Attention, Perception, & Psychophysics

, Volume 81, Issue 1, pp 61–70 | Cite as

Search efficiency is not sufficient: The nature of search modulates stimulus-driven attention

  • Koeun Jung
  • Suk Won HanEmail author
  • Yoonki MinEmail author


It has long been debated whether or not a salient stimulus automatically attracts people’s attention in visual search. Recent findings showed that a salient stimulus is likely to capture attention especially when the search process was inefficient due to high levels of competition between the target and distractors. Expanding these studies, the present study proposes that a specific nature of visual search, as well as search efficiency, determines whether or not a salient, task-irrelevant singleton stimulus captures attention. To test this proposition, we conducted three experiments, in which participants performed two visual search tasks whose underlying mechanisms are known to be different: orientation-feature search and Landolt-C search tasks. We found that color singleton distractors captured attention when participants performed the orientation-feature search task. The magnitude of this capture effect increased as search efficiency decreased. On the contrary, the capture by singleton distractors was not observed under the Landolt-C search task. This differential pattern of capture effect was not due to differences in search efficiency across the search tasks; even when search efficiency was controlled for, stimulus-driven capture of attention by a salient distractor was found only under the feature search. Based on these results, the present study suggests that in addition to search efficiency, the nature of search strategy and the extent to which attentional control is strained play crucial roles in observing stimulus-driven attentional capture in visual search.


Attentional capture Singleton distractor Search mechanism Attentional control 



K. Jung and Y. Min were supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2018-2016-0-00304) supervised by the IITP (Institute for Information & Communications Technology Promotion).

