Attention, Perception, & Psychophysics

, Volume 80, Issue 6, pp 1420–1435 | Cite as

On the limits of statistical learning: Intertrial contextual cueing is confined to temporally close contingencies

  • Cyril Thomas
  • André Didierjean
  • François Maquestiaux
  • Annabelle Goujon


Since the seminal study by Chun and Jiang (Cognitive Psychology, 36, 28–71, 1998), a large body of research based on the contextual-cueing paradigm has shown that the cognitive system is capable of extracting statistical contingencies from visual environments. Most of these studies have focused on how individuals learn regularities found within an intratrial temporal window: A context predicts the target position within a given trial. However, Ono, Jiang, and Kawahara (Journal of Experimental Psychology, 31, 703–712, 2005) provided evidence of an intertrial implicit-learning effect when a distractor configuration in preceding trials N − 1 predicted the target location in trials N. The aim of the present study was to gain further insight into this effect by examining whether it occurs when predictive relationships are impeded by interfering task-relevant noise (Experiments 2 and 3) or by a long delay (Experiments 1, 4, and 5). Our results replicated the intertrial contextual-cueing effect, which occurred in the condition of temporally close contingencies. However, there was no evidence of integration across long-range spatiotemporal contingencies, suggesting a temporal limitation of statistical learning.


Intertrial association Contextual cuing Visual attention Visual search Statistical learning 


