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Putting effort into task complexity

Published online by Cambridge University Press:  26 November 2025

Damian Koevoet  and
Stefan Van der Stigchel Open the ORCID record for Stefan Van der Stigchel [Opens in a new window]
Damian Koevoet*
Affiliation:
Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, Netherlands d.koevoet@uu.nl s.vanderstigchel@uu.nl
Stefan Van der Stigchel*
Affiliation:
Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, Netherlands d.koevoet@uu.nl s.vanderstigchel@uu.nl
*
*Corresponding author.
*Corresponding author.
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Abstract

Understanding the limits of visual processing is at the core of understanding visual attention. Rosenholtz proposes task complexity as a potential solution to identify a putative unifying capacity limit. We argue that if task complexity is indeed used to identify a unifying limit, effort must crucially be incorporated to prevent a future crisis in the field of visual attention.

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Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 48 , 2025 , e145
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Copyright
© The Author(s), 2025. Published by Cambridge University Press

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References

Ahern, S., & Beatty, J. (1979). Pupillary responses during information processing vary with scholastic aptitude test scores. Science, 205(4412), 1289–1292. https://doi.org/10.1126/science.472746 CrossRefGoogle ScholarPubMed
Ballard, D. H., Hayhoe, M. M., & Pelz, J. B. (1995). Memory representations in natural tasks. Journal of Cognitive Neuroscience, 7(1), 66–80. https://doi.org/10.1162/jocn.1995.7.1.66 CrossRefGoogle ScholarPubMed
Beatty, J. (1982). Task-evoked pupillary responses, processing load, and the structure of processing resources. Psychological Bulletin, 91(2), 276–292. https://doi.org/10.1037/0033-2909.91.2.276 CrossRefGoogle ScholarPubMed
Böing, S., Ten Brink, A. F., Hoogerbrugge, A. J., Oudman, E., Postma, A., Nijboer, T. C. W., & Van der Stigchel, S. (2023). Eye movements as proxy for visual working memory usage: Increased reliance on the external world in Korsakoff syndrome. Journal of Clinical Medicine, 12(11), Article 11. https://doi.org/10.3390/jcm12113630 CrossRefGoogle ScholarPubMed
Bumke, O. (1911). Die pupillenstörungen bei geistes-und nervenkrankheiten (2nd ed.). Fischer.Google Scholar
Draschkow, D., Kallmayer, M., & Nobre, A. C. (2021). When natural behavior engages working memory. Current Biology, 31(4), 869–874.e5. https://doi.org/10.1016/j.cub.2020.11.013 CrossRefGoogle ScholarPubMed
Hoogerbrugge, A. J., Strauch, C., Nijboer, T. C. W., & Van der Stigchel, S. (2023). Don’t hide the instruction manual: A dynamic trade-off between using internal and external templates during visual search. Journal of Vision, 23(7), 14. https://doi.org/10.1167/jov.23.7.14 CrossRefGoogle Scholar
Hoppe, D., & Rothkopf, C. A. (2016). Learning rational temporal eye movement strategies. Proceedings of the National Academy of Sciences, 113(29), 8332–8337. https://doi.org/10.1073/pnas.1601305113 CrossRefGoogle ScholarPubMed
Kadner, F., Thomas, T., Hoppe, D., & Rothkopf, C. A. (2022). Improving saliency models’ predictions of the next fixation with humans’ intrinsic cost of gaze shifts. arXiv:2207.04250.Google Scholar
Kahneman, D. (1973). Attention and effort. Prentice-Hall.Google Scholar
Koevoet, D., Naber, M., Strauch, C., Somai, R. S., & Van der Stigchel, S. (2023). Differential aspects of attention predict the depth of visual working memory encoding: Evidence from pupillometry. Journal of Vision, 23(6), 9. https://doi.org/10.1167/jov.23.6.9 CrossRefGoogle ScholarPubMed
Koevoet, D., Naber, M., Strauch, C., & Van der Stigchel, S. (2024). The intensity of internal and external attention assessed with pupillometry. Journal of Cognition, 7(1), Article 1. https://doi.org/10.5334/joc.336 CrossRefGoogle ScholarPubMed
Koevoet, D., Strauch, C., Naber, M., & Van der Stigchel, S. (2023). The costs of paying overt and covert attention assessed with pupillometry. Psychological Science, 34(8), 887–898. https://doi.org/10.1177/09567976231179378 CrossRefGoogle ScholarPubMed