S. W. Han was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A5A8018781).

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  1. Bacon, W. F., & Egeth, H. E. (1994). Overriding stimulus-driven attentional capture. Perception & Psychophysics, 55(5), 485–496.CrossRefGoogle Scholar
  2. Barras, C., & Kerzel, D. (2017a). Salient-but-irrelevant stimuli cause attentional capture in difficult, but attentional suppression in easy visual search. Psychophysiology, 54(12), 1826–1838.CrossRefPubMedGoogle Scholar
  3. Barras, C., & Kerzel, D. (2017b). Target-nontarget similarity decreases search efficiency and increases stimulus-driven control in visual search. Attention, Perception, & Psychophysics, 79(7), 2037–2043. doi: CrossRefGoogle Scholar
  4. Beck, D. M., & Kastner, S. (2005). Stimulus context modulates competition in human extrastriate cortex. Nature Neuroscience, 8(8), 1110.CrossRefPubMedPubMedCentralGoogle Scholar
  5. Beck, D. M., & Kastner, S. (2009). Top-down and bottom-up mechanisms in biasing competition in the human brain. Vision Research, 49(10), 1154–1165.CrossRefPubMedGoogle Scholar
  6. Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18(1), 193–222.CrossRefPubMedGoogle Scholar
  7. Eckstein, M. P., Thomas, J. P., Palmer, J., & Shimozaki, S. S. (2000). A signal detection model predicts the effects of set size on visual search accuracy for feature, conjunction, triple conjunction, and disjunction displays. Perception & Psychophysics, 62(3), 425–451.CrossRefGoogle Scholar
  8. Folk, C. L., Remington, R. W., & Johnston, J. C. (1992). Involuntary covert orienting is contingent on attentional control settings. Journal of Experimental Psychology Human Perception and Performance, 18, 1030–1030.CrossRefPubMedGoogle Scholar
  9. Gaspelin, N., Ruthruff, E., & Lien, M. C. (2016). The problem of latent attentional capture: Easy visual search conceals capture by task-irrelevant abrupt onsets. Journal of Experimental Psychology: Human Perception and Performance, 42(8), 1104–1120. doi: PubMedGoogle Scholar
  10. Gaspelin, N., Ruthruff, E., Lien, M.-C., & Jung, K. (2012). Breaking through the attentional window: Capture by abrupt onsets versus color singletons. Attention, Perception, & Psychophysics, 74(7), 1461–1474.CrossRefGoogle Scholar
  11. Han, S. W. (2017). Search for capacity-limited and super-capacity search. Experimental Psychology, 64(3), 149.CrossRefPubMedGoogle Scholar
  12. Han, S. W., & Marois, R. (2014). The effects of stimulus-driven competition and task set on involuntary attention. Journal of Vision, 14(7), 14–14.CrossRefPubMedPubMedCentralGoogle Scholar
  13. Huang, L., & Pashler, H. (2005). Attention capacity and task difficulty in visual search. Cognition, 94(3), B101–B111.CrossRefPubMedGoogle Scholar
  14. Kastner, S., De Weerd, P., Desimone, R., & Ungerleider, L. G. 1998. Mechanisms of directed attention in the human extrastriate cortex as revealed by functional MRI. Science, 282(5386), 108-111.CrossRefPubMedGoogle Scholar
  15. Kerzel, D., & Barras, C. (2016). Distractor rejection in visual search breaks down with more than a single distractor feature. Journal of Experimental Psychology: Human Perception and Performance, 42(5), 648.PubMedGoogle Scholar
  16. Lamy, D., & Egeth, H. E. (2003). Attentional capture in singleton-detection and feature-search modes. Journal of Experimental Psychology: Human Perception and Performance, 29(5), 1003.PubMedGoogle Scholar
  17. Leber, A. B., & Egeth, H. E. (2006). It’s under control: Top-down search strategies can override attentional capture. Psychonomic Bulletin & Review, 13(1), 132–138.CrossRefGoogle Scholar
  18. Mazyar, H., Van den Berg, R., & Ma, W. J. (2012). Does precision decrease with set size? Journal of Vision, 12(6), 10-10.CrossRefPubMedPubMedCentralGoogle Scholar
  19. McElree, B., & Carrasco, M. (1999). The temporal dynamics of visual search: Evidence for parallel processing in feature and conjunction searches. Journal of Experimental Psychology: Human Perception and Performance, 25(6), 1517.PubMedGoogle Scholar
  20. Palmer, J. (1994). Set-size effects in visual search: The effect of attention is independent of the stimulus for simple tasks. Vision Research, 34(13), 1703–1721.CrossRefPubMedGoogle Scholar
  21. Palmer, J., Ames, C. T., & Lindsey, D. T. (1993). Measuring the effect of attention on simple visual search. Journal of Experimental Psychology: Human Perception and Performance, 19(1), 108.PubMedGoogle Scholar
  22. Palmer, J., Verghese, P., & Pavel, M. (2000). The psychophysics of visual search. Vision Research, 40(10/12), 1227–1268.CrossRefPubMedGoogle Scholar
  23. Palmer, J., & Wright, R. (1998). Attentional effects in visual search: Relating search accuracy and search time. Visual Attention, 8, 348–388.Google Scholar
  24. Pavlov, I. P. (1927). Conditional reflexes: An investigation of the physiological activity of the cerebral cortex.Google Scholar
  25. Peirce, J. W. (2007). PsychoPy—Psychophysics software in Python. Journal of Neuroscience Methods, 162(1), 8–13.CrossRefPubMedPubMedCentralGoogle Scholar
  26. Proulx, M. J., & Egeth, H. E. (2006). Target-nontarget similarity modulates stimulus-driven control in visual search. Psychonomic Bulletin & Review, 13(3), 524–529.CrossRefGoogle Scholar
  27. Scharff, A., Palmer, J., & Moore, C. M. (2011). Extending the simultaneous-sequential paradigm to measure perceptual capacity for features and words. Journal of Experimental Psychology: Human Perception and Performance, 37(3), 813.PubMedGoogle Scholar
  28. Scharff, A., Palmer, J., & Moore, C. M. (2013). Divided attention limits perception of 3-D object shapes. Journal of Vision, 13(2), 18–18.CrossRefPubMedPubMedCentralGoogle Scholar
  29. Sokolov, E. N. (1963). Perception and the conditioned reflex. Oxford: Pergamon Press.Google Scholar
  30. Sung, K. (2008). Serial and parallel attentive visual searches: Evidence from cumulative distribution functions of response times. Journal of Experimental Psychology: Human Perception and Performance, 34(6), 1372.PubMedGoogle Scholar
  31. Theeuwes, J. (1992). Perceptual selectivity for color and form. Attention, Perception, & Psychophysics, 51(6), 599–606.CrossRefGoogle Scholar
  32. Theeuwes, J. (2004). Top-down search strategies cannot override attentional capture. Psychonomic Bulletin & Review, 11(1), 65–70.CrossRefGoogle Scholar
  33. Treisman, A. M., & Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology, 12(1), 97–136.CrossRefPubMedGoogle Scholar
  34. Wolfe, J. M., & Horowitz, T. S. (2004). What attributes guide the deployment of visual attention and how do they do it? Nature Reviews Neuroscience, 5(6), 495.CrossRefPubMedGoogle Scholar
  35. Woodman, G. F., & Luck, S. J. (1999). Electrophysiological measurement of rapid shifts of attention during visual search. Nature, 400(6747), 867–869.CrossRefPubMedGoogle Scholar
  36. Woodman, G. F., & Luck, S. J. (2003). Serial deployment of attention during visual search. Journal of Experimental Psychology: Human Perception and Performance, 29(1), 121.PubMedGoogle Scholar
  37. 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 and Performance, 33(2), 363.PubMedGoogle Scholar
  38. Woodman, G. F., Luck, S. J., & Schall, J. D. (2007). The role of working memory representations in the control of attention. Cerebral Cortex, 17(Suppl. 1), i118–i124.CrossRefPubMedGoogle Scholar

Copyright information

© The Psychonomic Society, Inc. 2018

Authors and Affiliations

  1. 1.Department of PsychologyChungnam National UniversityDaejeonKorea

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