Attention, Perception, & Psychophysics

, Volume 79, Issue 5, pp 1506–1523 | Cite as

Confident failures: Lapses of working memory reveal a metacognitive blind spot

Article

Abstract

Working memory performance fluctuates dramatically from trial to trial. On many trials, performance is no better than chance. Here, we assessed participants’ awareness of working memory failures. We used a whole-report visual working memory task to quantify both trial-by-trial performance and trial-by-trial subjective ratings of inattention to the task. In Experiment 1 (N = 41), participants were probed for task-unrelated thoughts immediately following 20% of trials. In Experiment 2 (N = 30), participants gave a rating of their attentional state following 25% of trials. Finally, in Experiments 3a (N = 44) and 3b (N = 34), participants reported confidence of every response using a simple mouse-click judgment. Attention-state ratings and off-task thoughts predicted the number of items correctly identified on each trial, replicating previous findings that subjective measures of attention state predict working memory performance. However, participants correctly identified failures on only around 28% of failure trials. Across experiments, participants’ metacognitive judgments reliably predicted variation in working memory performance but consistently and severely underestimated the extent of failures. Further, individual differences in metacognitive accuracy correlated with overall working memory performance, suggesting that metacognitive monitoring may be key to working memory success.

Keywords

Visual working memory Attentional control Metacognition 

Supplementary material

13414_2017_1331_MOESM1_ESM.docx (527 kb)
ESM 1(DOCX 527 kb)

