Pupillometry, Attention Control, and Working Memory

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Modern Pupillometry
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Abstract

Historically, pupillometry has been leveraged as a tool to understand both working memory and attention control, two intricately related cognitive processes. In this chapter, I summarize some typical findings in paradigms examining working memory capacity, conflict resolution, cognitive control, and sustained attention. I also report several new analyses of previously published datasets showing how pupillometry can be used to understand both intra- and interindividual variability in attention control. These analyses revealed that (1) pupillary responses – both their magnitude and latency – reveal insights into the speed and effectiveness of attention processes and (2) both the dynamics of pretrial pupil diameter and the magnitude of stimulus-evoked pupillary responses correlate with individual differences in attention control. Finally, this chapter interprets these findings in light of locus coeruleus–norepinephrine (LC–NE) theories of attention control and working memory (Unsworth and Robison, Psychon Bull Rev 24:1282–1311, 2017a; Tsukahara and Engle, Proc Nat Acad Sci 118(46):e2110630118, 2021).

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Notes

  1. 1.

    Massar et al. (2016) reported changes in pupil diameter overall but did not specifically compare the magnitude of the pupillary responses after stimulus onsets.

  2. 2.

    Unfortunately, due to eye-tracker malfunction, valid pupil data were unavailable for the majority of participants in the antisaccade task, so we were only able to examine pupil data from the Stroop and PVT.

References

  • Adam, K. C. S., Mance, I., Fukuda, K., & Vogel, E. K. (2015). The contribution of attentional lapses to individual differences in visual working memory capacity. Journal of Cognitive Neuroscience, 27, 1601–1616.

    Article  PubMed  PubMed Central  Google Scholar 

  • Alnæs, D., Sneve, M. H., Espeseth, T., Endestad, T., van de Pavert, S. H., & Laeng, B. (2014). Pupil size signals mental effort deployed during multiple object tracking and predicts brain activity in the dorsal attention network and the locus coeruleus. Journal of Vision, 14, 1–20.

    Article  PubMed  Google Scholar 

  • Aminihajibashi, S., Hagen, T., Foldal, M. D., Laeng, B., & Espeseth, T. (2019). Individual differences in resting-state pupil size: Evidence for association between working memory capacity and pupil size variability. International Journal of Psychophysiology, 140, 1–7.

    Article  PubMed  Google Scholar 

  • Aminihajibashi, S., Hagen, T., Andreassen, O. A., Laeng, B., & Espeseth, T. (2020). The effects of cognitive abilities and task demands on tonic and phasic pupil sizes. Biological Psychology, 156, 107945.

    Article  PubMed  Google Scholar 

  • Andrews-Hanna, J. R., Smallwood, J., & Spreng, R. N. (2014). The default network and self-generated thought: Component processes, dynamic control, and clinical relevance. Annals of the New York Academy of Sciences, 1316, 29–52.

    Article  PubMed  PubMed Central  Google Scholar 

  • Aston-Jones, G., & Cohen, J. D. (2005). An integrative theory of locus coeruleus-norepinephrine function: Adaptive gain and optimal performance. Annual Reviews of Neuroscience, 28, 403–450.

    Article  Google Scholar 

  • Awh, E., & Jonides, J. (2001). Overlap** mechanisms of attention and spatial working memory. Trends in Cognitive Sciences, 5, 119–126.

    Article  PubMed  Google Scholar 

  • Basner, M., & Dinges, D. F. (2011). Maximizing sensitivity of the psychomotor vigilance test (PVT) to sleep loss. Sleep, 34, 581–591.

    Article  PubMed  PubMed Central  Google Scholar 

  • Berridge, C. W., & Waterhouse, B. D. (2003). The locus coeruleus–noradrenergic system: modulation of behavioral state and state-dependent cognitive processes. Brain Research Reviews, 42, 33–84.

