Attention, Perception, & Psychophysics

, Volume 80, Issue 5, pp 1096–1109 | Cite as

Predictive visual search: Role of environmental regularities in the learning of context cues

  • Artyom Zinchenko
  • Markus Conci
  • Hermann J. Müller
  • Thomas Geyer


Repeatedly searching through invariant spatial arrangements in visual search displays leads to the buildup of memory about these displays (contextual-cueing effect). In the present study, we investigate (1) whether contextual cueing is influenced by global statistical properties of the task and, if so, (2) whether these properties increase the overall strength (asymptotic level) or the temporal development (speed) of learning. Experiment 1a served as baseline against which we tested the effects of increased or decreased proportions of repeated relative to nonrepeated displays (Experiments 1b and 1c, respectively), thus manipulating the global statistical properties of search environments. Importantly, probability variations were achieved by manipulating the number of nonrepeated (baseline) displays so as to equate the total number of repeated displays across experiments. In Experiment 1d, repeated and nonrepeated displays were presented in longer streaks of trials, thus establishing a stable environment of sequences of repeated displays. Our results showed that the buildup of contextual cueing was expedited in the statistically rich Experiments 1b and 1d, relative to the baseline Experiment 1a. Further, contextual cueing was entirely absent when repeated displays occurred in the minority of trials (Experiment 1c). Together, these findings suggest that contextual cueing is modulated by observers’ assumptions about the reliability of search environments.


Environmental statistics Contextual cueing Predictive coding Visual search 



This research was supported by a project grant from the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG, Grant GE 1889/4-1) to T. Geyer and M. Conci.