References

  1. Adam, K. C. S., Mance, I., Fukuda, K., & Vogel, E. K. (2015). The contribution of attentional lapses to individual differences in visual working memory capacity. Journal of Cognitive Neuroscience, 27(8), 1601–1616. doi:10.1162/jocn_a_00811 CrossRefPubMedPubMedCentralGoogle Scholar
  2. Adam, K. C. S., & Vogel, E. K. (2016). Reducing failures of working memory with performance feedback. Psychonomic Bulletin & Review,  23(5), 1520–1527. doi:10.3758/s13423-016-1019-4
  3. Antrobus, J. S. (1968). Information theory and stimulus-independent thought. British Journal of Psychology, 59(4), 423–430. doi:10.1111/j.2044-8295.1968.tb01157.x CrossRefGoogle Scholar
  4. Bays, P. M., & Husain, M. (2008). Dynamic shifts of limited working memory resources in human vision. Science, 321(5890), 851–854. doi:10.1126/science.1158023 CrossRefPubMedPubMedCentralGoogle Scholar
  5. Bona, S., & Silvanto, J. (2014). Accuracy and confidence of visual short-term memory do not go hand-in-hand: Behavioral and neural dissociations. PLoS ONE, 9(3), e90808. doi:10.1371/journal.pone.0090808 CrossRefPubMedPubMedCentralGoogle Scholar
  6. Brainard, D. H. (1997). The psychophysics toolbox. Spatial Vision, 10(4), 433–436. doi:10.1163/156856897X00357 CrossRefPubMedGoogle Scholar
  7. Burson, K. A., Larrick, R. P., & Klayman, J. (2006). Skilled or unskilled, but still unaware of it: How perceptions of difficulty drive miscalibration in relative comparisons. Journal of Personality and Social Psychology, 90(1), 60–77. doi:10.1037/0022-3514.90.1.60 CrossRefPubMedGoogle Scholar
  8. Ehrlinger, J., Johnson, K., Banner, M., Dunning, D., & Kruger, J. (2008). Why the unskilled are unaware: Further explorations of (absent) self-insight among the incompetent. Organizational Behavior and Human Decision Processes, 105(1), 98–121. doi:10.1016/j.obhdp.2007.05.002 CrossRefPubMedPubMedCentralGoogle Scholar
  9. Engle, R. W., Kane, M. J., & Tuholski, S. W. (1999). Individual differences in working memory capacity and what they tell us about controlled attention, general fluid intelligence, and functions of the prefrontal cortex. In A. Miyake & P. Shah (Eds.), Models of working memory (pp. 102–134). Cambridge: Cambridge University Press.Google Scholar
  10. Fleming, S. M., Ryu, J., Golfinos, J. G., & Blackmon, K. E. (2014). Domain-specific impairment in metacognitive accuracy following anterior prefrontal lesions. Brain, 137(10), 2811–2822. doi:10.1093/brain/awu221 CrossRefPubMedPubMedCentralGoogle Scholar
  11. Fleming, S. M., Weil, R. S., Nagy, Z., Dolan, R. J., & Rees, G. (2010). Relating introspective accuracy to individual differences in brain structure. Science, 329(5998), 1541–1543. doi:10.1126/science.1191883 CrossRefPubMedPubMedCentralGoogle Scholar
  12. Fougnie, D., Suchow, J. W., & Alvarez, G. A. (2012). Variability in the quality of visual working memory. Nature Communications, 3, 1229. doi:10.1038/ncomms2237 CrossRefPubMedPubMedCentralGoogle Scholar
  13. Fukuda, K., Vogel, E., Mayr, U., & Awh, E. (2010). Quantity, not quality: The relationship between fluid intelligence and working memory capacity. Psychonomic Bulletin & Review, 17(5), 673–679. doi:10.3758/17.5.673 CrossRefGoogle Scholar
  14. Head, J., & Helton, W. S. (2016). The troubling science of neurophenomenology. Experimental Brain Research. doi:10.1007/s00221-016-4623-7 PubMedGoogle Scholar
  15. Huang, L. (2010). Visual working memory is better characterized as a distributed resource rather than discrete slots. Journal of Vision, 10(14), 8–8. doi:10.1167/10.14.8 CrossRefPubMedGoogle Scholar
  16. Kane, M. J., Brown, L. H., McVay, J. C., Silvia, P. J., Myin-Germeys, I., & Kwapil, T. R. (2007). For whom the mind wanders, and when: An experience-sampling study of working memory and executive control in daily life. Psychological Science, 18(7), 614–621. doi:10.1111/j.1467-9280.2007.01948.x CrossRefPubMedGoogle Scholar
  17. Kliegl, R., Wei, P., Dambacher, M., Yan, M., & Zhou, X. (2011). Experimental effects and individual differences in linear mixed models: Estimating the relationship between spatial, object, and attraction effects in visual attention. Frontiers in Psychology, 1, 238. doi:10.3389/fpsyg.2010.00238
  18. Koriat, A. (2007). Metacognition and consciousness. In P. D. Zelazo, M. Moscovitch, & E. Thompson (Eds.), Cambridge handbook of consciousness (pp. 289–325). New York: Cambridge University Press.CrossRefGoogle Scholar
  19. Krueger, J., & Mueller, R. A. (2002). Unskilled, unaware, or both? The better-than-average heuristic and statistical regression predict errors in estimates of own performance. Journal of Personality & Social Psychology, 82(2), 180–188. doi:10.1037//0022-3514.82.2.180 CrossRefGoogle Scholar
  20. Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121–1134. doi:10.1037/0022-3514.77.6.1121 CrossRefPubMedGoogle Scholar
  21. McKiernan, K. A., D’Angelo, B. R., Kaufman, J. N., & Binder, J. R. (2006). Interrupting the “stream of consciousness”: An fMRI investigation. NeuroImage, 29(4), 1185–1191. doi:10.1016/j.neuroimage.2005.09.030 CrossRefPubMedGoogle Scholar
  22. Miranda, A. T., & Palmer, E. M. (2014). Intrinsic motivation and attentional capture from gamelike features in a visual search task. Behavior Research Methods, 46(1), 159–172. doi:10.3758/s13428-013-0357-7 CrossRefPubMedGoogle Scholar
