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Indirect assessment of visual working memory for simple and complex objects

Abstract

Previous research has shown that visual search performance is modulated by the current contents in visual working memory (VWM), even when the contents of VWM are irrelevant to the search task. For example, visual search is faster when the target—rather than a distractor—is surrounded by a shape currently held in VWM. This study uses the modulation of visual search by VWM to investigate properties of VWM. Participants were asked to remember the color or the shape of novel polygons whose “goodness” of figure varied according to Garner’s (1962) rotation and reflection transformation principle. During the memory retention interval, participants searched for a tilted line among vertical lines embedded inside colored polygons. Search was faster when the target—rather than a distractor—was enclosed by the remembered polygons. The congruity effect diminished with increasing memory load and decreasing figure goodness. We conclude that congruity effects in visual search can indirectly assess VWM representation strength.

References

  1. Alvarez, G. A., & Cavanagh, P. (2004). The capacity of visual shortterm memory is set both by visual information load and by number of objects. Psychological Science, 15, 106–111.

    Article  PubMed  Google Scholar 

  2. Attneave, F. (1957). Physical determinants of the judged complexity of shapes. Journal of Experimental Psychology, 53, 221–227.

    Article  PubMed  Google Scholar 

  3. Awh, E., Barton, B., & Vogel, E. K. (2007). Visual working memory represents a fixed number of items regardless of complexity. Psychological Science, 18, 622–628.

    Article  PubMed  Google Scholar 

  4. Ballard, D. H., Hayhoe, M. M., & Pelz, J. B. (1995). Memory representations in natural tasks. Journal of Cognitive Neuroscience, 7, 66–80.

    Article  Google Scholar 

  5. Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision, 10, 433–436.

    Article  PubMed  Google Scholar 

  6. Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral & Brain Sciences, 24, 87–185.

    Article  Google Scholar 

  7. Downing, P. E. (2000). Interactions between visual working memory and selective attention. Psychological Science, 11, 467–473.

    Article  PubMed  Google Scholar 

  8. Downing, P. E., & Dodds, C. M. (2004). Competition in visual working memory for control of search. Visual Cognition, 11, 689–703.

    Article  Google Scholar 

  9. Droll, J. A., Hayhoe, M. M., Triesch, J., & Sullivan, B. T. (2005). Task demands control acquisition and storage of visual information. Journal of Experimental Psychology: Human Perception & Performance, 31, 1416–1438.

    Article  Google Scholar 

  10. Duncan, J., & Humphreys, G. W. (1989). Visual-search and stimulus similarity. Psychological Review, 96, 433–458.

    Article  PubMed  Google Scholar 

  11. Eng, H. Y., Chen, D., & Jiang, Y. (2005). Visual working memory for simple and complex visual stimuli. Psychonomic Bulletin & Review, 12, 1127–1133.

    Article  Google Scholar 

  12. Garner, W. R. (1962). Uncertainty and structure as psychological concepts. New York: Wiley.

    Google Scholar 

  13. Garner, W. R., & Sutliff, D. (1974). The effect of goodness on encoding time in visual pattern discrimination. Perception & Psychophysics, 16, 426–430.

    Article  Google Scholar 

  14. Hayhoe, M., & Ballard, D. (2005). Eye movements in natural behavior. Trends in Cognitive Sciences, 9, 188–194.

    Article  PubMed  Google Scholar 

  15. Hochberg, J., & McAlister, E. (1953). A quantitative approach to figure “goodness.” Journal of Experimental Psychology, 46, 361–364.

    Article  PubMed  Google Scholar 

  16. Hollingworth, A. (2003). Failures of retrieval and comparison constrain change detection in natural scenes. Journal of Experimental Psychology: Human Perception & Performance, 29, 388–403.

    Article  Google Scholar 

  17. Huang, L., & Pashler, H. (2007). Working memory and the guidance of visual attention: Consonance-driven orienting. Psychonomic Bulletin & Review, 14, 148–153.

    Article  Google Scholar 

  18. Jiang, Y. V., Olson, I. R., & Chun, M. M. (2000). Organization of visual short-term memory. Journal of Experimental Psychology: Learning, Memory, & Cognition, 26, 683–702.

    Article  Google Scholar 

  19. Jiang, Y. V., Shim, W. M., & Makovski, T. (in press). Visual working memory for line orientations and face identities. Perception & Psychophysics.

  20. Keren, G., O’Hara, W. P., & Skelton, J. M. (1977). Levels of noise processing and attentional control. Journal of Experimental Psychology: Human Perception & Performance, 3, 653–664.

    Article  Google Scholar 

  21. Landman, R., Spekreijse, H., & Lamme, V. A. F. (2003). Large capacity storage of integrated objects before change blindness. Vision Research, 43, 149–164.

