Visual working-memory capacity load does not modulate distractor processing

Abstract

Over the last decade, researchers have explored the influence of visual working-memory (WM) load on selective attention in general, by focusing on the modulation of visual WM load on distractor processing in perception. However, there were three distinct hypotheses (perceptual-load hypothesis, resolution hypothesis, and domain-specific hypothesis) with different predictions. While the perceptual-load hypothesis suggests that visual WM capacity load serves as a type of perceptual load, the latter two hypotheses consider visual WM capacity load acting as a type of central executive load, with a constraint that the domain-specific hypothesis claimed that only a content overlap existed between WM load and the perceptual task. By adding a flanker task into the maintenance phase of visual WM, here we attempted to understand the influence of visual WM load on distractor processing. We systematically manipulated the parameters of the task setting between WM and flanker tasks (Experiments 14), the perceptual load of flanker task (Experiment 5), the settings of the flanker stimuli and the WM load (Experiment 6), and the content overlap between WM task and flanker task and the exposure time of flanker task (Experiments 7, 8, and 9). However, in 11 out of 12 sub-experiments we consistently found that the visual WM load did not modulate the distractor processing. The implications of these findings are discussed.

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Data availability

All the data are available at: https://osf.io/fns8a

All the programming codes are available at: https://osf.io/6rdz8

Notes

  1. 1.

    For simplicity, we refer to “Experiment 1b of Konstantinou et al. (2014)” as “Konstantinou et al. (2014)” henceforth.

  2. 2.

    The colored squares and the grid in Konstantinou et al. (2014) were 0.38° × 0.38°, 1.38° × 1.38°, respectively. Our setting hence was larger than Konstantinou et al. (2014). This was made to ensure the participants did not have difficulty in WM encoding.

  3. 3.

    Here we did not use the color pink as in Konstantinou et al. (2014), to improve color distinctions.

  4. 4.

    Zhang and Luck (2015) used a low load of memorizing two colors. To have a direct comparison with Experiment 1 and manipulating the load more effectively, we used a low memory load of memorizing one color in Experiment 2.

  5. 5.

    It is worth noting that the letters in Konstantinou et al. (2014) were “X” and “Z”; to be in line with Experiment 1, we used “X” and “N.”

  6. 6.

    Konstantinou et al. (2014) used a duration of 150 ms, with a question mark of 1,850 ms. The current setting was due to a programming bug. Yet we argue these slight differences should not affect the result pattern.

  7. 7.

    We thanked an anonymous reviewer for pointing out this possibility.

References

  1. Ahmed, L., & de Fockert, J. W. (2012a). Working memory load can both improve and impair selective attention: evidence from the Navon paradigm. Attention, Perception, & Psychophysics, 74(7), 1397-1405.

    Article  Google Scholar 

  2. Ahmed, L., & de Fockert, J. W. (2012b). Focusing on attention: The effects of working memory capacity and load on selective attention. PLoS One, 7(8). doi:ARTN e43101 DOI https://doi.org/10.1371/journal.pone.0043101

  3. Awh, E., Dhaliwal, H., Christensen, S., & Matsukura, M. (2001). Evidence for two components of object-based selection. Psychological Science, 12, 329–334. https://doi.org/10.1111/1467-9280.00360

    Article  Google Scholar 

  4. Baddeley, A. (2003). Working memory and language: an overview. Journal of Communication Disorders, 36(3), 189-208.

    Article  Google Scholar 

  5. Baddeley, A. (2012). Working memory: Theories, models, and controversies. Annual Review of Psychology, 63(1), 1-29.

    Article  Google Scholar 

  6. Baddeley, A. D., & Hitch, G. J. (1974). Working memory. In G. H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol. 8, pp. 47-89). New York: Academic Press.

    Google Scholar 

  7. Barnes, L. L., Nelson, J. K., & Reuter-Lorenz, P. A. (2001). Object-based attention and object-based working memory: Overlapping processes revealed by selective interference effects in humans. In C. Casanova & M. Ptito (Eds.), Progress in brain research (Vol. 134, pp. 471–481). Amsterdam: Elsevier. https://doi.org/10.1016/S0079-6123(01)34031-1

  8. Bettencourt, K. C., & Xu, Y. (2016). Decoding the content of visual short-term memory under distraction in occipital and parietal areas. Nature Neuroscience, 19(1), 150-157. doi:https://doi.org/10.1038/nn.4174

    Article  Google Scholar 

  9. Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision, 10(4), 433-436.

