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Familiarity, recollection, and receiver-operating characteristic (ROC) curves in recognition memory

  • James F. JuolaEmail author
  • Alexandra Caballero-Sanz
  • Adrián R. Muñoz-García
  • Juan Botella
  • Manuel Suero
Article
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Abstract

The Atkinson-Shiffrin theory describes and explains some of the processes involved in storing and retrieving information in human memory. Here we examine predictions of related models for search and decision processes in recognizing information in long-term memory. In some models, recognition is presumably based on a test item’s familiarity judgment, and subsequent decisions follow from the sensitivity and decision parameters of signal detection theory. Other models dispense with the continuous notion of familiarity and base recognition on discrete internal states such as relative certainty that an item has or has not been previously studied, with an intermediate state of uncertainty that produces guesses. Still others are hybrid models with two criteria located along a familiarity continuum defining areas for rapid decisions based on high or low familiarities. For intermediate familiarity values, the decision can be delayed pending the results of search for, and occasional recollection of, relevant episodic information. Here we present the results from a study of human recognition memory for lists of words using both response time and error data to construct receiver-operating characteristic (ROC) curves derived from three standard methods based on the same data set. Models are evaluated against, and parameters estimated from, group as well as individual subjects’ behavior. We report substantially different ROC curves when they are based on variations in target-word frequency, confidence judgments, and response latencies. The results indicate that individual versus group data must be used with caution in determining the appropriate theoretical interpretation of recognition memory performance.

