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Attention, Perception, & Psychophysics

, Volume 80, Issue 5, pp 1157–1168 | Cite as

Memory guidance in distractor suppression is governed by the availability of cognitive control

  • Wen Wen
  • Yin Hou
  • Sheng Li
Article
  • 190 Downloads

Abstract

Information stored in the memory systems can affect visual search. Previous studies have shown that holding the to-be-ignored features of distractors in working memory (WM) could accelerate target selection. However, such facilitation effect was only observed when the cued to-be-ignored features remained unchanged within an experimental block (i.e., the fixed cue condition). No search benefit was obtained if the to-be-ignored features varied from trial to trial (i.e., the varied cue condition). In the present study, we conducted three behavioral experiments to investigate whether the WM and long-term memory (LTM) representations of the to-be-ignored features could facilitate visual search in the fixed cue (Experiment 1) and varied cue (Experiments 2 and 3) conditions. Given the importance of the processing time of cognitive control in distractor suppression, we divided visual search trials into five quintiles based on their reaction times (RTs) and examined the temporal characteristics of the suppression effect. Results showed that both the WM and LTM representations of the to-be-ignored features could facilitate distractor suppression in the fixed cue condition, and the facilitation effects were evident across the quintiles in the RT distribution. However, in the varied cue condition, the RT benefits of the WM-matched distractors occurred only in the trials with the longest RTs, whereas no advantage of the LTM-matched distractors was observed. These results suggest that the effective WM-guided distractor suppression depends on the availability of cognitive control and the LTM-guided suppression occurs only if sufficient WM resource is accessible by LTM reactivation.

Keywords

Attention and memory Cognitive and attentional control Visual search 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (31470974, 31230029) and the National Key R&D Program of China (2017YFB1002503).

