Advertisement

Cognitive, Affective, & Behavioral Neuroscience

, Volume 18, Issue 6, pp 1105–1120 | Cite as

A daytime nap enhances visual working memory performance and alters event-related delay activity

  • Kevin J. MacDonald
  • Holly A. Lockhart
  • Alex C. Storace
  • Stephen M. Emrich
  • Kimberly A. Cote
Article

Abstract

Working memory (WM) is impaired following sleep loss and may be improved after a nap. The goal of the current study was to better understand sleep-related WM enhancement by: (1) employing a WM task that assesses the ability to hold and report visual representations as well as the fidelity of the reports on a fine scale, (2) investigating neurophysiological properties of sleep and WM capacity as potential predictors or moderators of sleep-related enhancement, and (3) exploring frontal and occipital event-related delay activity to index the neural processing of stimuli in WM. In a within-subjects design, 36 young adults (Mage = 20, 20 men, 16 women) completed a 300-trial, continuous-report task of visual WM following a 90-min nap opportunity and an equivalent period of wakefulness. Mixed-effect models were used to estimate the odds of successful WM reports and the fidelity of those reports. The odds of a successful report were approximately equal between nap and wake conditions for the start of the task, but by the end, the odds of success were 1.26 times greater in the nap condition. Successful WM reports were more accurate after a nap, independent of the time on task. Neither WM capacity nor any of the sleep variables measured were found to significantly moderate the nap effect on WM. Lastly, napping resulted in amplitude changes for frontal and occipital delay activity relative to the wake condition. The findings are discussed in relation to contemporary models of visual WM and the role of sleep in sustained attention.

Keywords

Sleep Napping Working memory Attention 

Notes

Acknowledgements

The data were collected in the Brock University Sleep Research Laboratory, which is funded by the Natural Science and Engineering Research Council (NSERC) of Canada. The authors wish to thank the editors and reviewers for their time in consideration of this manuscript.