    Article  PubMed  Google Scholar 

  • Binda, P., Pereverzeva, M., & Murray, S. O. (2013). Attention to bright surfaces enhances the pupillary light reflex. Journal of Neuroscience, 5, 2199–2204.

    Article  Google Scholar 

  • Binda, P., Pereverzeva, M., & Murray, S. O. (2014). Pupil size reflects the focus of feature-based attention. Journal of Neurophysiology, 12, 3046–3052.

    Article  Google Scholar 

  • Braver, T. S. (2012). The variable nature of cognitive control: A dual mechanisms framework. Trends in Cognitive Sciences, 16, 106–113.

    Article  PubMed  PubMed Central  Google Scholar 

  • Brown, G. G., Kindermann, S. S., Siegle, G. J., Granholm, E., Wong, E. C., & Buxton, R. B. (1999). Brain activation and pupil response during covert performance of the Stroop Color Word task. Journal of the International Neuropsychological Society, 5, 308–319.

    Article  PubMed  Google Scholar 

  • Chatham, C. H., Frank, M. J., & Munakata, Y. (2009). Pupillometric and behavioral markers of a developmental shift in the temporal dynamics of cognitive control. Proceedings of the National Academy of Sciences, 106(14), 5529–5533.

    Article  Google Scholar 

  • Chiew, K. S., & Braver, T. S. (2013). Temporal dynamics of motivation-cognitive control interactions revealed by high-resolution pupillometry. Frontiers in Psychology, 4, 15.

    Article  PubMed  PubMed Central  Google Scholar 

  • Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3, 215–229.

    Article  Google Scholar 

  • Dalmaso, M., Castelli, L., & Galfano, G. (2020). Microsaccadic rate and pupil size dynamics in pro−/anti-saccade preparation: The impact of intermixed vs. blocked trial administration. Psychological Research, 84, 1320–1332.

    Article  PubMed  Google Scholar 

  • Dinges, D. F., Orne, M. T., Whitehouse, W. G., & Orne, E. C. (1987). Temporal placement of a nap for alertness: Contributions of circadian phase and prior wakefulness. Sleep, 10, 313–329.

    PubMed  Google Scholar 

  • Drummond, S. P., Bischoff-Grethe, A., Dinges, D. F., Ayalon, L., Mednick, S. C., & Meloy, M. J. (2005). The neural basis of the psychomotor vigilance task. Sleep, 28, 1059–1068.

    PubMed  Google Scholar 

  • Eriksen, B. A., & Eriksen, C. W. (1974). Effects of noise letters upon the identification of a target letter in a non-search task. Perception & Psychophysics, 16, 143–149.

    Article  Google Scholar 

  • Engle, R. W., & Kane, M. J. (2004). Executive attention, working memory capacity, and a two-factor theory of cognitive control. In B. H. Ross (Ed.), The Psychology of Learning and Motivation, (Vol. 44), pp. 145–199. Elsevier.

    Google Scholar 

  • Friedman, D., Hakerem, G., Sutton, S., & Fleiss, J. L. (1973). Effect of stimulus uncertainty on the pupillary dilation response and the vertex evoked potential. Electroencephalography and Clinical Neurophysiology, 34, 475–484.

    Article  PubMed  Google Scholar 

  • Geva, R., Zivan, M., Warsha, A., & Olchik, D. (2013). Alerting, orienting or executive attention networks: Differential patterns of pupil dilations. Frontiers in Behavioral Neuroscience, 7, 145.

    Article  PubMed  PubMed Central  Google Scholar 

  • Gilzenrat, M. S., Nieuwenhuis, S., Jepma, M., & Cohen, J. D. (2010). Pupil diameter tracks changes in control state predicted by the adaptive gain theory of locus coeruleus function. Cognitive, Affective, & Behavioral Neuroscience, 10, 252–269.

    Article  Google Scholar 

  • Heitz, R. P., Schrock, J. C., Payne, T. W., & Engle, R. W. (2008). Effects of incentive on working memory capacity: Behavioral and pupillometric data. Psychophysiology, 45, 119–129.

