior fit for data associated with weakly encoded stimuli.

    Conclusions:

    • The equivalence between discrete and continuous models in recognition memory is explained by their differential fit to stimuli based on encoding strength.
    • A novel framework is proposed where a control process, potentially driven by metacognitive judgments of item strength, can shift memory mediation between discrete and continuous processes.
    • This suggests that recognition memory may not be exclusively discrete or continuous but dynamically regulated by strategic control mechanisms.