  23. Mrazek, M. D., Smallwood, J., Franklin, M. S., Chin, J. M., Baird, B., & Schooler, J. W. (2012). The role of mind-wandering in measurements of general aptitude. Journal of Experimental Psychology: General, 141(4), 788–798. doi:10.1037/a0027968 CrossRefGoogle Scholar
  24. Mutluturk, A., & Boduroglu, A. (2014). Effects of spatial configurations on the resolution of spatial working memory. Attention, Perception, & Psychophysics, 76(8), 2276–2285. doi:10.3758/s13414-014-0713-4 CrossRefGoogle Scholar
  25. Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision, 10(4), 437–442. doi:10.1163/156856897X00366 CrossRefPubMedGoogle Scholar
  26. Rademaker, R. L., Tredway, C. H., & Tong, F. (2012). Introspective judgments predict the precision and likelihood of successful maintenance of visual working memory. Journal of Vision, 12(13), 21–21. doi:10.1167/12.13.21 CrossRefPubMedPubMedCentralGoogle Scholar
  27. Reason, J. T. (1984). Lapses of attention in everyday life. In R. Paraswaman & D. R. Davies (Eds.), Varieties of attention (pp. 515–549). Orlando: Academic Press.Google Scholar
  28. Rouder, J. N., Morey, R. D., Cowan, N., Zwilling, C. E., Morey, C. C., & Pratte, M. S. (2008). An assessment of fixed-capacity models of visual working memory. Proceedings of the National Academy of Sciences of the United States of America, 105(16), 5975–5979. doi:10.1073/pnas.0711295105 CrossRefPubMedPubMedCentralGoogle Scholar
  29. Schooler, J. W., Reichle, E. D., & Halpern, D. V. (2004). Zoning out while reading: Evidence for dissociations between experience and metaconsciousness. In D. T. Levin (Ed.), Thinking and seeing: Visual metacognition in adults and children (pp. 203–226). Cambridge: MIT Press.Google Scholar
  30. Schooler, J. W., Smallwood, J., Christoff, K., Handy, T. C., Reichle, E. D., & Sayette, M. A. (2011). Meta-awareness, perceptual decoupling and the wandering mind. Trends in Cognitive Sciences, 15(7), 319–326. doi:10.1016/j.tics.2011.05.006
  31. Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2012). A 21 word solution. Dialogue: The Official Newsletter of the Society for Personality and Social Psychology, 26, 4–7.Google Scholar
  32. Smallwood, J., McSpadden, M., & Schooler, J. W. (2007). The lights are on but no one’s home: Meta-awareness and the decoupling of attention when the mind wanders. Psychonomic Bulletin & Review, 14(3), 527–533. doi:10.3758/BF03194102 CrossRefGoogle Scholar
  33. Song, C., Kanai, R., Fleming, S. M., Weil, R. S., Schwarzkopf, D. S., & Rees, G. (2011). Relating inter-individual differences in metacognitive performance on different perceptual tasks. Consciousness and Cognition, 20(4), 1787–1792. doi:10.1016/j.concog.2010.12.011 CrossRefPubMedPubMedCentralGoogle Scholar
  34. Stawarczyk, D., Majerus, S., Maj, M., Van der Linden, M., & D’Argembeau, A. (2011). Mind-wandering: Phenomenology and function as assessed with a novel experience sampling method. Acta Psychologica, 136(3), 370–381. doi:10.1016/j.actpsy.2011.01.002 CrossRefPubMedGoogle Scholar
  35. Teasdale, J. D., Proctor, L., Lloyd, C. A., & Baddeley, A. D. (1993). Working memory and stimulus-independent thought: Effects of memory load and presentation rate. European Journal of Cognitive Psychology, 5(4), 417–433. doi:10.1080/09541449308520128 CrossRefGoogle Scholar
  36. Unsworth, N., Fukuda, K., Awh, E., & Vogel, E. K. (2014). Working memory and fluid intelligence: Capacity, attention control, and secondary memory retrieval. Cognitive Psychology, 71, 1–26. doi:10.1016/j.cogpsych.2014.01.003 CrossRefPubMedPubMedCentralGoogle Scholar
  37. Unsworth, N., & McMillan, B. D. (2014a). Fluctuations in pre-trial attentional state and their influence on goal neglect. Consciousness and Cognition, 26, 90–96. doi:10.1016/j.concog.2014.03.003 CrossRefPubMedGoogle Scholar
  38. Unsworth, N., & McMillan, B. D. (2014b). Trial-to-trial fluctuations in attentional state and their relation to intelligence. Journal of Experimental Psychology: Learning, Memory, and Cognition, 40(3), 882–891. doi:10.1037/a0035544 PubMedGoogle Scholar
  39. Unsworth, N., & Robison, M. K. (2016). The influence of lapses of attention on working memory capacity. Memory & Cognition, 44(2), 188–196. doi:10.3758/s13421-015-0560-0 CrossRefGoogle Scholar
  40. Vandenbroucke, A. R. E., Sligte, I. G., Barrett, A. B., Seth, A. K., Fahrenfort, J. J., & Lamme, V. A. F. (2014). Accurate metacognition for visual sensory memory representations. Psychological Science, 25(4), 861–873. doi:10.1177/0956797613516146 CrossRefPubMedGoogle Scholar
  41. Wilken, P., & Ma, W. J. (2004). A detection theory account of change detection. Journal of Vision, 4(12), 1120–1135. doi:10.1167/4.12.11 CrossRefPubMedGoogle Scholar
  42. Zedelius, C. M., Broadway, J. M., & Schooler, J. W. (2015). Motivating meta-awareness of mind wandering: A way to catch the mind in flight? Consciousness and Cognition, 36, 44–53. doi:10.1016/j.concog.2015.05.016 CrossRefPubMedGoogle Scholar
  43. Zhang, W., & Luck, S. J. (2008). Discrete fixed-resolution representations in visual working memory. Nature, 453(7192), 233–235. doi:10.1038/nature06860 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© The Psychonomic Society, Inc. 2017

Authors and Affiliations

  1. 1.Department of PsychologyUniversity of ChicagoChicagoUSA
  2. 2.Institute for Mind & BiologyUniversity of ChicagoChicagoUSA

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