    Article  PubMed  Google Scholar 

  22. Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390, 279–281.

    Article  PubMed  Google Scholar 

  23. Makovski, T., Shim, W. M., & Jiang, Y. V. (2006). Interference from filled delays on visual change detection. Journal of Vision, 6, 1459–1470.

    Article  PubMed  Google Scholar 

  24. Makovski, T., Sussman, R. S., & Jiang, Y. V. (2008). Orienting attention in visual working memory reduces interference from memory probes. Journal of Experimental Psychology: Learning, Memory, & Cognition, 34, 369–380.

    Article  Google Scholar 

  25. Olivers, C. N. L., Meijer, F., & Theeuwes, J. (2006). Feature-based memory-driven attentional capture: Visual working memory content affects visual attention. Journal of Experimental Psychology: Human Perception & Performance, 32, 1243–1265.

    Article  Google Scholar 

  26. Olsson, H., & Poom, L. (2005). Visual memory needs categories. Proceedings of the National Academy of Sciences, 102, 8776–8780.

    Article  Google Scholar 

  27. Pashler, H. (1988). Familiarity and visual change detection. Perception & Psychophysics, 44, 369–378.

    Article  Google Scholar 

  28. Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision, 10, 437–442.

    Article  PubMed  Google Scholar 

  29. Phillips, W. A. (1974). On the distinction between sensory storage and short-term visual memory. Perception & Psychophysics, 16, 283–290.

    Article  Google Scholar 

  30. Rauschenberger, R., & Yantis, S. (2006). Perceptual encoding efficiency in visual search. Journal of Experimental Psychology: General, 135, 116–131.

    Article  Google Scholar 

  31. Rensink, R. A. (2002). Change detection. Annual Review of Psychology, 53, 245–277.

    Article  PubMed  Google Scholar 

  32. Song, J. H., & Jiang, Y. V. (2006). Visual working memory for simple and complex features: An fMRI study. NeuroImage, 30, 963–972.

    Article  PubMed  Google Scholar 

  33. Soto, D., Heinke, D., Humphreys, G. W., & Blanco, M. J. (2005). Early, involuntary top-down guidance of attention from working memory. Journal of Experimental Psychology: Human Perception & Performance, 31, 248–261.

    Article  Google Scholar 

  34. Soto, D., & Humphreys, G. W. (2007). Automatic guidance of visual attention from verbal working memory. Journal of Experimental Psychology: Human Perception & Performance, 33, 730–737.

    Article  Google Scholar 

  35. Soto, D., Humphreys, G. W., & Heinke, D. (2006). Working memory can guide pop-out search. Vision Research, 46, 1010–1018.

    Article  PubMed  Google Scholar 

  36. Vickery, T. J., King, L. W., & Jiang, Y. V. (2005). Setting up the target template in visual search. Journal of Vision, 5, 81–92.

    Article  PubMed  Google Scholar 

  37. Vogel, E. K., Woodman, G. F., & Luck, S. J. (2006). The time course of consolidation in visual working memory. Journal of Experimental Psychology: Human Perception & Performance, 32, 1436–1451.

    Article  Google Scholar 

  38. Wilken, P., & Ma, W. J. (2004). A detection theory account of change detection. Journal of Vision, 4, 1120–1135.

    Article  PubMed  Google Scholar 

  39. Wolfe, J. M., Butcher, S. J., Lee, C., & Hyle, M. (2003). Changing your mind: On the contributions of top-down and bottom-up guidance in visual search for feature singletons. Journal of Experimental Psychology: Human Perception & Performance, 29, 483–502.

    Article  Google Scholar 

  40. Woodman, G. F., & Luck, S. J. (2004). Visual search is slowed when visuospatial working memory is occupied. Psychonomic Bulletin & Review, 11, 269–274.

    Article  Google Scholar 

  41. Woodman, G. F., & Luck, S. J. (2007). Do the contents of visual working memory automatically influence attentional selection during visual search? Journal of Experimental Psychology: Human Perception & Performance, 33, 363–377.

    Article  Google Scholar 

  42. Woodman, G. F., Vogel, E. K., & Luck, S. J. (2001). Visual search remains efficient when visual working memory is full. Psychological Science, 12, 219–224.

    Article  PubMed  Google Scholar 

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Correspondence to Tal Makovski.

Additional information

This research was supported in part by NSF Grant 0733764 and NIH Grant 071788.

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Makovski, T., Jiang, Y.V. Indirect assessment of visual working memory for simple and complex objects. Memory & Cognition 36, 1132–1143 (2008). https://doi.org/10.3758/MC.36.6.1132

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Keywords

  • Visual Search
  • Congruity Effect
  • Memory Load
  • Gruity Effect
  • Ruent Trial