Variation in Pupil Diameter by Day and Time of Day

  • Shannon R. FlynnEmail author
  • Jacob S. Quartuccio
  • Ciara Sibley
  • Joseph T. Coyne
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10906)


Over 60 years of prior work has shown that an individual’s pupil diameter increases as the cognitive demands of a task increase. Recent work has also shown that resting pupil size is significantly correlated with an individual’s working memory capacity, suggesting that between subjects variation in pupil size is important. Given the importance of both within and between variations in pupil size, the present study sought to examine the reliability of pupil diameter measurements across multiple days. A longitudinal, within subjects design was used to study pupil diameter to determine if it is possible to find stable estimates of pupil diameter across several days and across time of day. This study collected pupil data using a low-cost Gazepoint GP3 HD desktop eye tracking system. Seven participants engaged in a resting luminance change task twice per day for a total of 10 days. The participants sat in a completely dark room for two minutes prior to the start of the experiment to allow their eyes to acclimate to the darkness. They then performed the resting luminance change task, as well as two other tasks omitted from analysis. This paper presents an analysis demonstrating that there are stable estimates of pupil diameter across days, as well as across time of day. These results suggest that pupil diameter is a reliable measure within individuals. The ability to reliably capture pupil diameter using low-cost eye trackers suggests that these new low cost systems may be incorporated into a broader range of cognitive research.


Eye tracking Pupil diameter Variability Gazepoint 


  1. 1.
    Hess, E.H., Polt, J.M.: Pupil size in relation to mental activity during simple problem-solving. Science 143(3611), 1190–1192 (1964)CrossRefGoogle Scholar
  2. 2.
    Kahneman, D., Beatty, J.: Pupil diameter and load on memory. Science 154, 1583–1585 (1966)CrossRefGoogle Scholar
  3. 3.
    Ahern, S., Beatty, J.: Pupillary responses during information processing vary with scholastic aptitude test scores. Science 205(21), 1289–1292 (1979)CrossRefGoogle Scholar
  4. 4.
    Tsukahara, J.S., Harrison, T.L., Engle, R.W.: The relationship between baseline pupil size and intelligence. Cogn. Psychol. 91, 109–123 (2016)CrossRefGoogle Scholar
  5. 5.
    Beatty, J., Lucero-Wagoner, B.: The pupillary system. In: Handbook of Psychophysiology, 2nd edn, pp. 142–162. Cambridge University Press, New York (2000)Google Scholar
  6. 6.
    Aston-Jones, G., Cohen, J.D.: An integrative theory of locus coeruleus- norepinephrine function: adaptive gain and optimal performance. Neuroscience 28, 403–450 (2005)Google Scholar
  7. 7.
    Luque-Casado, A., Zabala, M., Morales, E., Mateo-March, M., Sanabria, D.: Cognitive performance and heart rate variability: the influence of fitness level. PLoS ONE 8(2), 1–9 (2013)CrossRefGoogle Scholar
  8. 8.
    Tsunoda, K., Chiba, A., Yoshida, K., Watanabe, T., Mizuno, O.: Predicting changes in cognitive performance using heart rate variability. Inst. Electron. Inf. Commun. Eng. E100-D, 2411–2419 (2017)Google Scholar
  9. 9.
    Brown, S.M., Khanani, A.M., Xu, K.T.: Day to day variability of the dark-adapted pupil diameter. J. Cataract Refract. Surg. 30, 639–644 (2004)CrossRefGoogle Scholar
  10. 10.
    R Development Core Team: R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2014)Google Scholar
  11. 11.
    Foroughi, C.K., Coyne, J.T., Sibley, C., Olson, T., Moclaire, C., Brown, N.: Pupil dilation and task adaptation. In: Schmorrow, D.D., Fidopiastis, C.M. (eds.) AC 2017. LNCS (LNAI), vol. 10284, pp. 304–311. Springer, Cham (2017). Scholar
  12. 12.
    van Buuren, S., Groothuis-Oudshoorn, K.: MICE: multivariate imputation by chained equations in R. J. Stat. Softw. 45(3), 1–67 (2011)CrossRefGoogle Scholar
  13. 13.
    Wickham, H.: ggplot2: Elegant Graphics for Data Analysis. Springer, New York (2009). Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Shannon R. Flynn
    • 1
    Email author
  • Jacob S. Quartuccio
    • 2
  • Ciara Sibley
    • 3
  • Joseph T. Coyne
    • 3
  1. 1.University of New HampshireDurhamUSA
  2. 2.George Mason UniversityFairfaxUSA
  3. 3.Naval Research LaboratoryWashingtonUSA

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