    Article  Google Scholar 

  10. Burnham, B. R., Sabia, M., & Langan, C. (2014). Components of working memory and visual selective attention. Journal of Experimental Psychology. Human Perception and Performance, 40(1), 391-403. doi:https://doi.org/10.1037/a0033753

    Article  Google Scholar 

  11. Buschman, T. J., & Miller, E. K. (2007). Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science, 315(5820), 1860-1862. doi:https://doi.org/10.1126/science.1138071

    Article  Google Scholar 

  12. Caparos, S., & Linnell, K. J. (2010). The spatial focus of attention is controlled at perceptual and cognitive levels. Journal of Experimental Psychology. Human Perception and Performance, 36(5), 1080-1107

    Article  Google Scholar 

  13. Chen, Z. (2012). Object-based attention: A tutorial review. Attention, Perception, & Psychophysics, 74, 784–802. https://doi.org/10.3758/s13414-012-0322-z

    Article  Google Scholar 

  14. Cohen, E. H., & Tong, F. (2015). Neural Mechanisms of Object-Based Attention. Cerebral Cortex, 25(4), 1080-1092.

    Article  Google Scholar 

  15. Cohen, M. A., Konkle, T., Rhee, J. Y., Nakayama, K., & Alvarez, G. A. (2014). Processing multiple visual objects is limited by overlap in neural channels. PNAS, 111(24), 8955-8960. doi:https://doi.org/10.1073/pnas.1317860111

    Article  Google Scholar 

  16. Cowan, N. (2001). The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24(1), 87-114; discussion 114-185.

    Article  Google Scholar 

  17. De Fockert, J. W. (2013). Beyond perceptual load and dilution: A review of the role of working memory in selective attention. Frontiers in Psychology, 4(287), 287-299.

    PubMed Central  Google Scholar 

  18. De Fockert, J. W., Rees, G., Frith, C. D., & Lavie, N. (2001). The Role of Working Memory in Visual Selective Attention. Science, 291(5509), 1803-1806.

    Article  Google Scholar 

  19. Dehaene, S., & Cohen, L. (2011). The unique role of the visual word form area in reading. Trends in Cognitive Sciences, 15(6), 254-262.

    Article  Google Scholar 

  20. Duncan, J. (1984). Selective attention and the organization of visual information. Journal of Experimental Psychology: General, 113, 501–517. https://doi.org/10.1037/0096-3445.113.4.501

    Article  Google Scholar 

  21. Egly, R., Driver, J., & Rafal, R. D. (1994). Shifting visual attention between objects and locations: Evidence from normal and parietal lesion subjects. Journal of Experimental Psychology: General, 123, 161–177. https://doi.org/10.1037/0096-3445.123.2.161

    Article  Google Scholar 

  22. Ester, E. F., Serences, J. T., & Awh, E. (2009). Spatially global representations in human primary visual cortex during working memory maintenance. Journal of Neuroscience, 29(48), 15258-15265.

    Article  Google Scholar 

  23. Failing, M., & Theeuwes, J. (2018). Selection history: How reward modulates selectivity of visual attention. Psychonomic Bulletin and Review, 25(2), 514-538. doi:https://doi.org/10.3758/s13423-017-1380-y

    Article  Google Scholar 

  24. Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G * Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149-1160.

    Article  Google Scholar 

  25. Haist, F., Song, A. W., Wild, K., Faber, T. L., Popp, C. A., & Morris, R. D. (2001). Linking sight and sound: fMRI evidence of primary auditory cortex activation during visual word recognition. Brain and Language, 76(3), 340-350.

    Article  Google Scholar 

  26. Harrison, S. A., & Tong, F. (2009). Decoding reveals the contents of visual working memory in early visual areas. Nature, 458(7238), 632-635.

    Article  Google Scholar 

  27. Jeffreys, H., & Lindsay, R. B. (1963). Theory of probability. Physics Today,16(3), 68-70.

    Article  Google Scholar 

  28. Jiang, Y. V., Remington, R. W., Asaad, A., Lee, H. J., & Mikkalson, T. C. (2016). Remembering faces and scenes: The mixed-category advantage in visual working memory. Journal of Experimental Psychology: Human Perception and Performance, 42(9), 1399-1411. doi:https://doi.org/10.1037/xhp0000228

    Article  Google Scholar 

  29. Joseph, J. E., Cerullo, M. A., Farley, A. B., Steinmetz, N. A., & Mier, C. R. (2006). fMRI correlates of cortical specialization and generalization for letter processing. Neuroimage, 32(2), 806-820.