References

  1. Anderson, B. A., Laurent, P. A., & Yantis, S. (2011). Value-driven attentional capture. Proceedings of the National Academy of Sciences, 108(25), 10367–10371.CrossRefGoogle Scholar
  2. Arita, J. T., Carlisle, N. B., & Woodman, G. F. (2012). Templates for rejection: Configuring attention to ignore task-irrelevant features. Journal of experimental psychology: human perception and performance, 38(3), 580–584.PubMedGoogle Scholar
  3. Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. Psychology of learning and motivation, 2, 89–195.CrossRefGoogle Scholar
  4. Baddeley, A. (1992). Working memory. Science, 255(5044), 556–559.Google Scholar
  5. Baddeley, A. D., & Hitch, G. (1974). Working memory. Psychology of learning and motivation, 8, 47–89.CrossRefGoogle Scholar
  6. Brainard, D. H. (1997). The psychophysics toolbox. Spatial Vision, 10(4), 433–436.CrossRefPubMedGoogle Scholar
  7. Braver, T. S. (2012). The variable nature of cognitive control: A dual mechanisms framework. Trends in cognitive sciences, 16(2), 106–113.CrossRefPubMedPubMedCentralGoogle Scholar
  8. Braver, T. S., Gray, J. R., & Burgess, G. C. (2007). Explaining the many varieties of working memory variation: Dual mechanisms of cognitive control. In Variation in Working Memory (Conway, A. et al., eds), pp. 76–106, New York, NY: Oxford University Press.Google Scholar
  9. Bundesen, C. (1990). A theory of visual attention. Psychological review, 97(4), 523.CrossRefPubMedGoogle Scholar
  10. Carlisle, N. B., & Woodman, G. F. (2011). When memory is not enough: Electrophysiological evidence for goal-dependent use of working memory representations in guiding visual attention. Journal of Cognitive Neuroscience, 23(10), 2650–2664.CrossRefPubMedPubMedCentralGoogle Scholar
  11. Chen, Y., & Du, F. (2017). Two visual working memory representations simultaneously control attention. Scientific reports, 7, 6107.CrossRefPubMedPubMedCentralGoogle Scholar
  12. Cunningham, C. A., & Egeth, H. E. (2016). Taming the white bear initial costs and eventual benefits of distractor inhibition. Psychological science, 27(4), 476–485.Google Scholar
  13. Dalvit, S., & Eimer, M. (2011). Memory-driven attentional capture is modulated by temporal task demands. Visual Cognition, 19(2), 145–153.CrossRefGoogle Scholar
  14. Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual review of neuroscience, 18(1), 193–222.CrossRefPubMedGoogle Scholar
  15. D'esposito, M., & Postle, B. R. (2015). The cognitive neuroscience of working memory. Annual review of psychology, 66, 115–142.CrossRefPubMedGoogle Scholar
  16. Downing, P., & Dodds, C. (2004). Competition in visual working memory for control of search. Visual Cognition, 11(6), 689–703.CrossRefGoogle Scholar
  17. Downing, P. E. (2000). Interactions between visual working memory and selective attention. Psychological Science, 11(6), 467–473.CrossRefPubMedGoogle Scholar
  18. Fan, J. E., & Turk-Browne, N. B. (2016). Incidental biasing of attention from visual long-term memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 42(6), 970.PubMedGoogle Scholar
  19. Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior research methods, 39(2), 175–191.CrossRefPubMedGoogle Scholar
  20. Fukuda, K., & Woodman, G. F. (2017). Visual working memory buffers information retrieved from visual longterm memory. Proceedings of the National Academy of Sciences, 114, 5306–5311.Google Scholar
  21. Gaspelin, N., Leonard, C. J., & Luck, S. J. (2015). Direct evidence for active suppression of salient-butirrelevant sensory inputs. Psychological science, 26(11), 1740–1750.Google Scholar
  22. Gaspelin, N., Leonard, C. J., & Luck, S. J. (2017). Suppression of overt attentional capture by salient-but-irrelevant color singletons. Attention, Perception, & Psychophysics, 79(1), 45–62.CrossRefGoogle Scholar
  23. Geng, J. J. (2014). Attentional mechanisms of distractor suppression. Current Directions in Psychological Science, 23(2), 147–153.CrossRefGoogle Scholar
  24. Gong, M., Jia, K., & Li, S. (2017). Perceptual competition promotes suppression of reward salience in behavioral selection and neural representation. Journal of Neuroscience, 37(26), 6242–6252.Google Scholar
  25. Gong, M., Yang, F., & Li, S. (2016). Reward association facilitates distractor suppression in human visual search. European Journal of Neuroscience, 43(7), 942–953.CrossRefPubMedGoogle Scholar
  26. Han, S. W., & Kim, M. S. (2009). Do the contents of working memory capture attention? Yes, but cognitive control matters. Journal of Experimental Psychology: Human Perception and Performance, 35(5), 1292.PubMedGoogle Scholar
  27. Hollingworth, A., & Beck, V. M. (2016). Memory-based attention capture when multiple items are maintained in visual working memory. Journal of experimental psychology: human perception and performance, 42(7), 911.PubMedGoogle Scholar
  28. Houtkamp, R., & Roelfsema, P. R. (2006). The effect of items in working memory on the deployment of attention and the eyes during visual search. Journal of Experimental Psychology: Human Perception and Performance, 32(2), 423.PubMedGoogle Scholar
  29. Hutchinson, J. B., & Turk-Browne, N. B. (2012). Memory-guided attention: Control from multiple memory systems. Trends in cognitive sciences, 16(12), 576–579.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 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
  31. Kiyonaga, A., Egner, T., & Soto, D. (2012). Cognitive control over working memory biases of selection. Psychonomic bulletin & review, 19(4), 639–646.CrossRefGoogle Scholar
  32. Kleiner, M., Brainard, D., Pelli, D., Ingling, A., Murray, R., & Broussard, C. (2007). What’s new in Psychtoolbox-3. Perception, 36(14), 1.Google Scholar