Koevoet, D., Strauch, C., Van der Stigchel, S., Mathôt, S., & Naber, M. (2024). Revealing visual working memory operations with pupillometry: Encoding, maintenance, and prioritization. WIREs Cognitive Science, 15(2), e1668. https://doi.org/10.1002/wcs.1668 CrossRefGoogle ScholarPubMed
Koevoet, D., Van Zantwijk, L., Naber, M., Mathôt, S., Van der Stigchel, S., & Strauch, C. (2024). Effort drives saccade selection. eLife, 13, 1–25. https://doi.org/10.7554/eLife.97760.1 Google Scholar
Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390(6657), Article 6657. https://doi.org/10.1038/36846 CrossRefGoogle ScholarPubMed
Master, S. L., Li, S., & Curtis, C. E. (2024). Trying harder: How cognitive effort sculpts neural representations during working memory. Journal of Neuroscience, 44(28), 1–12. https://doi.org/10.1523/JNEUROSCI.0060-24.2024 CrossRefGoogle ScholarPubMed
Robison, M. K., & Brewer, G. A. (2020). Individual differences in working memory capacity and the regulation of arousal. Attention, Perception, & Psychophysics, 82(7), 3273–3290. https://doi.org/10.3758/s13414-020-02077-0 CrossRefGoogle ScholarPubMed
Robison, M. K., Ralph, K. J., Gondoli, D. M., Torres, A., Campbell, S., Brewer, G. A., & Gibson, B. S. (2023). Testing locus coeruleus-norepinephrine accounts of working memory, attention control, and fluid intelligence. Cognitive, Affective, & Behavioral Neuroscience, 23(4), 1014–1058. https://doi.org/10.3758/s13415-023-01096-2 CrossRefGoogle ScholarPubMed
Robison, M. K., & Unsworth, N. (2019). Pupillometry tracks fluctuations in working memory performance. Attention, Perception, & Psychophysics, 81(2), 407–419. https://doi.org/10.3758/s13414-018-1618-4 CrossRefGoogle Scholar
Sahakian, A., Gayet, S., Paffen, C. L. E., & Van der Stigchel, S. (2023). Mountains of memory in a sea of uncertainty: Sampling the external world despite useful information in visual working memory. Cognition, 234, 105381. https://doi.org/10.1016/j.cognition.2023.105381 CrossRefGoogle Scholar
Shenhav, A., Musslick, S., Lieder, F., Kool, W., Griffiths, T. L., Cohen, J. D., & Botvinick, M. M. (2017). Toward a rational and mechanistic account of mental effort. Annual Review of Neuroscience, 40, 99–124. https://doi.org/10.1146/annurev-neuro-072116-031526 CrossRefGoogle Scholar
Somai, R. S., Schut, M. J., & Van der Stigchel, S. (2020). Evidence for the world as an external memory: A trade-off between internal and external visual memory storage. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior, 122, 108–114. https://doi.org/10.1016/j.cortex.2018.12.017 CrossRefGoogle Scholar
Strauch, C., Wang, C.-A., Einhäuser, W., Van der Stigchel, S., & Naber, M. (2022). Pupillometry as an integrated readout of distinct attentional networks. Trends in Neurosciences, 45(8), 635–647. https://doi.org/10.1016/j.tins.2022.05.003 CrossRefGoogle Scholar
Thomas, T., Hoppe, D., & Rothkopf, C. A. (2022). The neuroeconomics of individual differences in saccadic decisions (p. 2022.06.03.494508). bioRxiv. https://doi.org/10.1101/2022.06.03.494508 CrossRefGoogle Scholar
Unsworth, N., & Miller, A. L. (2021). Individual differences in the intensity and consistency of attention. Current Directions in Psychological Science, 30(5), 391–400. https://doi.org/10.1177/09637214211030266 CrossRefGoogle Scholar
Unsworth, N., & Robison, M. K. (2017). The importance of arousal for variation in working memory capacity and attention control: A latent variable pupillometry study. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(12), 1962–1987. https://doi.org/10.1037/xlm0000421 Google ScholarPubMed
Van der Stigchel, S. (2020). An embodied account of visual working memory. Visual Cognition, 28(5–8), 414–419. https://doi.org/10.1080/13506285.2020.1742827 CrossRefGoogle Scholar
van der Wel, P., & van Steenbergen, H. (2018). Pupil dilation as an index of effort in cognitive control tasks: A review. Psychonomic Bulletin & Review, 25(6), 2005–2015. https://doi.org/10.3758/s13423-018-1432-y CrossRefGoogle Scholar
Westbrook, A., & Braver, T. S. (2015). Cognitive effort: A neuroeconomic approach. Cognitive, Affective, & Behavioral Neuroscience, 15(2), 395–415. https://doi.org/10.3758/s13415-015-0334-y CrossRefGoogle ScholarPubMed