    Article  PubMed  Google Scholar 

  • Hess, E. H., & Polt, J. M. (1964). Pupil size in relation to mental activity during simple problem-solving. Science, 143, 1190–1192.

    Article  PubMed  Google Scholar 

  • Hopstaken, J. F., Van Der Linden, D., Bakker, A. B., & Kompier, M. A. (2015a). A multifaceted investigation of the link between mental fatigue and task disengagement. Psychophysiology, 52, 305–315.

    Article  PubMed  Google Scholar 

  • Hopstaken, J. F., van der Linden, D., Bakker, A. B., & Kompier, M. A. (2015b). The window of my eyes: Task disengagement and mental fatigue covary with pupil dynamics. Biological Psychology, 110, 100–106.

    Article  PubMed  Google Scholar 

  • Hopstaken, J. F., van der Linden, D., Bakker, A. B., Kompier, M. A., & Leung, Y. K. (2016). Shifts in attention during mental fatigue: Evidence from subjective, behavioral, physiological, and eye-tracking data. Journal of Experimental Psychology: Human Perception and Performance, 42, 878–889.

    PubMed  Google Scholar 

  • Hutchison, K. A., Moffitt, C. C., Hart, K., Hood, A. V., Watson, J. M., & Marchak, F. M. (2020). Measuring task set preparation versus mind wandering using pupillometry. Journal of Experimental Psychology: Learning, Memory, and Cognition, 46, 280–295.

    PubMed  Google Scholar 

  • Jensen, A. R., & Rohwer, W. D., Jr. (1966). The Stroop color-word test: A review. Acta Psychologica, 25, 36–93.

    Article  PubMed  Google Scholar 

  • Kahneman, D., & Beatty, J. (1966). Pupil diameter and load on memory. Science, 154, 1583–1585.

    Article  PubMed  Google Scholar 

  • Kamp, S. M., & Donchin, E. (2015). ERP and pupil responses to deviance in an oddball paradigm. Psychophysiology, 52, 460–471.

    Article  PubMed  Google Scholar 

  • Kane, M. J., Bleckley, M. K., Conway, A. R., & Engle, R. W. (2001). A controlled-attention view of working-memory capacity. Journal of Experimental Psychology: General, 130, 169–183.

    Article  PubMed  Google Scholar 

  • Kiesel, A., Miller, J., Jolicœur, P., & Brisson, B. (2008). Measurement of ERP latency differences: A comparison of single-participant and jackknife-based scoring methods. Psychophysiology, 45, 250–274.

    Article  PubMed  Google Scholar 

  • Kuchinke, L., Võ, M. L. H., Hofmann, M., & Jacobs, A. M. (2007). Pupillary responses during lexical decisions vary with word frequency but not emotional valence. International Journal of Psychophysiology, 65, 132–140.

    Article  PubMed  Google Scholar 

  • Kurzban, R., Duckworth, A., Kable, J. W., & Myers, J. (2013). An opportunity cost model of subjective effort and task performance. Behavioral and Brain Sciences, 36, 661–679.

    Article  PubMed  Google Scholar 

  • Laeng, B., & Endestad, T. (2012). Bright illusions reduce the eye’s pupil. Proceedings of the National Academy of Sciences, 109, 2162–2167.

    Article  Google Scholar 

  • Laeng, B., Ørbo, M., Holmlund, T., & Miozzo, M. (2011). Pupillary stroop effects. Cognitive Processing, 12, 13–21.

    Article  PubMed  Google Scholar 

  • Langner, R., Kellermann, T., Eickhoff, S. B., Boers, F., Chatterjee, A., Willmes, K., & Sturm, W. (2012). Staying responsive to the world: Modality-specific and -nonspecific contributions to speeded auditory, tactile, and visual stimulus detection. Human Brain Map**, 33, 398–418.