  33. Lu, J., Tian, L., Zhang, J., Wang, J., Ye, C., & Liu, Q. (2017). Strategic inhibition of distractors with visual working memory contents after involuntary attention capture. Scientific reports, 7(1), 16314.CrossRefPubMedPubMedCentralGoogle Scholar
  34. Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390(6657), 279.CrossRefPubMedGoogle Scholar
  35. Mannan, S. K., Kennard, C., Potter, D., Pan, Y., & Soto, D. (2010). Early oculomotor capture by new onsets driven by the contents of working memory. Vision research, 50(16), 1590–1597.CrossRefPubMedGoogle Scholar
  36. Moher, J., & Egeth, H. E. (2012). The ignoring paradox: Cueing distractor features leads first to selection, then to inhibition of to-be-ignored items. Attention, Perception, & Psychophysics, 74(8), 1590–1605.CrossRefGoogle Scholar
  37. Moher, J., Lakshmanan, B. M., Egeth, H. E., & Ewen, J. B. (2014). Inhibition drives early feature-based attention. Psychological science, 25(2), 315–324.CrossRefPubMedPubMedCentralGoogle Scholar
  38. Noonan, M. P., Adamian, N., Pike, A., Printzlau, F., Crittenden, B. M., & Stokes, M. G. (2016). Distinct mechanisms for distractor suppression and target facilitation. Journal of Neuroscience, 36(6), 1797–1807.CrossRefPubMedGoogle Scholar
  39. Olivers, C. N. (2009). What drives memory-driven attentional capture? The effects of memory type, display type, and search type. Journal of Experimental Psychology: Human Perception and Performance, 35(5), 1275.PubMedGoogle Scholar
  40. Olivers, C. N. (2011). Long-term visual associations affect attentional guidance. Acta psychologica, 137(2), 243–247.CrossRefPubMedGoogle Scholar
  41. Olivers, C. N., Meijer, F., & Theeuwes, J. (2006). Feature-based memory-driven attentional capture: Visual working memory content affects visual attention. Journal of Experimental Psychology: Human Perception and Performance, 32(5), 1243.PubMedGoogle Scholar
  42. Olivers, C. N., Peters, J., Houtkamp, R., & Roelfsema, P. R. (2011). Different states in visual working memory: When it guides attention and when it does not. Trends in cognitive sciences, 15(7), 327–334.PubMedGoogle Scholar
  43. Peters, J. C., Goebel, R., & Roelfsema, P. R. (2009). Remembered but unused: The accessory items in working memory that do not guide attention. Journal of Cognitive Neuroscience, 21(6), 1081–1091.CrossRefPubMedGoogle Scholar
  44. Schmidt, L. J., Belopolsky, A. V., & Theeuwes, J. (2015). Attentional capture by signals of threat. Cognition and emotion, 29(4), 687–694.CrossRefPubMedGoogle Scholar
  45. 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 and Performance, 31(2), 248.PubMedGoogle Scholar
  46. Soto, D., Hodsoll, J., Rotshtein, P., & Humphreys, G. W. (2008). Automatic guidance of attention from working memory. Trends in cognitive sciences,12(9), 342–348.CrossRefPubMedGoogle Scholar
  47. Soto, D., & Humphreys, G. W. (2007). Automatic guidance of visual attention from verbal working memory. Journal of Experimental Psychology Human Perception and Performance, 33(3), 730.CrossRefPubMedGoogle Scholar
  48. Soto, D., & Humphreys, G. W. (2008). Stressing the mind: The effect of cognitive load and articulatory suppression on attentional guidance from working memory. Attention, Perception, & Psychophysics, 70(5), 924–934.CrossRefGoogle Scholar
  49. Soto, D., & Humphreys, G. W. (2009). Automatic selection of irrelevant object features through working memory: Evidence for top-down attentional capture. Experimental psychology, 56(3), 165–172.CrossRefPubMedGoogle Scholar
  50. Stokes, M. G., Atherton, K., Patai, E. Z., & Nobre, A. C. (2012). Long-term memory prepares neural activity for perception. Proceedings of the National Academy of Sciences, 109(6), E360–E367.CrossRefGoogle Scholar
  51. Theeuwes, J. (1992). Perceptual selectivity for color and form. Attention, Perception, & Psychophysics, 51(6), 599–606.Google Scholar
  52. Theeuwes, J. (2010). Top–down and bottom–up control of visual selection. Acta Psychologica, 135(2), 77–99.Google Scholar
  53. Van Selst, M., & Jolicoeur, P. (1994). A solution to the effect of sample size on outlier elimination. Quarterly Journal of Experimental Psychology, 47A, 631–650.Google Scholar
  54. Vatterott, D. B., & Vecera, S. P. (2012). Experience-dependent attentional tuning of distractor rejection. Psychonomic bulletin & review, 19(5), 871–878.CrossRefGoogle Scholar
  55. Wolfe, J. M. (1994). Guided search 2.0 a revised model of visual search. Psychonomic bulletin & review, 1(2), 202–238.CrossRefGoogle Scholar
  56. Woodman, G. F., Carlisle, N. B., & Reinhart, R. M. (2013). Where do we store the memory representations that guide attention? Journal of Vision, 13(3), 1–1.CrossRefPubMedPubMedCentralGoogle Scholar
  57. Woodman, G. F., & Chun, M. M. (2006). The role of working memory and long-term memory in visual search. Visual Cognition, 14(4-8), 808–830.CrossRefGoogle Scholar
  58. 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
  59. Yi, D. J., Turk-Browne, N. B., Chun, M. M., & Johnson, M. K. (2008). When a thought equals a look: Refreshing enhances perceptual memory. Journal of Cognitive Neuroscience, 20(8), 1371–1380.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© The Psychonomic Society, Inc. 2018

Authors and Affiliations

  1. 1.School of Psychological and Cognitive SciencesPeking UniversityBeijingChina
  2. 2.Beijing Key Laboratory of Behavior and Mental HealthPeking UniversityBeijingChina
  3. 3.PKU-IDG/McGovern Institute for Brain ResearchPeking UniversityBeijingChina
  4. 4.Key Laboratory of Machine Perception (Ministry of Education)Peking UniversityBeijingChina
  5. 5.Department of Psychology, School of Sociology and PsychologyCentral University of Finance and EconomicsBeijingChina

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