Pupil size as a measure of within-task learning
Corresponding Author
Cyrus K. Foroughi
U. S. Naval Research Laboratory, Washington, District of Columbia, USA
Correspondence Cyrus K. Foroughi, U. S. Naval Research Laboratory (NRL), 4555 Overlook Ave SW, Washington, DC 20375, USA. Email: [email protected]Search for more papers by this authorCiara Sibley
U. S. Naval Research Laboratory, Washington, District of Columbia, USA
Search for more papers by this authorJoseph T. Coyne
U. S. Naval Research Laboratory, Washington, District of Columbia, USA
Search for more papers by this authorCorresponding Author
Cyrus K. Foroughi
U. S. Naval Research Laboratory, Washington, District of Columbia, USA
Correspondence Cyrus K. Foroughi, U. S. Naval Research Laboratory (NRL), 4555 Overlook Ave SW, Washington, DC 20375, USA. Email: [email protected]Search for more papers by this authorCiara Sibley
U. S. Naval Research Laboratory, Washington, District of Columbia, USA
Search for more papers by this authorJoseph T. Coyne
U. S. Naval Research Laboratory, Washington, District of Columbia, USA
Search for more papers by this authorAbstract
Pupillometry is commonly used in research to determine how much mental effort an individual is exerting while completing tasks. Traditionally, larger pupils are associated with increased mental effort when completing more difficult tasks. However, little research has investigated how pupils change as individuals learn a new task. In theory, as one repeatedly completes a task, the task demands should reduce, reliance on working memory should decrease, and the task should become more automatic. This should translate to faster completion times and smaller peak pupil dilations. We tested this hypothesis by having participants complete multiple trials of a cognitive task that requires individuals to orient themselves in space relative to a target. We found that trial completion times and maximum pupil size significantly reduced across trials. These data suggest that measuring changes in pupil dilation may help researchers determine whether individuals have shifted from a learned procedure to an automatic processing of information when learning a new task.
REFERENCES
- 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. doi:10.1146/annurev.neuro.28.061604.135709
- Aston-Jones, G., & Waterhouse, B. (2016). Locus coeruleus: From global projection system to adaptive regulation of behavior. Brain Research, 1645, 75–78. doi:10.1016/j.brainres.2016.03.001
- Bartlett, F. C. (1932). Remembering: An experimental and social study. Cambridge, UK: Cambridge University Press.
- Beatty, J. (1982). Task-evoked pupillary responses, processing load, and the structure of processing resources. Psychological Bulletin, 91(2), 276–292. doi:10.1037/0033-2909.91.2.276
-
Beatty, J., &
Kahneman, D. (1966). Pupillary changes in two memory tasks. Psychonomic Science, 5(10), 371–372. doi:10.3758/BF03328444
10.3758/BF03328444 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(1), 33–84. doi:10.1016/S0165-0173(03)00143-7
- Borchers, H. W. (2016). Package ‘pracma.’ R package version 1.9.5 [Computer software]. Retrieved from https://cran.r-project.org/web/packages/pracma/pracma.pdf
- Champely, S., Ekstrom, C., Dalgaard, P., Gill, J., Weibelzahl, S., Anandkumar, A., … Rosario, H. (2017). Package ‘pwr.’ R package version 1.2–1 [Computer software]. Retrieved from https://cran.r-project.org/web/packages/pwr/index.html
- Chen, S., & Epps, J. (2014). Using task-induced pupil diameter and blink rate to infer cognitive load. Human–Computer Interaction, 29(4), 390–413. doi:10.1080/07370024.2014.892428
- Corbetta, M., Patel, G., & Shulman, G. L. (2008). The reorienting system of the human brain: From environment to theory of mind. Neuron, 58(3), 306–324. doi:10.1016/j.neuron.2008.04.017
- Coull, J. T., Büchel, C., Friston, K. J., & Frith, C. D. (1999). Noradrenergically mediated plasticity in a human attentional neuronal network. NeuroImage, 10(6), 705–715. doi:10.1016/j.tics.2007.10.011
- Ericsson, K. A., & Kintsch, W. (1995). Long-term working memory. Psychological Review, 102(2), 211–245. doi:10.1037/0033-295X.102.2.211
- Friedman, H. (1968). Magnitude of experimental effect and a table for its rapid estimation. Psychological Bulletin, 70(4), 245–251. doi:10.1037/h0026258
- Hess, E. H., & Polt, J. M. (1964). Pupil size in relation to mental activity during simple problem-solving. Science, 143(3611), 1190–1192. doi:10.1126/science.143.3611.1190
- Koss, M. C. (1986). Pupillary dilation as an index of central nervous system α2-adrenoceptor activation. Journal of Pharmacological Methods, 15(1), 1–19. doi:10.1016/0160-5402(86)90002-1
- Laeng, B., Sirois, S., & Gredebäck, G. (2012). Pupillometry a window to the preconscious? Perspectives on Psychological Science, 7(1), 18–27. doi:10.1177/1745691611427305
- Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4, 863. doi:10.3389/fpsyg.2013.00863
- Loftus, G. R., & Masson, M. E. (1994). Using confidence intervals in within-subject designs. Psychonomic Bulletin & Review, 1(4), 476–490. doi:10.3758/BF03210951
-
Morey, R. D. (2008). Confidence intervals from normalized data: A correction to Cousineau (2005). Tutorial in Quantitative Methods for Psychology, 4(2), 61–64. doi:10.20982/tqmp.04.2.p061
10.20982/tqmp.04.2.p061 Google Scholar
- Murphy, P. R., O'Connell, R. G., O'Sullivan, M., Robertson, I. H., & Balsters, J. H. (2014). Pupil diameter covaries with BOLD activity in human locus coeruleus. Human Brain Mapping, 35(8), 4140–4154. doi:10.1002/hbm.22466
- Ostoin, S. D. (2007). An assessment of the performance-based measurement battery (PBMB), the Navy's psychomotor supplement to the Aviation Selection Test Battery (ASTB). Naval Postgraduate School. Monterey, CA.