  1. Annac, E., Conci, M., Müller, H. J., & Geyer, T. (2017). Local item density modulates adaptation of learned contextual cues. Visual Cognition, 25, 262–277. doi: CrossRefGoogle Scholar
  2. Annac, E., Manginelli, A. A., Pollmann, S., Shi, Z., Müller, H. J., & Geyer, T. (2013). Memory under pressure: Secondary-task effects on contextual cueing of visual search. Journal of Vision, 13(6), 1–15. doi: CrossRefGoogle Scholar
  3. Assumpção, L., Shi, Z., Zang, X., Müller, H. J., & Geyer, T. (2015). Contextual cueing: Implicit memory of tactile context facilitates tactile search. Attention, Perception, & Psychophysics, 77(4), 1212–22. doi: CrossRefGoogle Scholar
  4. Brainard, D. H. (1997). The psychophysics toolbox. Spatial Vision, 10, 433–436. doi: CrossRefPubMedGoogle Scholar
  5. Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354–380.Google Scholar
  6. Chun, M. M. (2000). Contextual cueing of visual attention. Trends in Cognitive Sciences, 4(5):170-178. doi: CrossRefPubMedGoogle Scholar
  7. Chun, M. M., & Jiang, Y. (1998). Contextual cueing: Implicit learning and memory of visual context guides spatial attention. Cognitive Psychology, 36(1), 28–71. doi: CrossRefPubMedGoogle Scholar
  8. Chun, M. M., & Jiang, Y. (1999). Top-down attentional guidance based on implicit learning of visual covariation. Psychological Science, 10, 360–365. doi: CrossRefGoogle Scholar
  9. Chun, M. M., & Jiang, Y. V. (2003). Implicit, long-term spatial contextual memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(2), 224–234. doi: PubMedGoogle Scholar
  10. Chun, M. M., & Phelps, E. A. (1999). Memory deficits for implicit contextual information in amnesic subjects with hippocampal damage. Nature Neuroscience, 2(9), 844–847. doi: CrossRefPubMedGoogle Scholar
  11. Chun, M. M., & Turk-Browne, N. B. (2008). Associative learning mechanisms in vision. In S. J. Luck & Hollingworth, A. (Eds.), Visual memory (pp. 209–245). Oxford, UK: Oxford University Press. doi: CrossRefGoogle Scholar
  12. Colagiuri, B., & Livesey, E. J. (2016). Contextual cuing as a form of nonconscious learning: Theoretical and empirical analysis in large and very large samples. Psychonomic Bulletin & Review, 23(6), 1996–2009. doi: CrossRefGoogle Scholar
  13. Conci, M., Zellin, M., & Müller, H. J. (2012). Whatever after next? Adaptive predictions based on short- and long-term memory in visual search. Frontiers in Psychology, 3, 409. doi: CrossRefPubMedPubMedCentralGoogle Scholar
  14. Dempster, F. N. (1987). Effects of variable encoding and spaced presentations on vocabulary learning. Journal of Educational Psychology, 79(2), 162–170. doi: CrossRefGoogle Scholar
  15. den Ouden, H. E., Kok, P., & de Lange, F. P. (2012). How prediction errors shape perception, attention, and motivation. Frontiers in Psychology, 3, 548. doi: Google Scholar
  16. Dienes, Z. (2013). How Bayesian statistics are needed to determine whether mental states are unconscious. Behavioural Methods in Consciousness Research, 1–5. doi:
  17. Friston, K. (2010). The free-energy principle: A unified brain theory? Nature Reviews. Neuroscience, 11(2), 127–138. doi: CrossRefPubMedGoogle Scholar
  18. Geringswald, F., Herbik, A., Hofmüller, W., Hoffmann, M. B., & Pollmann, S. (2015). Visual memory for objects following foveal vision loss. Journal of Experimental Psychology: Learning, Memory, and Cognition, 41, 1471–1484.PubMedGoogle Scholar
  19. Geyer, T., Müller, H.J., & Krummenacher, J. (2008). Expectancies modulate attentional capture by salient color singletons. Vision Research, 48, 1315–1326.Google Scholar
  20. Geyer, T., Müller, H. J., Assumpcao, L., & Gais, S. (2013). Sleep-effects on implicit and explicit memory in repeated visual search. PLoS ONE, 8(8), e69953. doi: CrossRefPubMedPubMedCentralGoogle Scholar
  21. Geyer, T., Zehetleitner, M., & Müller, H. J. (2010). Contextual cueing of pop-out visual search: When context guides the deployment of attention. Journal of Vision, 10, 20. doi:10.1167/10.5.20Google Scholar