    Article  PubMed  Google Scholar 

  • Lim, J., & Dinges, D. (2008). Sleep deprivation and vigilant attention. Annals of the New York Academy of Sciences, 1129, 305–322.

    Article  PubMed  Google Scholar 

  • Luck, S. J. (2014). An introduction to the event-related potential technique. MIT press.

    Google Scholar 

  • MacLeod, C. M. (1991). Half a century of research on the Stroop effect: An integrative review. Psychological Bulletin, 109, 163–203.

    Article  PubMed  Google Scholar 

  • Massar, S. A., Lim, J., Sasmita, K., & Chee, M. W. (2016). Rewards boost sustained attention through higher effort: A value-based decision making approach. Biological Psychology, 120, 21–27.

    Article  PubMed  Google Scholar 

  • Mathôt, S., Van der Linden, L., Grainger, J., & Vitu, F. (2013). The pupillary light response reveals the focus of covert visual attention. PLoS One, 8, e78168.

    Article  PubMed  PubMed Central  Google Scholar 

  • Meier, M. E., Smeekens, B. A., Silvia, P. J., Kwapil, T. R., & Kane, M. J. (2018). Working memory capacity and the antisaccade task: A microanalytic–macroanalytic investigation of individual differences in goal activation and maintenance. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44, 68–84.

    PubMed  Google Scholar 

  • Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: A network model of insula function. Brain Structure and Function, 214, 655–667.

    Article  PubMed  Google Scholar 

  • Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex functioning. Annual Review of Neuroscience, 24, 167–202.

    Article  PubMed  Google Scholar 

  • Murphy, P. R., Robertson, I. H., Balsters, J. H., & O’Connell, R. G. (2011). Pupillometry and P3 index the locus coeruleus–noradrenergic arousal function in humans. Psychophysiology, 48, 1532–1543.

    Article  PubMed  Google Scholar 

  • Peavler, W. S. (1974). Pupil size, information overload, and performance differences. Psychophysiology, 11, 559–566.

    Article  PubMed  Google Scholar 

  • Petersen, S. E., & Posner, M. I. (2012). The attention system of the human brain: 20 years after. Annual Review of Neuroscience, 35, 73–89.

    Article  PubMed  PubMed Central  Google Scholar 

  • Preuschoff, K., t Hart, B. M., & Einhauser, W. (2011). Pupil dilation signals surprise: Evidence for noradrenaline’s role in decision making. Frontiers in Neuroscience, 5, 115.

    Article  PubMed  PubMed Central  Google Scholar 

  • Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001). A default mode of brain function. Proceedings of the National Academy of Sciences, 98, 676–682.

    Article  Google Scholar 

  • Robison, M. K. (2018). Regulating mind-wandering and sustained attention with goal-setting, feedback, and incentives [Doctor Dissertation].

    Google Scholar 

  • Robison, M. K., & Brewer, G. A. (2020). Individual differences in working memory capacity and the regulation of arousal. Attention, Perception, & Psychophysics, 82, 3273–3290.

    Article  Google Scholar 

  • Robison, M. K., & Unsworth, N. (2019). Pupillometry tracts fluctuations in working memory performance. Attention, Perception, & Psychophysics, 81, 407–419.

    Article  Google Scholar 

  • Robison, M. K., Unsworth, N., & Brewer, G. A. (2020). Examining the effects of goal-setting, feedback, and incentives on sustained attention. Journal of Experimental Psychology: Human Perception and Performance, 47, 869.

    Google Scholar 

  • Rondeel, E., Van Steenbergen, H., Holland, R., & van Knippenberg, A. (2015). A closer look at cognitive control: Differences in resource allocation during updating, inhibition and switching as revealed by pupillometry. Frontiers in Human Neuroscience, 9, 494.

    Article  PubMed  PubMed Central  Google Scholar 

  • Sadaghiani, S., & D’Esposito, M. (2015). Functional characterization of the cingulo-opercular network in the maintenance of tonic alertness. Cerebral Cortex, 25, 2763–2773.