References

  1. Adam, K. C., 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(8), 1601-1616.  https://doi.org/10.1162/jocn_a_00811 CrossRefGoogle Scholar
  2. Angel, J., Cortez, J., Juarez, D., Guerrero, M., Garcia, A., Ramirez, C., & Valdez, P. (2015). Effects of sleep reduction on the phonological and visuospatial components of working memory. Sleep Science, 8(1), 68-73.  https://doi.org/10.1016/j.slsci.2015.06.001 CrossRefGoogle Scholar
  3. Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390-412.  https://doi.org/10.1016/j.jml.2007.12.005 CrossRefGoogle Scholar
  4. Baddeley, A. (2000). The episodic buffer: a new component of working memory?. Trends in Cognitive Sciences, 4(11), 417-423.  https://doi.org/10.1016/S1364-6613(00)01538-2 CrossRefGoogle Scholar
  5. Baddeley, A., & Hitch, G. (1974). Working memory. Psychology of Learning and Motivation, 8(1), 47-89.  https://doi.org/10.1016/S0079-7421(08)60452-1 CrossRefGoogle Scholar
  6. Bae, G. Y., Olkkonen, M., Allred, S. R., & Flombaum, J. I. (2015). Why some colors appear more memorable than others: A model combining categories and particulars in color working memory. Journal of Experimental Psychology: General, 144(4), 744.  https://doi.org/10.1037/xge0000076 CrossRefGoogle Scholar
  7. Barr, D. J., Levy, R., Scheepers, C., & Tily, H. J. (2013). Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 68(3), 255-278.  https://doi.org/10.1016/j.jml.2012.11.001 CrossRefGoogle Scholar
  8. Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1).  https://doi.org/10.18637/jss.v067.i01
  9. Bays, P. M. (2014). Noise in neural populations accounts for errors in working memory. Journal of Neuroscience, 34(10), 3632–3645.  https://doi.org/10.1523/JNEUROSCI.3204-13.2014 CrossRefGoogle Scholar
  10. Bays, P. M., Catalao, R. F. G., & Husain, M. (2009). The precision of visual working memory is set by allocation of a shared resource. Journal of Vision, 9(10), 7–7.  https://doi.org/10.1167/9.10.7 CrossRefGoogle Scholar
  11. Bays, P. M., & Husain, M. (2008). Dynamic shifts of limited working memory resources in human vision. Science, 321, 851–854.  https://doi.org/10.1126/science.1158023 CrossRefGoogle Scholar
  12. Bódizs, R., Tamas, K., Dandor, A., Havran, L., Rigo, P., Clemens, Z., & Halasz, P. (2005). Prediction of general mental ability based on neural oscillation measures of sleep. Journal of Sleep Research, 14(1), 285-292.  https://doi.org/10.1111/j.1365-2869.2005.00472.x CrossRefGoogle Scholar
  13. Chee, M. W., & Choo, W. C. (2004). Functional imaging of working memory after 24 hr of total sleep deprivation. Journal of Neuroscience, 24(19), 4560-4567.  https://doi.org/10.1523/JNEUROSCI.0007-04.2004 CrossRefGoogle Scholar
  14. Choo, W. C., Lee, W. W., Venkatraman, V., Sheu, F. S., & Chee, M. W. (2005). Dissociation of cortical regions modulated by both working memory load and sleep deprivation and by sleep deprivation alone. Neuroimage, 25(2), 579–587.  https://doi.org/10.1016/j.neuroimage.2004.11.029 CrossRefGoogle Scholar
  15. Clemens, Z., Fabo, D., & Halasz, P. (2005). Overnight verbal memory retention correlates with the number of sleep spindles. Journal of Neuroscience, 132, 529-535.  https://doi.org/10.1016/j.neuroscience.2005.01.011 CrossRefGoogle Scholar
  16. Cote, K. A., Epps, T., & Campbell, K. B. (2000). The role of the spindle in human information processing of high-intensity stimuli during sleep. Journal of Sleep Research, 9(1), 19-26.  https://doi.org/10.1046/j.1365-2869.2000.00188.x CrossRefGoogle Scholar
  17. Cowan, N. (2010). The magical mystery four: How is working memory capacity limited, and why?. Current Directions in Psychological Science, 19(1), 51-57.  https://doi.org/10.1177/0963721409359277 CrossRefGoogle Scholar
  18. Dang-Vu, T. T., McKinney, S. M., Buxton, O. M., Solet, J. M., & Ellenbogen, J. M. (2010). Spontaneous brain rhythms predict sleep stability in the face of noise. Current Biology, 20(15), R626-R627.  https://doi.org/10.1016/j.cub.2010.06.032 CrossRefGoogle Scholar