  22. Gold, J. I., & Shadlen, M. N. (2007). The neural basis of decision making. Annual Reviews in Neuroscience, 30, 535–574. doi: CrossRefGoogle Scholar
  23. Goujon, A., Didierjean, A., & Thorpe, S. (2015). Investigating implicit statistical learning mechanisms through contextual cueing. Trends in Cognitive Sciences, 19(9), 524–533. doi: CrossRefPubMedGoogle Scholar
  24. Hohwy, J. (2015). The predictive mind. CEUR Workshop Proceedings (Vol. 1542). doi:
  25. Huang, Y., & Rao, R. P. N. (2011). Predictive coding. Wiley Interdisciplinary Reviews: Cognitive Science, 2(5), 580–593. doi: PubMedGoogle Scholar
  26. Jarosz, A. F., & Wiley, J. (2014). What are the odds? A practical guide to computing and reporting Bayes factors. The Journal of Problem Solving, 7, 2–9. doi: CrossRefGoogle Scholar
  27. Jeffreys, H. (1961). Theory of probability. Oxford, UK: Clarendon Press.Google Scholar
  28. Jiang, Y., & Leung, A. W. (2005). Implicit learning of ignored visual context. Psychonomic Bulletin & Review, 12(1), 100–106. doi: CrossRefGoogle Scholar
  29. Jiang, Y., Song, J.-H., & Rigas, A. (2005). High-capacity spatial contextual memory. Psychonomic Bulletin & Review, 12(3), 524–529.CrossRefGoogle Scholar
  30. Johnson, J. S., Woodman, G. F., Braun, E. L., & Luck, S. J. (2007). Implicit memory influences the allocation of attention in visual cortex. Psychonomic Bulletin & Review, 14(5), 834–839. doi: CrossRefGoogle Scholar
  31. Jungé, J. A., Scholl, B. J., & Chun, M. M. (2007). How is spatial context learning integrated over signal versus noise? A primacy effect in contextual cueing. Visual Cognition, 15(1), 1–11. doi: CrossRefPubMedPubMedCentralGoogle Scholar
  32. Kersten, D., Mamassian, P., & Yuille, A. (2004). Object perception as Bayesian inference. Annual Review of Psychology, 55, 271–304. doi: CrossRefPubMedGoogle Scholar
  33. Kirsner, K., Smith, M. C., Lockhart, R. S., King, M. L., & Jain, M. (1984). The bilingual lexicon: Language-specific units in an integratednetwork, Journal of Verbal Leaming and Verbal Behavior, 23, 519–539.Google Scholar
  34. Kornell, N., & Bjork, R.A. (2008). Learning concepts and categories: Is spacing the “enemy of induction”? Psychological Science, 19, 585–92.Google Scholar
  35. Kovacs, G., Kaiser, D., Kaliukhovich, D. A., Vidnyanszky, Z. & Vogels, R. (2013). Repetition probability does not affect fMRI repetition suppression for objects. Journal of Neuroscience, 33, 9805–9812Google Scholar
  36. Kristjansson, A., Wang, D. L., & Nakayama, K. (2002). The role of priming in conjunctive visual search. Cognition, 85(1), 37–52. doi: CrossRefPubMedGoogle Scholar
  37. Kunar, M. A., Flusberg, S., Horowitz, T. S., & Wolfe, J. M. (2007). Does contextual cuing guide the deployment of attention? Journal of Experimental Psychology: Human Perception and Performance, 33(4), 816–828. doi: PubMedGoogle Scholar
  38. Larsson, J., & Smith, A. T. (2012). fMRI repetition suppression: Neuronal adaptation or stimulus expectation? Cerebral Cortex, 22(3), 567–576. doi: CrossRefPubMedGoogle Scholar
  39. Marsman, M., & Wagenmakers, E.-J. (2017). Bayesian benefits with JASP. European Journal of Developmental Psychology, 14(5), 545–555. doi: CrossRefGoogle Scholar
  40. Müller, H.J., Geyer, T., Zehetleitner, M. & Krummenacher, J. (2009). Attentional capture by salient color singleton distractors is modulated by top-down dimensional set. Journal of Experimental Psychology: Human Perception & Performance, 35, 1–16.Google Scholar
  41. Palmer, S. E. (1975). The effects of contextual scenes on the identification of objects. Memory & Cognition, 3(5), 519–526. doi: CrossRefGoogle Scholar
  42. Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision, 10(4), 437–442. doi: CrossRefPubMedGoogle Scholar
  43. Peterson, M. S., & Kramer, A. F. (2001). Attentional guidance of the eyes by contextual information and abrupt onsets. Perception & Psychophysics, 63(7), 1239–1249. doi: CrossRefGoogle Scholar