    Article  Google Scholar 

  30. Kim, S. Y., Kim, M. S., & Chun, M. M. (2005). Concurrent working memory load can reduce distraction. PNAS, 102(45), 16524-16529. doi:https://doi.org/10.1073/pnas.0505454102

    Article  Google Scholar 

  31. Konstantinou, N., & Lavie, N. (2013). Dissociable roles of different types of working memory load in visual detection. Journal of Experimental Psychology. Human Perception and Performance, 39(4), 919-924. doi:https://doi.org/10.1037/a0033037

    Article  PubMed Central  Google Scholar 

  32. Konstantinou, N., Bahrami, B., Rees, G., & Lavie, N. (2012). Visual short-term memory load reduces retinotopic cortex response to contrast. Journal of Cognitive Neuroscience, 24(11), 2199-2210.

    Article  Google Scholar 

  33. Konstantinou, N., Beal, E., King, J. R., & Lavie, N. (2014). Working memory load and distraction: dissociable effects of visual maintenance and cognitive control. Attention, Perception, & Psychophysics, 76(7), 1985-1997. doi:https://doi.org/10.3758/s13414-014-0742-z

    Article  Google Scholar 

  34. Koshino, H., & Olid, P. (2015). Interactions between modality of working memory load and perceptual load in distractor processing. The Journal of General Psychology, 142(3), 135-149. doi:https://doi.org/10.1080/00221309.2015.1036830

    Article  Google Scholar 

  35. Lavie, N. (1995). Perceptual load as a necessary condition for selective attention. Journal of Experimental Psychology: Human Perception and Performance, 21(3), 451-468. doi:https://doi.org/10.1037/0096-1523.21.3.451

    Article  Google Scholar 

  36. Lavie, N. (2005). Distracted and confused?: selective attention under load. Trends in Cognitive Science, 9(2), 75-82. doi:https://doi.org/10.1016/j.tics.2004.12.004

    Article  Google Scholar 

  37. Lavie, N. (2010). Attention, distraction, and cognitive control under load. Current Directions in Psychological Science, 19(3), 143-148. doi:https://doi.org/10.1177/0963721410370295

    Article  Google Scholar 

  38. Lavie, N., & Tsal, Y. (1994). Perceptual load as a major determinant of the locus of selection in visual attention. Perception & Psychophysics, 56(2), 183-197.

    Article  Google Scholar 

  39. Lavie, N., Hirst, A., de Fockert, J. W., & Viding, E. (2004). Load theory of selective attention and cognitive control. Journal of Experimental Psychology: General, 133(3), 339-354. doi:https://doi.org/10.1037/0096-3445.133.3.339

    Article  Google Scholar 

  40. Lavie, N., Beck, D. M., & Konstantinou, N. (2014). Blinded by the load: Attention, awareness and the role of perceptual load. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 369(1641), 20130205-20130215. doi:https://doi.org/10.1098/rstb.2013.0205

    Article  Google Scholar 

  41. Lee, H., & Yi, D. (2018). Visual short-term memory load does not enhance attentional selection. Journal of Vision, 18(10), 1181. doi:https://doi.org/10.1167/18.10.1181

    Article  Google Scholar 

  42. Lin, S. H., & Yeh, Y. Y. (2014). Domain-specific control of selective attention. PLoS One, 9(5), e98260. doi:https://doi.org/10.1371/journal.pone.0098260

    Article  PubMed Central  Google Scholar 

  43. Linnell, K. J., & Caparos, S. (2011). Perceptual and cognitive load interact to control the spatial focus of attention. Journal of Experimental Psychology. Human Perception and Performance, 37(5), 1643-1648. doi:https://doi.org/10.1037/a0024669

    Article  Google Scholar 

  44. Linnell, K. J., & Caparos, S. (2013). Perceptual load and early selection: an effect of attentional engagement? Frontiers in Psychology, 4, 498. doi:https://doi.org/10.3389/fpsyg.2013.00498

    Article  PubMed Central  Google Scholar 

  45. Luck, S. J. , & Vogel, E. K. . (1997). The capacity of visual working memory for features and conjunctions. Nature, 390(6657), 279-281.

    Article  Google Scholar 

  46. Luck, S. J., & Vogel, E. K. (2013). Visual working memory capacity: From psychophysics and neurobiology to individual differences. Trends in Cognitive Sciences, 17(8), 391-400. doi:https://doi.org/10.1016/j.tics.2013.06.006

    Article  PubMed Central  Google Scholar 

  47. Matsukura, M., & Vecera, S. P. (2009). Interference between object-based attention and object-based memory. Psychonomic Bulletin & Review, 16, 529–536. https://doi.org/10.3758/PBR.16.3.529

    Article  Google Scholar 

  48. Moore, T., & Zirnsak, M. (2017). Neural mechanisms of selective visual attention. Annual Review of Psychology, 68(1), 47-72. doi:https://doi.org/10.1146/annurev-psych-122414-033400

    Article  Google Scholar 

  49. Mullen, K. Dumoulin, S. Hess, R. (2007). Color processing in the human LGN and cortex measured with fMRI. Journal of Vision, 7(15):4, 4a, http://journalofvision.org/7/15/4/, doi:https://doi.org/10.1167/7.15.4.