  19. Dijk, D. J., Beersma, D. G., & Bloem, G. M. (1989). Sex differences in the sleep EEG of young adults: visual scoring and spectral analysis. Sleep, 12(6), 500-507.  https://doi.org/10.1093/sleep/12.6.500 CrossRefGoogle Scholar
  20. Dijk, D. J., Brunner, D. P., Beersma, D. G., & Borbély, A. A. (1990). Electroencephalogram power density and slow wave sleep as a function of prior waking and circadian phase. Sleep, 13(5), 430-440.  https://doi.org/10.1093/sleep/13.5.430 CrossRefGoogle Scholar
  21. Drummond, S., Anderson, D., Straus, L., Vogel, E., & Perez, V. (2012). The effects of two types of sleep deprivation on visual working memory capacity and filtering efficiency. PLoS One, 7(4), 35653-35661.  https://doi.org/10.1371/journal.pone.0035653 CrossRefGoogle Scholar
  22. Dube, B., Emrich, S. M., & Al-Aidroos, N. (2017). More than a filter: Feature based attention regulates the distribution of visual working memory resources. Journal of Experimental Psychology: Human Perception and Performance, 43(10), 1843–1854.  https://doi.org/10.1037/xhp0000428 Google Scholar
  23. Durmer, J. S., & Dinges, D. F. (2005). Neurocognitive consequences of sleep deprivation. Seminars in Neurology, 25(1), 117-129.  https://doi.org/10.1055/s-2005-867080 CrossRefGoogle Scholar
  24. Edin, F., Klingberg, T., Johansson, P., McNab, F., Tegnér, J., & Compte, A. (2009). Mechanism for top-down control of working memory capacity. Proceedings of the National Academy of Sciences, 106(16), 6802-6807.  https://doi.org/10.1073/pnas.0901894106 CrossRefGoogle Scholar
  25. Emrich, S. M., & Busseri, M. A. (2015). Re-evaluating the relationships among filtering activity, unnecessary storage, and visual working memory capacity. Cognitive, Affective, & Behavioral Neuroscience, 15(3), 589-597.  https://doi.org/10.3758/s13415-015-0341-z CrossRefGoogle Scholar
  26. Emrich, S. M., Lockhart, H. A., & Al-Aidroos, N. (2017). Attention mediates the flexible allocation of visual working memory resources. Journal of Experimental Psychology: Human Perception and Performance, 43(7), 1454–1465.  https://doi.org/10.1037/xhp0000398 Google Scholar
  27. Emrich, S. M., Riggall, A. C., LaRocque, J. J., & Postle, B. R. (2013). Distributed patterns of activity in sensory cortex reflect the precision of multiple items maintained in visual short-term memory. Journal of Neuroscience, 33(15), 6516–6523.  https://doi.org/10.1523/JNEUROSCI.5732-12.2013 CrossRefGoogle Scholar
  28. Engle, R., Tulhoski, S., Laughlin, J., & Conway, A. (1999). Working memory, short-term memory, and general fluid intelligence: A latent variable approach. Journal of Experimental Psychology, 128(1), 309-331.  https://doi.org/10.1037/0096-3445.128.3.309 CrossRefGoogle Scholar
  29. Engle, R. W., & Kane, M. J. (2004). Executive attention, working memory capacity, and a two-factor theory of cognitive control. Psychology of Learning and Motivation, 44, 145-200.  https://doi.org/10.1016/S0079-7421(03)44005-X CrossRefGoogle Scholar
  30. Fang, Z., Sergeeva, V., Ray, L. B., Viczko, J., Owen, A. M., & Fogel, S. M. (2017). Sleep spindles and intellectual ability: Epiphenomenon or directly related?. Journal of Cognitive Neuroscience, 29(1), 167-182.  https://doi.org/10.1162/jocn_a_01034 CrossRefGoogle Scholar
  31. Finelli, L. A., Borbély, A. A., & Achermann, P. (2001). Functional topography of the human nonREM sleep electroencephalogram. European Journal of Neuroscience, 13(12), 2282-2290.  https://doi.org/10.1046/j.0953-816x.2001.01597.x CrossRefGoogle Scholar
  32. Fogel, S., Nader, R., Cote, K., & Smith, C. (2007). Sleep spindles and learning potential. Behavioural Neuroscience, 121(1), 1-10.  https://doi.org/10.1037/0735-7044.121.1.1 CrossRefGoogle Scholar
  33. Fox, J., & Weisberg, S. (2011). An R companion to applied regression (2nd). Thousand Oaks: Sage Publications.Google Scholar
  34. Frenda, S. J., & Fenn, K. M. (2016). Sleep less, think worse: The effect of sleep deprivation on working memory. Journal of Applied Research in Memory and Cognition, 5(4), 463-469.  https://doi.org/10.1016/j.jarmac.2016.10.001 CrossRefGoogle Scholar