    Article  PubMed  Google Scholar 

  • Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., et al. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. Journal of Neuroscience, 27, 2349–2356.

    Article  PubMed  Google Scholar 

  • Siegle, G. J., Steinhauer, S. R., & Thase, M. E. (2004). Pupillary assessment and computational modeling of the Stroop task in depression. International Journal of Psychophysiology, 52, 63–76.

    Article  PubMed  Google Scholar 

  • Siegle, G. J., Ichikawa, N., & Steinhauer, S. (2008). Blink before and after you think: Blinks occur prior to and following cognitive load indexed by pupillary responses. Psychophysiology, 45, 679–687.

    Article  PubMed  Google Scholar 

  • Smit, A. S., Eling, P. A., & Coenen, A. M. (2004). Mental effort causes vigilance decrease due to resource depletion. Acta Psychologica, 115, 35–42.

    Article  PubMed  Google Scholar 

  • Spreng, R. N., Mar, R. A., & Kim, A. S. (2009). The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: A quantitative meta-analysis. Journal of Cognitive Neuroscience, 21, 489–510.

    Article  PubMed  Google Scholar 

  • Strauch, C., Koniakowsky, I., & Huckauf, A. (2020). Decision making and oddball effects on pupil size: Evidence for a sequential process. Journal of Cognition, 3, 7.

    Article  PubMed  PubMed Central  Google Scholar 

  • Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643–662.

    Article  Google Scholar 

  • Sturm, W., & Willmes, K. (2001). On the functional neuroanatomy of intrinsic and phasic alertness. NeuroImage, 14, S76–S84.

    Article  PubMed  Google Scholar 

  • Thomson, D. R., Besner, D., & Smilek, D. (2015). A resource-control account of sustained attention: Evidence from mind-wandering and vigilance paradigms. Perspectives on Psychological Science, 10, 82–96.

    Article  PubMed  Google Scholar 

  • Tsukahara, J. S., & Engle, R. W. (2020). The locus coeruleus-norepinephrine system and fluid intelligence. PsyAr**v.

    Book  Google Scholar 

  • Tsukahara, J. S., & Engle, R. W. (2021). Fluid intelligence and the locus coeruleus–norepinephrine system. Proceedings of the National Academy of Sciences, 118(46), e2110630118.

    Google Scholar 

  • Tsukahara, J. S., Harrison, T. L., & Engle, R. W. (2016). The relationship between baseline pupil size and intelligence. Cognitive Psychology, 91, 109–123.

    Article  PubMed  Google Scholar 

  • Unsworth, N., & McMillan, B. D. (2014). Similarities and differences between mind-wandering and external distraction: A latent variable analysis of lapses of attention and their relation to cognitive abilities. Acta Psychologica, 150, 14–25.

    Article  PubMed  Google Scholar 

  • Unsworth, N., & Robison, M. K. (2015). Individual differences in the allocation of attention to items in working memory: Evidence from pupillometry. Psychonomic Bulletin & Review, 22, 757–765.

    Article  Google Scholar 

  • Unsworth, N., & Robison, M. K. (2016). Pupillary correlates of lapses of sustained attention. Cognitive, Affective, & Behavioral Neuroscience, 16, 601–615.

    Article  Google Scholar 

  • Unsworth, N., & Robison, M. K. (2017a). A locus coeruleus-norepinephrine account of individual differences in working memory capacity and attention control. Psychonomic Bulletin & Review, 24, 1282–1311.

    Article  Google Scholar 

  • Unsworth, N., & Robison, M. K. (2017b). Pupillary correlates of covert shifts of attention during working memory maintenance. Attention, Perception, & Psychophysics, 79, 782–795.

    Article  Google Scholar 

  • Unsworth, N., & Robison, M. K. (2017c). The importance of arousal for variation in working memory capacity and attention control: A latent variable pupillometry study. Journal of Experimental Psychology: Learning, Memory, & Cognition, 43, 1962–1987.