    Article  Google Scholar 

  50. Murphy, G., Groeger, J. A., & Greene, C. M. (2016). Twenty years of load theory-Where are we now, and where should we go next? Psychonomic Bulletin & Review, 23(5), 1-25.

    Article  Google Scholar 

  51. Oh, S. H., & Kim, M. S. (2004). The role of spatial working memory in visual search efficiency. Psychonomic Bulletin & Review, 11(2), 275-281.

    Article  Google Scholar 

  52. Remington, A., Cartwright-Finch, U., & Lavie, N. (2014). I can see clearly now: the effects of age and perceptual load on inattentional blindness. Frontiers in Human Neuroscience, 8(1), 229-240.

    PubMed Central  Google Scholar 

  53. Roper, Z. J., & Vecera, S. P. (2013). Response terminated displays unload selective attention. Frontiers in Psychology, 4, 967. doi:https://doi.org/10.3389/fpsyg.2013.00967

    Article  PubMed Central  Google Scholar 

  54. 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.

    Article  Google Scholar 

  55. Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56(5), 356-374.

    Article  Google Scholar 

  56. Scimeca, J. M., Kiyonaga, A., & D'Esposito, M. (2018). Reaffirming the sensory recruitment account of working memory. Trends in Cognitive Sciences, 22(3), 190-192. doi:https://doi.org/10.1016/j.tics.2017.12.007

    Article  Google Scholar 

  57. Shen, M., Huang, X., & Gao, Z. (2015). Object-Based Attention Underlies the Rehearsal of Feature Binding in Visual Working Memory. Journal of Experimental Psychology. Human Perception and Performance, 41(2), 479-493.

    Article  Google Scholar 

  58. Shulman, G. L., & Corbetta, M. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3(3), 201-215. doi:https://doi.org/10.1038/nrn755

    Article  Google Scholar 

  59. Sreenivasan, K. K., & Jha, A. P. (2007). Selective attention supports working memory maintenance by modulating perceptual processing of distractors. Journal of Cognitive Neuroscience, 19(1), 32-41. doi:https://doi.org/10.1162/jocn.2007.19.1.32

    Article  Google Scholar 

  60. Tsal, Y., & Benoni, H. (2010). Diluting the burden of load: perceptual load effects are simply dilution effects. Journal of Experimental Psychology. Human Perception and Performance, 36(6), 1645-1656. doi:https://doi.org/10.1037/a0018172

    Article  Google Scholar 

  61. Wheeler, M. E., & Treisman, A. M. (2002). Binding in short-term visual memory. Journal of Experimental Psychology General, 131(1), 48-64. doi:https://doi.org/10.1037//0096-3445.131.1.48

    Article  Google Scholar 

  62. Woodman, G. F., & Luck, S. J. (2004). Visual search is slowed when visuospatial working memory is occupied. Psychonomic Bulletin & Review, 11(2), 269-274.

    Article  Google Scholar 

  63. Woodman, G. F., Vogel, E. K., & Luck, S. J. (2001). Visual Search Remains Efficient When Visual Working Memory Is Full. Psychological Science, 12(3), 219-224.

    Article  Google Scholar 

  64. Xu, Y. (2017). Reevaluating the sensory account of visual working memory storage. Trends in Cognitive Science, 21(10), 794-815.

    Article  Google Scholar 

  65. Zhang, W., & Luck, S. J. (2008). Discrete fixed-resolution representations in visual working memory. Nature, 453(7192), 233-235.

    Article  Google Scholar 

  66. Zhang, W., & Luck, S. J. (2015). Opposite effects of capacity load and resolution load on distractor processing. Journal of Experimental Psychology. Human Perception and Performance, 41(1), 22–27. https://doi.org/10.1037/xhp0000013

    Article  Google Scholar 

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Acknowledgement

This research was supported by National Key R&D Program of China(2019YFB1600504)

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Correspondence to Mowei Shen or Zaifeng Gao.

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Yao, N., Guo, Y., Liu, Y. et al. Visual working-memory capacity load does not modulate distractor processing. Atten Percept Psychophys (2020). https://doi.org/10.3758/s13414-020-01991-7

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Keywords

  • Visual working memory
  • Selective attention
  • Distractor processing