  1. Armstrong, B. C., Frost, R., & Christiansen, M. H. (2017). The long road of statistical learning research: Past, present and future. Philosophical Transactions of the Royal Society B: Biological Sciences, 372(1711). doi:
  2. Aslin, R. N., & Newport, E. L. (2012). Statistical learning: From acquiring specific items to forming general rules. Current Directions in Psychological Science, 21, 170–176.CrossRefPubMedPubMedCentralGoogle Scholar
  3. Baker, C. I., Olson, C. R., & Behrmann, M. (2004). Role of attention and perceptual grouping in visual statistical learning. Psychological Science, 15, 460–466.CrossRefPubMedGoogle Scholar
  4. Chun, M. M., & Jiang, Y. (1998). Contextual cueing: Implicit learning and memory of visual context guides spatial attention. Cognitive Psychology, 36, 28–71.CrossRefPubMedGoogle Scholar
  5. Chun, M. M., & Jiang, Y. (1999). Top-down attentional guidance based on implicit learning of visual covariation. Psychological Science, 10, 360–365.CrossRefGoogle Scholar
  6. Chun, M. M., & Jiang, Y. (2003). Implicit, long-term spatial contextual memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 224–234.PubMedGoogle Scholar
  7. Colagiuri, B., & Livesey, E. (2016). Contextual cuing as a form of nonconscious learning: Theoretical and empirical analysis in large and very large samples. Psychonomic Bulletin & Review, 23, 1996–2009.CrossRefGoogle Scholar
  8. Conci, M., & von Mühlenen, A. (2011). Limitations of perceptual segmentation on contextual cueing in visual search. Visual Cognition 19, 203–233.CrossRefGoogle Scholar
  9. Endo, N., & Takeda, Y. (2004). Selective learning of spatial configuration and object identity in visual search. Perception and Psychophysics. 66, 293–302.CrossRefPubMedGoogle Scholar
  10. Erickson, L. C., & Thiessen, E. D. (2015). Statistical learning of language: Theory, validity, and predictions of a statistical learning account of language acquisition. Developmental Review, 37, 66–108.CrossRefGoogle Scholar
  11. Ferrand, L. (1996). The masked repetition priming effect dissipates when increasing the interstimulus interval: Evidence from word naming. Acta Psychologica, 91, 15–25.CrossRefGoogle Scholar
  12. Forster, K. I. (1976). Accessing the mental lexicon. In R. J. Wales & E. Walker (Eds.), New approaches to language mechanisms. Amsterdam: North-Holland.Google Scholar
  13. Forster, K. I., & Davis, C. (1984). Repetition priming and frequency attenuation in lexical access. Journal of Experimental Psychology: Learning, Memory and Cognition, 10, 680–698.Google Scholar
  14. Gebhart, A. L., Newport, E. L., & Aslin, R. N. (2009). Statistical learning of adjacent and nonadjacent dependencies among nonlinguistic sounds. Psychonomic Bulletin & Review, 16, 486–490.CrossRefGoogle Scholar
  15. Gobet, F., Lane, P. C. R., Croker, S., Cheng, P. C. H., Jones, G., Oliver, I., & Pine, J. M. (2001). Chunking mechanisms in human learning. Trends in Cognitive Sciences, 5, 236–243.CrossRefPubMedGoogle Scholar
  16. Goujon, A. (2011). Categorical implicit learning in real-world scenes: Evidence from contextual cuing. Quarterly Journal of Experimental Psychology, 64, 920–941.CrossRefGoogle Scholar
  17. Goujon, A., Didierjean, A., & Marmèche, E. (2007). Contextual cueing based on specific and categorical properties of the environment. Visual Cognition, 15, 257–275.CrossRefGoogle Scholar
  18. Goujon, A., Didierjean, A., & Marmèche, E. (2009). Semantic contextual cueing and visual attention. Journal of Experimental Psychology: Human Perception and Performance, 35, 50–71.PubMedGoogle Scholar
  19. Goujon, A., Didierjean, A., & Poulet, S. (2014). The emergence of explicit knowledge from implicit learning. Memory & Cognition, 42, 225–236.CrossRefGoogle Scholar
  20. Goujon, A., Didierjean, A., & Thorpe, S. (2015). Investigating implicit statistical learning mechanisms through contextual cueing. Trends in Cognitive Sciences, 9, 524–533.CrossRefGoogle Scholar
  21. Hoffmann, J., & Sebald, A. (2005). Local contextual cuing in visual search. Experimental Psychology, 52, 31–38.CrossRefPubMedGoogle Scholar
  22. Hunt, R. H., & Aslin, R. N. (2001). Statistical learning in a serial reaction time task: Access to separable statistical cues by individual learners. Journal of Experimental Psychology: General, 130, 658–680.CrossRefGoogle Scholar
  23. Jeffreys, H. (1961). Theory of probability. Oxford: Oxford University Press.Google Scholar
  24. Jiang, Y., & Chun, M. M. (2001). Selective attention modulates implicit learning. Quarterly Journal of Experimental Psychology: Section A, 54, 1105–1124.CrossRefGoogle Scholar
  25. Jiang, Y., & Leung, A. W. (2005). Implicit learning of ignored visual context. Psychonomic Bulletin & Review, 12, 100–106.CrossRefGoogle Scholar
  26. Jiang, Y., & Song, J.-H. (2005). Hyperspecificity in visual implicit learning: Learning of spatial layout is contingent on item identity. Journal of Experimental Psychology: Human Perception and Performance, 31, 1439–1448.PubMedGoogle Scholar
  27. Jiménez, L., & Vázquez, G. A. (2011). Implicit sequence learning and contextual cueing do not compete for central cognitive resources. Journal of Experimental Psychology: Human Perception and Performance, 37, 222–235.PubMedGoogle Scholar
  28. Love, J., Selker, R., Verhagen, J., Marsman, M., Gronau, Q. F., Jamil, T., … Wagenmakers, E. J. (2015). JASP (Version 0.6) [Computer software].Google Scholar
  29. Newport, E. L., Aslin, R. N. (2004). Learning at a distance: I. Statistical learning of nonadjacent dependencies. Cognitive Psychology, 48, 127–162.CrossRefPubMedGoogle Scholar
  30. Olson, I. R., & Chun, M. M. (2001). Temporal contextual cuing of visual attention. Journal of Experimental Psychology: Learning, Memory, and Cognition, 27, 1299–1313.PubMedGoogle Scholar
  31. Olson, I. R., & Chun, M. M. (2002). Perceptual constraints on implicit learning of spatial context. Visual Cognition, 9, 273–302.CrossRefGoogle Scholar
  32. Onnis, L., Monaghan, P., Richmond, K., & Chater, N. (2005). Phonology impacts segmentation in online speech processing. Journal of Memory & Language, 53, 225–237.CrossRefGoogle Scholar
  33. Ono, F., Jiang, Y., & Kawahara, J. (2005). Intertrial temporal contextual cuing: Association across successive visual search trials guides spatial attention. Journal of Experimental Psychology: Human Perception and Performance, 31, 703–712.PubMedGoogle Scholar
  34. Perruchet, P., & Pacton, S. (2006). Implicit learning and statistical learning: Two approaches, one phenomenon. Trends in Cognitive Sciences, 10, 233–238.CrossRefPubMedGoogle Scholar
  35. Perruchet, P., & Vinter, A. (1998). PARSER: A model for word segmentation. Journal of Memory and Language, 39, 246–263.CrossRefGoogle Scholar
  36. Perruchet, P., & Vinter, A. (2002). The self-organizing consciousness. Behavioral and Brain Sciences, 25, 297–388.PubMedGoogle Scholar
  37. Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56, 356–374.CrossRefGoogle Scholar
  38. Smyth, A. C., & Shanks, D. R. (2008). Awareness in contextual cueing with extended and concurrent explicit tests. Memory & Cognition, 36, 403–415.CrossRefGoogle Scholar
  39. Thiessen, E. D. (2017). What’s statistical about learning? Insights from modelling statistical learning as a set of memory processes. Philosophical Transactions of the Royal Society B: Biological Sciences, 372. doi:
  40. Turk-Browne, N. B., Isola, P. J., Scholl, B. J., & Treat, T. A. (2008). Multidimensional visual statistical learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34, 399–407.PubMedGoogle Scholar
  41. Turk-Browne, N. B., Junge, J. A., & Scholl, B. J. (2005). The automaticity of visual statistical learning. Journal of Experimental Psychology: General, 134, 552–564.CrossRefGoogle Scholar
  42. Turk-Browne, N. B., & Scholl, B. J. (2009). Flexible visual statistical learning: Transfer across space and time. Journal of Experimental Psychology: Human Perception and Performance, 35, 195–202.PubMedGoogle Scholar
  43. Turk-Browne, N. B., Scholl, B. J., Chun, M. M., & Johnson, M. K. (2009). Neural evidence of statistical learning: Efficient detection of visual regularities without awareness. Journal of Cognitive Neuroscience, 21, 1934–1945.CrossRefPubMedPubMedCentralGoogle Scholar
  44. Vadillo, M. A., Konstantinidis, E., & Shanks, D. R. (2016). Underpowered samples, false negatives, and unconscious learning. Psychonomic Bulletin & Review, 23, 87–102.CrossRefGoogle Scholar

Copyright information

© The Psychonomic Society, Inc. 2018

Authors and Affiliations

  1. 1.Université de Bourgogne-Franche-ComtéBesançonFrance
  2. 2.Laboratoire de Psychologie de l’Université de Franche-ComtéBesançonFrance
  3. 3.Institut Universitaire de FranceParisFrance

Personalised recommendations