    Google Scholar 

  • Unsworth, N., & Robison, M. K. (2018b). Tracking working memory maintenance with pupillometry. Attention, Perception, & Psychophysics, 80, 461–484.

    Article  Google Scholar 

  • Unsworth, N., & Robison, M. K. (2020). Working memory capacity and sustained attention: A cognitive-energetic perspective. Journal of Experimental Psychology: Learning, Memory, and Cognition, 46, 77–103.

    PubMed  Google Scholar 

  • Unsworth, N., & Spillers, G. J. (2010). Working memory capacity: Attention, memory, or both? A direct test of the dual-component model. Journal of Memory and Language, 62, 392–406.

    Article  Google Scholar 

  • Unsworth, N., Schrock, J. C., & Engle, R. W. (2004). Working memory capacity and the antisaccade task: Individual differences in voluntary saccade control. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30, 1302–1321.

    PubMed  Google Scholar 

  • Unsworth, N., Redick, T. S., Lakey, C. E., & Young, D. L. (2010). Lapses in sustained attention and their relation to executive control and fluid abilities: An individual differences investigation. Intelligence, 38, 111–122.

    Article  Google Scholar 

  • Unsworth, N., Robison, M. K., & Miller, A. L. (2018). Pupillary correlates of fluctuations in sustained attention. Journal of Cognitive Neuroscience, 30, 1241–1253.

    Article  PubMed  Google Scholar 

  • Unsworth, N., Miller, A. L., & Robison, M. K. (2020). Individual differences in lapses of sustained attention: Ocolumetric indicators of intrinsic alertness. Journal of Experimental Psychology: Human Perception and Performance, 46, 569–592.

    PubMed  Google Scholar 

  • Unsworth, M., Miller, A. L., & Robison, M. K. (2019). Is working memory capacity related to baseline pupil diameter? Psychonomic Bulletin & Review, 28, 228–237.

    Google Scholar 

  • van Bochove, M. E., Van der Haegen, L., Notebaert, W., & Verguts, T. (2013). Blinking predicts enhanced cognitive control. Cognitive, Affective, & Behavioral Neuroscience, 13, 346–354.

    Article  Google Scholar 

  • van Zomeren, A. H., & Brouwer, W. H. (1994). Clinical neuropsychology of attention. Oxford Press.

    Google Scholar 

  • Vincent, J. L., Kahn, I., Snyder, A. Z., Raichle, M. E., & Buckner, R. L. (2008). Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. Journal of Neurophysiology, 100, 3328–3342.

    Article  PubMed  PubMed Central  Google Scholar 

  • Vogel, E. K., McCollough, A. W., & Machizawa, M. G. (2005). Neural measures reveal individual differences in controlling access to working memory. Nature, 438, 500–503.

    Article  PubMed  Google Scholar 

  • Wahn, B., Ferris, D. P., Hairston, W. D., & König, P. (2016). Pupil sizes scale with attentional load and task experience in a multiple object tracking task. PLoS One, 11, e0168087.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wang, C. A., Brien, D. C., & Munoz, D. P. (2015). Pupil size reveals preparatory processes in the generation of pro-saccades and anti-saccades. European Journal of Neuroscience, 41, 1102–1110.

    Article  PubMed  Google Scholar 

  • Warm, J. S., Parasuraman, R., & Matthews, G. (2008). Vigilance requires hard mental work and is stressful. Human Factors, 50, 433–441.

    Article  PubMed  Google Scholar 

  • Wendt, M., Kiesel, A., Geringswald, F., Purmann, S., & Fischer, R. (2014). Attentional adjustment to conflict strength. Experimental Psychology, 61, 55–67.

    Article  PubMed  Google Scholar 

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Robison, M. (2024). Pupillometry, Attention Control, and Working Memory. In: Papesh, M.H., Goldinger, S.D. (eds) Modern Pupillometry. Springer, Cham. https://doi.org/10.1007/978-3-031-54896-3_4

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