Advertisement

Using Computational Modeling to Assess Use of Cognitive Strategies

  • Michael J. Haass
  • Laura E. Matzen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6780)

Abstract

Although there are many strategies and techniques that can improve memory, cognitive biases generally lead people to choose suboptimal memory strategies. In this study, participants were asked to memorize words while their brain activity was recorded using electroencephalography (EEG). The participants’ memory performance and EEG data revealed that a self-testing (retrieval practice) strategy could improve memory. The majority of the participants did not use self-testing, but computational modeling revealed that a subset of the participants had brain activity that was consistent with this optimal strategy. We developed a model that characterized the brain activity associated with passive study and with explicit memory testing. We used that model to predict which participants adopted a self-testing strategy, and then evaluated the behavioral performance of those participants. This analysis revealed that, as predicted, the participants whose brain activity was consistent with a self-testing strategy had better memory performance at test.

Keywords

Memory computational modeling electroencephalography 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Benjamin, A.S.: Memory is more than just remembering: Strategic control of encoding, accessing memory, and making decisions. In: Ross, B.H., Benjamin, A.S. (eds.) The Psychology of Learning and Motivation: Skill and Strategy in Memory Use, vol. 48, pp. 175–223. Academic Press, London (2008)CrossRefGoogle Scholar
  2. 2.
    Benjamin, A.S., Bjork, R.A., Schwartz, B.L.: The mismeasure of memory: When retrieval fluency is misleading as a metamnemonic index. Journal of Experimental Psychology: General 127, 55–68 (1998)CrossRefGoogle Scholar
  3. 3.
    Bjork, R.A.: Assessing our own competence: Heuristics and Illusions. In: Gopher, D., Koriat, A. (eds.) Attention and Performance XVII: Cognitive Regulation of Performance: Interaction of Theory and Application, pp. 435–459. MIT Press, Cambridge (1999)Google Scholar
  4. 4.
    Koriat, A., Bjork, R.A.: Illusions of competence in monitoring one’s knowledge during study. Journal of Experimental Psychology: Learning, Memory, and Cognition 31, 187–194 (2005)Google Scholar
  5. 5.
    Koriat, A., Bjork, R.A., Sheffer, L., Bar, S.K.: Predicting one’s own forgetting: The role of experience-based and theory-based processes. Journal of Experimental Psychology: General 133, 643–656 (2004)CrossRefGoogle Scholar
  6. 6.
    Schwartz, B.L., Benjamin, A.S., Bjork, R.A.: The inferential and experiential bases of metamemory. Current Directions in Psychological Science 6, 132–137 (1997)CrossRefGoogle Scholar
  7. 7.
    Landauer, T.K., Bjork, R.A.: Optimum rehearsal patterns and name learning. In: Gruneberg, M.M., Morris, P.E., Sykes, R.N. (eds.) Practical Aspects of Memory, pp. 625–632. Academic Press, London (1978)Google Scholar
  8. 8.
    Allan, K., Rugg, M.D.: An event-related potential study of explicit memory on tests of cued recall and recognition. Neuropsychologia 35, 387–397 (1997)CrossRefGoogle Scholar
  9. 9.
    Neville, H.J., Kutas, M., Chesney, G., Schmidt, A.: Event-related brain potentials during the initial encoding and subsequent recognition memory of congruous and incongruous words. Journal of Memory and Language 25, 75–92 (1986)CrossRefGoogle Scholar
  10. 10.
    Paller, K.A., Kutas, M.: Brain potentials during memory retrieval provide neuropsychological support for the distinction between conscious recollection and priming. Journal of Cognitive Neuroscience 4, 375–391 (1992)CrossRefGoogle Scholar
  11. 11.
    Rugg, M.D., Doyle, M.C.: Event-related potentials and stimulus repetition in direct and indirect tests of memory. In: Heinze, H.J., Munte, T.F., Mangun, G.R. (eds.) Cognitive Electrophysiology, pp. 124–138. Birkhauser, Boston (1994)CrossRefGoogle Scholar
  12. 12.
    Van Petten, C., Senkfor, A.J.: Memory for words and novel visual patterns: Repetition, recognition, and encoding effects in the event-related brain potential. Psychophysiology 33, 491–508 (1996)CrossRefGoogle Scholar
  13. 13.
    MATLAB version 7.11.0.584 (R2010b). The MathWorks Inc., Natick (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Michael J. Haass
    • 1
  • Laura E. Matzen
    • 1
  1. 1.Sandia National LaboratoriesAlbuquerqueUSA

Personalised recommendations