Keywords

Recognition memory Familiarity vs. recollection Memory models 

Notes

References

  1. Alonso, M. A., Fernández, A., Díez, E., & Beato, M. S. (2004). Índices de producción de falso recuerdo y falso reconocimiento para 55 listas de palabras en castellano. Psicothema, 16, 357-362.Google Scholar
  2. Annis, J., Lenes, J. G., Westfall, H. A., Criss, A. H., & Malmberg, K. J. (2015). The list-length effect does not discriminate between models of recognition memory. Journal of Memory and Language, 85, 27-41.CrossRefGoogle Scholar
  3. Atkinson, R. C., & Juola, J. F. (1973). Factors influencing speed and accuracy of word recognition. In S. Kornblum (Ed.), Attention and Performance IV. New York: Academic Press.Google Scholar
  4. Atkinson, R. C., & Juola, J. F. (1974). Search and decision processes in recognition memory. In D. Krantz, R. Atkinson, R. Luce, and P. Suppes (Eds.). Contemporary Developments in Mathematical Psychology, Vol. 1, San Francisco: W.H. Freeman.Google Scholar
  5. Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence & J. T. Spence (Eds.), The Psychology of Learning and Motivation: Advances in Research and Theory (Vol. 2). New York: Academic Press.Google Scholar
  6. Atkinson, R. C., & Shiffrin, R. M. (1971). The control of short-term memory. Scientific American, 225, 82-90. doi: https://doi.org/10.1038/scientificamerican0871-82 .
  7. Banks, W. P. (1970). Signal detection theory and human memory. Psychological Bulletin, 14, 81-99.CrossRefGoogle Scholar
  8. Botella, J., Privado, J., Suero, M., Colom, R., & Juola, J. F. (2019). Group analyses can hide heterogeneity effects when searching for a general model: Evidence based on a conflict monitoring task. Acta Psychologica, 193, 171-179.CrossRefGoogle Scholar
  9. Brainerd, C. J., Nakamura, K., & Lee, W.-F., (2019). Recollection is fast and slow. Journal of Experimental Psychology: Learning Memory and Cognition. CrossRefGoogle Scholar
  10. Bröder, A., Kellen, D., Schütz, J., & Rohmeier, C. (2013). Validating a two-high-threshold measurement model for confidence rating data in recognition. Memory, 21, 916-944.CrossRefGoogle Scholar
  11. Bröder, A. & Malejka, S. (2017). On a problematic procedure to manipulate response biases in recognition experiments: The case of “implied” base rates. Memory, 25, 736-743.CrossRefGoogle Scholar
  12. Bröder, A. & Schütz, J. (2009). Recognition ROCs are curvilinear – or are they? On premature arguments against the two-high-threshold model of recognition. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35, 587-606.Google Scholar
  13. Callejas, A., Correa, A., Lupiáñez, J., & Tudela, P. (2003). Normas asociativas Intracategoriales para 612 Palabras de Seis Categorías Semánticas en Español. Psicológica, 24, 185-214.Google Scholar
  14. Chen, T., Starns, J. J., & Rotello, C. M. (2015). A Violation of the conditional independence assumption in the two-high-threshold model of recognition memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 41, 1205-1225.Google Scholar
  15. Cohen, A. L., Sanborn, A. N., & Shiffrin, R. M. (2008). Model evaluation using grouped or individual data. Psychonomic Bulletin & Review, 15(4), 692-712.CrossRefGoogle Scholar
  16. Cox, G. E., & Shiffrin, R. M. (2017). A dynamic approach to recognition memory. Psychological Review, 124, 795-860.CrossRefGoogle Scholar
  17. Dube, C. & Rotello, C. M. (2012). Binary ROCs in perception and recognition memory are curved. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18, 130-151.Google Scholar
  18. Dube, C., Starns, J. J., Rotello, C. M., & Ratcliff, R. (2012). Beyond ROC curvature: Strength and response time data support continuous-evidence models of recognition memory. Journal of Memory and Language, 67, 389-406.CrossRefGoogle Scholar
  19. Ebbinghaus, H. (1885). Über das Gedächtnis: Intersuchngen zur Experimentellen Psychologie. Liepzig: Dunker and Humboldt. (Translated by H. A. Ruger & C. E. Bussenius, 1913, and reissued by Dover Publications, 1964.)Google Scholar
  20. Egan, J. P. (1958). Recognition memory and the operating characteristic (Tech. Note AFCAC-TN-58-51). Bloomington: Indiana University, Hearing and Communication Laboratory.Google Scholar
  21. Estes, W. K., & Maddox, W. T. (2005). Risks of drawing inferences about cognitive processes from model fits to individual versus average performance. Psychonomic Bulletin & Review, 12(3), 403-408.CrossRefGoogle Scholar
  22. Fechner, G. T. (1966). Elements of Psychophysics (Vol. 1.). Translated by H. E., Adler, D. H. Howes & E. G. Boring. New York: Holt, Rinehart, & Winston. (Original work published in 1860.)Google Scholar
  23. Gardner, R. M., Macfee, M., & Krinsky, R. (1975). A comparison of binary and rating techniques in the signal detection analysis of recognition memory. Acta Psychologica, 39, 13-19.CrossRefGoogle Scholar
  24. Green, D. M., & Swets, J. A. (1966). Signal Detection Theory and Psychophysics. New York: Wiley.Google Scholar
  25. Grider, R. C., & Malmberg, K. J., (2008). Discriminating between changes in bias and changes in accuracy for recognition memory of emotional stimuli. Memory & Cognition, 36, 933-946.CrossRefGoogle Scholar
  26. Gronlund, S. D., & Elam, L. E. (1994). List-length effect: Recognition accuracy and variance of underlying distributions. Journal of Experimental Psychology: Learning, Memory, and Cognition. 20, 1355-1369.Google Scholar
  27. Jang, Y., Wixted, J. T., & Huber, D. E. (2011). The diagnosticity of individual data for model selection: Comparing signal-detection models of recognition memory. Psychonomic Bulletin & Review, 18, 751-757.CrossRefGoogle Scholar
  28. Juola, J. F., Fischler, I., Wood, C. T., & Atkinson, R. C. (1971). Recognition time for information stored in long-term memory. Perception & Psychophysics, 10, 8-14.CrossRefGoogle Scholar
  29. Kellen, D. & Klauer, K. C. (2015). Signal detection and threshold modeling of confidence-rating ROCs: A critical test with minimal assumptions. Psychological Review, 122, 542-557. doi: https://doi.org/10.1037/a0039251.CrossRefGoogle Scholar