  44. Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009). Bayesian t tests for accepting and rejecting the null hypothesis. Psychonomic Bulletin & Review, 16(2), 225–237. doi: CrossRefGoogle Scholar
  45. Schankin, A., & Schubö, A. (2009). Cognitive processes facilitated by contextual cueing. Evidence from event-related brain potentials. Psychophysiology, 46, 668–679. doi: CrossRefPubMedGoogle Scholar
  46. Schankin, A., & Schubö, A. (2010). Contextual cueing effects despite of spatially cued target locations. Psychophysiology, 47, 717–727. PubMedGoogle Scholar
  47. Schlagbauer, B., Müller, H. J., Zehetleitner, M., & Geyer, T. (2012). Awareness in contextual cueing of visual search as measured with concurrent access- and phenomenal- consciousness tasks. Journal of Vision, 12(11), 1–12. doi: CrossRefGoogle Scholar
  48. Smyth, A. C., & Shanks, D. R. (2008). Awareness in contextual cuing with extended and concurrent explicit tests. Memory & Cognition, 36(2), 403–415. doi: CrossRefGoogle Scholar
  49. Summerfield, C., Trittschuh, E. H., Monti, J. M., Mesulam, M. M., & Egner, T. (2008). Neural repetition suppression reflects fulfilled perceptual expectations. Nature Neuroscience, 11(9), 1004–1006. doi: CrossRefPubMedPubMedCentralGoogle Scholar
  50. Summerfield, C., Wyart, V., Johnen, V. M., & de Gardelle, V. (2011). Human scalp electroencephalography reveals that repetition suppression varies with expectation. Frontiers in Human Neuroscience, 5, 67. doi: CrossRefPubMedPubMedCentralGoogle Scholar
  51. Theeuwes, J. (1991). Cross-dimensional perceptual selectivity. Perception & Psychophysics, 50, 184–193.Google Scholar
  52. Töllner, T., Müller, H. J., & Zehetleitner, M. (2012). Top-down dimensional weight set determines the capture of visual attention: Evidence from the PCN component. Cerebral Cortex, 22(7), 1554-1563.Google Scholar
  53. Tseng, P., Hsu, T. Y., Tzeng, O. J. L., Hung, D. L., & Juan, C. H. (2011). Probabilities in implicit learning. Perception, 40(7), 822–829. doi: CrossRefPubMedGoogle Scholar
  54. Vadillo, M. A., Konstantinidis, E., & Shanks, D. R. (2015). Underpowered samples, false negatives, and unconscious learning. Psychonomic Bulletin & Review, 23(1), 87–102. doi: CrossRefGoogle Scholar
  55. van Asselen, M., & Castelo-Branco, M. (2009). The role of peripheral vision in implicit contextual cuing. Attention, Perception & Psychophysics, 71(1), 76–81. doi: CrossRefGoogle Scholar
  56. von Mühlenen, A., & Conci, M. (2016). The role of unique color changes and singletons in attention capture. Attention, Perception, & Psychophysics, 78(7), 1926–1934. doi: CrossRefGoogle Scholar
  57. 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 and Performance, 29(2), 483–502. doi: PubMedGoogle Scholar
  58. Zang, X., Zinchenko, A., Jia, L., Assumpção, L., Li, H. (2018) Global Repetition Influences Contextual Cueing. Frontiers in Psychology 9Google Scholar
  59. Zellin, M., Conci, M., von Mühlenen, A., & Müller, H. J. (2013). Here today, gone tomorrow - Adaptation to change in memory-guided visual search. PLOS ONE, 8(3), e59466. doi: CrossRefPubMedPubMedCentralGoogle Scholar
  60. Zellin, M., von Mühlenen, A., Müller, H. J., & Conci, M. (2013). Statistical learning in the past modulates contextual cueing in the future. Journal of Vision, 13(3),19, 1–14. doi: CrossRefPubMedGoogle Scholar
  61. Zellin, M., von Mühlenen, A., Müller, H. J., & Conci, M. (2014). Long-term adaptation to change in implicit contextual learning. Psychonomic Bulletin & Review, 21, 1073–1079. doi: Google Scholar

Copyright information

© The Psychonomic Society, Inc. 2018

Authors and Affiliations

  • Artyom Zinchenko
    • 1
  • Markus Conci
    • 1
  • Hermann J. Müller
    • 1
    • 2
  • Thomas Geyer
    • 1
  1. 1.Department Psychologie, Lehrstuhl für Allgemeine und Experimentelle PsychologieLudwig-Maximilians-Universität MünchenMunichGermany
  2. 2.Department of Psychological Science, Birkbeck CollegeUniversity of LondonLondonUK

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