- Paas, F., Tuovinen, J. E., Tabbers, H., & Van Gerven, P. W. (2003). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38(1), 63–71. doi:10.1207/S15326985EP3801_8
- Pearson, R. K., Neuvo, Y., Astola, J., & Gabbouj, M. (2016). Generalized hampel filters. EURASIP Journal on Advances in Signal Processing, 1, 87. doi:10.1186/s13634-016-0383-6
- Peysakhovich, V., Vachon, F., & Dehais, F. (2017). The impact of luminance on tonic and phasic pupillary responses to sustained cognitive load. International Journal of Psychophysiology, 112, 40–45. doi:10.1016/j.ijpsycho.2016.12.003
- R Development Core Team. (2014). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
- Rajkowski, J., Kubiak, P., & Aston-Jones, G. (1993). Correlations between locus coeruleus (LC) neural activity, pupil diameter and behavior in monkey support a role of LC in attention [Abstract]. Society for Neuroscience Abstracts, 19, 974.
- Richer, F., & Beatty, J. (1987). Contrasting effects of response uncertainty on the task-evoked pupillary response and reaction time. Psychophysiology, 24(3), 258–262. doi:10.1111/j.1469-8986.1987.tb00291.x
- Richstone, L., Schwartz, M. J., Seideman, C., Cadeddu, J., Marshall, S., & Kavoussi, L. R. (2010). Eye metrics as an objective assessment of surgical skill. Annals of Surgery, 252(1), 177–182. doi:10.1097/SLA.0b013e3181e464fb
- Robertson, E. M. (2007). The serial reaction time task: Implicit motor skill learning? Journal of Neuroscience, 27(38), 10073–10075. doi:10.1523/JNEUROSCI.2747-07.2007
-
Rosenthal, R. (1991). Meta-analytic procedures for social research. Newbury Park, CA: Sage Publications, Incorporated.
10.4135/9781412984997 Google Scholar
- Samuels, E. R., & Szabadi, E. (2008). Functional neuroanatomy of the noradrenergic locus coeruleus: Its roles in the regulation of arousal and autonomic function Part I: Principles of functional organisation. Current Neuropharmacology, 6(3), 235–253. doi:10.2174/157015908785777229
- Sara, S. J. (2009). The locus coeruleus and noradrenergic modulation of cognition. Nature Reviews Neuroscience, 10(3), 211–223. doi:10.1038/nrn2573
- Sibley, C., Cole, A., Gibson, G., Roberts, D., Barrow, J., Baldwin, C., & Coyne, J. (2010). Adaptive training in an unmanned aerial vehicle: Examination of several candidate real-time metrics. Naval Research Laboratory, Washington, DC.
-
Sibley, C.,
Coyne, J., &
Baldwin, C. (2011, September). Pupil dilation as an index of learning. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 55(1), 237–241. doi:10.1177/1071181311551049
10.1177/1071181311551049 Google Scholar
- Sibley, C., Foroughi, C. K., Olson, T., Moclaire, C., & Coyne, J. T. (in press). Paper to be presented at the 2017 Human-Computer Interaction International Conference, Vancouver, BC, Canada.
-
Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295–312. doi:10.1016/0959-4752(94)90003-5
10.1016/0959-4752(94)90003-5 Google Scholar
- Unsworth, N., & Engle, R. W. (2005). Individual differences in working memory capacity and learning: Evidence from the serial reaction time task. Memory & Cognition, 33(2), 213–220. doi:10.3758/BF03195310
- Zeileis, A., Grothendieck, G., Ryan, J. A., Andrews, F., & Zeileis, M. A. (2014). Package ‘zoo’. R package version 1.7–12 [Computer software]. Retrieved from http://CRAN.R-project.org/package= zoo