  35. Harrison, S. A., & Tong, F. (2009). Decoding reveals the contents of visual working memory in early visual areas. Nature, 458(7238), 632–635.  https://doi.org/10.1038/nature07832 CrossRefGoogle Scholar
  36. Ilkowska, M., & Engle, R. W. (2010). Trait and state differences in working memory capacity. In Handbook of individual differences in cognition (pp. 295-320). Springer, New York.  https://doi.org/10.1007/978-1-4419-1210-7_18
  37. Ishihara, S. (2014). Ishihara’s tests for colour deficiency (Concise). Tokyo: Kanehara Trading Inc.Google Scholar
  38. Jiang, F., VanDyke, R., Zhang, J., Li, F., Gozal, D., & Shen, X. (2011). Effect of chronic sleep restriction on sleepiness and working memory in adolescents and young adults. Journal of Clinical and Experimental Neuropsychology, 33(8), 892-900.  https://doi.org/10.1080/13803395.2011.570252 CrossRefGoogle Scholar
  39. Jolicœur, P., Brisson, B., & Robitaille, N. (2008). Dissociation of the N2pc and sustained posterior contralateral negativity in a choice response task. Brain Research, 1215, 160–172.  https://doi.org/10.1016/j.brainres.2008.03.059 CrossRefGoogle Scholar
  40. Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2015). lmerTest: tests in linear mixed effects models. R package version 2.0-20. Vienna: R Foundation for Statistical Computing.Google Scholar
  41. Lau, E. Y. Y., Wong, M. L., Lau, K. N. T., Hui, F. W. Y., & Tseng, C. (2015). Rapid-eye-movement-sleep (REM) associated with enhancement of working memory performance after a daytime nap. PLoS ONE, 10(5), 1-16.  https://doi.org/10.1371/journal.pone.0125752 Google Scholar
  42. Liesefeld, A. M., Liesefeld, H. R., & Zimmer, H. D. (2014). Intercommunication between prefrontal and posterior brain regions for protecting visual working memory from distractor interference. Psychological Science, 25(2), 325–333.  https://doi.org/10.1177/0956797613501170 CrossRefGoogle Scholar
  43. Lim, J., & Dinges, D. F. (2008). Sleep deprivation and vigilant attention. Annals of the New York Academy of Sciences, 1129(1), 305-322.  https://doi.org/10.1196/annals.1417.002 CrossRefGoogle Scholar
  44. Lim, J., & Dinges, D. F. (2010). A meta-analysis of the impact of short-term sleep deprivation on cognitive variables. Psychological Bulletin, 136(3), 375-389.  https://doi.org/10.1037/a0018883 CrossRefGoogle Scholar
  45. Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390(6657), 279–281.  https://doi.org/10.1038/36846 CrossRefGoogle Scholar
  46. Lund, H. G., Reider, B. D., Whiting, A. B., & Prichard, J. R. (2010). Sleep patterns and predictors of disturbed sleep in a large population of college students. Journal of Adolescent Health, 46(2), 124-132.  https://doi.org/10.1016/j.jadohealth.2009.06.016 CrossRefGoogle Scholar
  47. Lustenberger, C., Maric, A., Dürr, R., Achermann, P., & Huber, R. (2012). Triangular relationship between sleep spindle activity, general cognitive ability and the efficiency of declarative learning. PLoS One, 7(11), e49561.  https://doi.org/10.1371/journal.pone.0049561 CrossRefGoogle Scholar
  48. Mednick, S. C., McDevitt, E. A., Walsh, J. K., Wamsley, E., Paulus, M., Kanady, J. C., & Drummond, S. P. (2013). The critical role of sleep spindles in hippocampal-dependent memory: a pharmacology study. Journal of Neuroscience, 33(10), 4494-4504.  https://doi.org/10.1523/JNEUROSCI.3127-12.2013 CrossRefGoogle Scholar
  49. Owens, M., Stevenson, J., Hadwin, J. A. & Norgate, R. (2014). When does anxiety help or hinder cognitive test performance? The role of working memory capacity. British Journal of Psychology, 105(1), 92–101.  https://doi.org/10.1111/bjop.12009 CrossRefGoogle Scholar
  50. Pashler, H. (1988). Familiarity and visual change detection. Attention, Perception, & Psychophysics, 44(4), 369–378.  https://doi.org/10.3758/BF03210419 CrossRefGoogle Scholar
  51. Pivik, R. T., Broughton, R. J., Coppola, R., Davidson, R. J., Fox, N., & Nuwer, M. R. (1993). Guidelines for the recording and quantitative analysis of electroencephalographic activity in research contexts. Psychophysiology, 30(6), 547-558.  https://doi.org/10.1111/j.1469-8986.1993.tb02081.x CrossRefGoogle Scholar