  30. Kellen, D., Klauer, K. C., & Bröder, A. (2013). Recognition memory models and binary-response ROCs: A comparison by minimum description length. Psychonomic Bulletin and Review, 20, 693-719.CrossRefGoogle Scholar
  31. Kellen, D., Singmann, H., Vogt, J., & Klauer, K. C. (2015). Further evidence for discrete-state mediation in recognition memory. Experimental Psychology, 62, 40-53.CrossRefGoogle Scholar
  32. Kintsch, W. (1967). Memory and decision aspects of recognition learning. Psychological Review, 74, 496-504.CrossRefGoogle Scholar
  33. Klauer, K. C., & Kellen, D. (2015). The flexibility of models of recognition memory: The case of confidence ratings. Journal of Mathematical Psychology, 67, 8-25.CrossRefGoogle Scholar
  34. Luce, R. D. (1986). Response Times. New York: Oxford University Press.Google Scholar
  35. Macmillan, N. A., & Creelman, C. D. (2005). Detection Theory: A User’s Guide (2nd). New York: Psychological Press.Google Scholar
  36. Malejka, S. & Bröder, A. (2019). Exploring the shape of signal-detection distributions in individual recognition ROC data. Journal of Memory and Language, 104, 83-107.CrossRefGoogle Scholar
  37. Malmberg, K. J. (2002). On the form of ROCs constructed from confidence ratings. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 380-387.Google Scholar
  38. Malmberg, K. J. (2008). Recognition memory: A review of the critical findings and an integrated theory for relating them. Cognitive Psychology, 57, 335-384.CrossRefGoogle Scholar
  39. Malmberg, K. J., Raaijmakers, J. G. W., & Shiffrin, R. M. (2019). 50 years of research sparked by Aykinson and Shiffrin (1968). Memory & Cognition.Google Scholar
  40. Malmberg, K. J. & Xu, J. (2006). The influence of averaging and noisy decision strategies on the recognition memory ROC. Psychonomic Bulletin & Review, 13, 99-105.CrossRefGoogle Scholar
  41. Mandler, G. (1980). Recognizing: The judgment of previous occurrence. Psychological Review, 87, 252-271.CrossRefGoogle Scholar
  42. McAdoo, R. M., Key, K. N., & Gronlund, S. D. (2019). Task effects determine whether recognition memory is mediated discretely or continuously. Memory & Cognition.Google Scholar
  43. Parks, C. M. & Yonelinas, A. P. (2007). Moving beyond pure signal-detection models: Comment on Wixted (2007). Psychological Review, 114, 188-202.CrossRefGoogle Scholar
  44. Parks, T.E. (1966). Signal-detectability theory of recognition-memory performance. Psychological Review, 73, 44-58.CrossRefGoogle Scholar
  45. Pérez Dueñas, C., Acosta, A., Megías, J. L., & Lupiáñez, J. (2010). Evaluación de las dimensiones de valencia: Activación, frecuencia subjetiva de uso y relevancia para la ansiedad. La depresión y la ira de 238 sustantivos en una muestra universitaria. Psicológica, 31, 241-273.Google Scholar
  46. Province, J. M., & Rouder, J. N. (2012). Proceedings of the National Academy of Sciences of the United States of America, 109, 14357-14362.CrossRefGoogle Scholar
  47. Shiffrin, R. M., & Steyvers, M. (1997). A model for recognition memory: REM – retrieving effectively from memory. Psychological Bulletin & Review, 4, 145-166.CrossRefGoogle Scholar
  48. Singmann, H., & Kellen, D. (2013). MPTinR: Analysis of Multinomial Processing Tree models with R. Behavior Research Methods, 45, 560–575.CrossRefGoogle Scholar
  49. Snodgrass, J. G., & Corwin, J. (1988). Pragmatics of measuring recognition memory: Applications to dementia and amnesia. Journal of Experimental Psychology: General, 117, 34-50.CrossRefGoogle Scholar
  50. Sternberg, S. (1966). High-speed scanning in human memory. Science, 153, 652-654.CrossRefGoogle Scholar
  51. Sternberg, S. (2016). In defence of high-speed memory scanning. Quarterly Journal of Experimental Psychology, 69, 10, 2020-2075.  https://doi.org/10.1080/17470218.2016.1198820.CrossRefGoogle Scholar
  52. Swets, J.A., Dawes, R.M., & Monahan, J.M. (2002). Psychological science can improve diagnostic decisions. Psychological Science in the Public Interest, 1, 1-24.CrossRefGoogle Scholar
  53. Thomas, E. A. C. & Myers, J. L. (1972). Implications of listing data for threshold and nonthreshold models of signal detection. Journal of Mathematical Psychology, 9, 253-285.CrossRefGoogle Scholar
  54. Tulving, E. (1972). Episodic and semantic memory. In E. Tulving & W. Donaldson (Eds.), Organization of Memory. New York: Academic Press.Google Scholar
  55. Van Zandt, T. (2000). ROC curves and confidence judgments in recognition memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26(3), 582-600.Google Scholar
  56. Weidemann, C. T. & Kahana, M. J. (2016). Assessing recognition memory using confidence ratings and response times. Royal Society Open Science. 3: 150670.  https://doi.org/10.1098/rsos.150670.CrossRefGoogle Scholar
  57. Wickens, T. D. (2002). Elementary Signal Detection Theory. New York: Oxford University Press.Google Scholar
  58. Wixted, J. T. (2007). Dual-process theory and signal detection theory of recognition memory. Psychological Review, 114, 152-176.CrossRefGoogle Scholar
  59. Yonelinas, A. P. (1994). Receiver-operating characteristics in recognition memory: Evidence for a dual-process model. Journal of Experimental Psychology: Learning. Memory. and Cognition, 20, 1341-1354.Google Scholar
  60. Yonelinas, A. P. (1997). Recognition memory ROCs for item and associative information: The contribution of recollection and familiarity. Memory & Cognition, 25, 747-763.CrossRefGoogle Scholar
  61. Yonelinas, A. P. & Parks, C. M. (2007). Receiver operating characteristics (ROCs) in recognition memory: A review. Psychological Bulletin, 133(5), 800-832.CrossRefGoogle Scholar

Copyright information

© The Psychonomic Society, Inc. 2019

Authors and Affiliations

  • James F. Juola
    • 1
    Email author
  • Alexandra Caballero-Sanz
    • 1
  • Adrián R. Muñoz-García
    • 1
  • Juan Botella
    • 1
  • Manuel Suero
    • 1
  1. 1.Social Psychology and MethodologyUniversidad Autónoma de MadridMadridSpain

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