  52. Quigley, N., Green, J. F., Morgan, D., Idzikowski, C., & King, D. J.(2000). The effect of sleep deprivation on memory and psychomotor function in healthy volunteers. Human Psychopharmacology, 15(3),171–177.  https://doi.org/10.1002/(SICI)1099-1077(200004)15:3<171::AID-HUP155>3.0.CO;2-D CrossRefGoogle Scholar
  53. Raven, J., Raven, J. C., & Court, J. H. (1998). Manual for Raven’s progressive matrices and vocabulary scales. section 3: Standard progressive matrices. San Antonio: Harcourt.Google Scholar
  54. Rechtschaffen, A., & Kales, A. (1968). Manual of standardized terminology, techniques and scoring system for sleep stages of human subjects. Los Angeles: UCLA Brain Information Service/Brain Research Institute.Google Scholar
  55. Ruchkin, D. S., Johnson Jr, R., Canoune, H., & Ritter, W. (1990). Short-term memory storage and retention: An event-related brain potential study. Electroencephalography and Clinical Neurophysiology, 76(5), 419-439.  https://doi.org/10.1016/0013-4694(90)90096-3 CrossRefGoogle Scholar
  56. Satterthwaite, F. E. (1946). An approximate distribution of estimates of variance components. Biometrics Bulletin, 2(6), 110-114.  https://doi.org/10.2307/3002019 CrossRefGoogle Scholar
  57. Schabus, M., Gruber, M., Parapatics, S., Sauter, C., Klosch, G., Anderer, P., Klimesch, W., Bernd, S., & Zeitlhofer, J. (2004). Sleep spindles and their significance for declarative memory consolidation. Sleep Physiology, 27(8), 1479-1484.  https://doi.org/10.1093/sleep/27.7.1479 CrossRefGoogle Scholar
  58. Schabus, M., Holdmoser, K., Gruber, G., Sauter, C., Anderer, P., Klosch, G., Parapatics, S., Saletu, B., Klimesch, W., & Zeitlhofer, J. (2006). Sleep spindle-related activity in the human EEG and its relation to general cognitive and learning abilities. European Journal of Neuroscience, 23, 1738-1746.  https://doi.org/10.1111/j.1460-9568.2006.04694.x CrossRefGoogle Scholar
  59. Tempesta, D., De’Gennaro, L., Presaghi, F., & Ferrara, M. (2014). Emotional working memory during sustained wakefulness. Journal of Sleep Research, 23(1), 646-656.  https://doi.org/10.1111/jsr.12170 CrossRefGoogle Scholar
  60. Van Dongen, H., Maislin, G., Mullington, J. M., & Dinges, D. F. (2003). The cumulative cost of additional wakefulness: dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep, 26(2), 117-126.  https://doi.org/10.1093/sleep/26.2.117
  61. Van Dongen, H. P. A., Belenky, G., & Krueger, J. M. (2011). A local, bottom-up perspective on sleep deprivation and neurobehavioral performance. Current Topics in Medicinal Chemistry, 11(19), 2414-2422.  https://doi.org/10.2174/156802611797470286 CrossRefGoogle Scholar
  62. Vogel, E. K., & Machizawa, M. G. (2004). Neural activity predicts individual differences in visual working memory capacity. Nature, 428(6984), 748–751.  https://doi.org/10.1038/nature02447 CrossRefGoogle Scholar
  63. Vyazovskiy, V. V., Olcese, U., Hanlon, E. C., Nir, Y., Cirelli, C., Tononi, G. (2011). Local sleep in awake rats. Nature, 472(7344), 443-447.  https://doi.org/10.1038/nature10009 CrossRefGoogle Scholar
  64. Vyazovskiy, V. V., Olcese, U., Lazimy, Y. M., Faraguna, U., Esser, S. K., Williams, J. C., ... & Tononi, G. (2009). Cortical firing and sleep homeostasis. Neuron, 63(6), 865-878.  https://doi.org/10.1016/j.neuron.2009.08.024
  65. Wilken, P., & Ma, W. J. (2004). A detection theory account of change detection. Journal of Vision, 4(12), 11.  https://doi.org/10.1167/4.12.11 CrossRefGoogle Scholar
  66. Wilkinson, G. S., & Robertson, G. J. (2006). Wide range achievement test. (4th ed.) Odessa, FL: Psychological Assessment Resources.Google Scholar
  67. Zhang, W., & Luck, S. J. (2008). Discrete fixed-resolution representations in visual working memory. Nature, 453(7192), 233–235.  https://doi.org/10.1038/nature06860 CrossRefGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2018

Authors and Affiliations

  1. 1.Psychology DepartmentBrock UniversitySt. CatharinesCanada

Personalised recommendations